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  • 1.
    Jamil, Mohammad Newaj
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Expert System for Evaluating Technological Innovation Capability of High-Tech Firms Under Uncertainty2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), IEEE, 2019Conference paper (Refereed)
    Abstract [en]

    Technological innovation capability (TIC) is a complicated and subtle concept which is based on multiple quantitative and qualitative criteria. The cores of a firm’s long-term competitive dominance are defined by technological innovation capability which is the incentive for a firm’s innovation. Various types of uncertainty can be noticed while considering multiple criteria for evaluating TIC. In order to evaluate TIC in a reliable way, a Belief Rule Base (BRB) Expert System can be used to handle both quantitative and qualitative data and their associated uncertainties. In this paper, a RESTful API-based BRB expert system is introduced to evaluate technological innovation capability by taking uncertainties into consideration. This expert system will facilitate firms’ managers to obtain a recapitulation of the TIC evaluation. It will help them to take essential steps to ensure corporate survival and strengthen their weak capabilities continuously to facilitate a competitive advantage. Other users can also use this API to apply BRB for a different domain. However, a comparison between the knowledge-driven approach (BRBES) and several data-driven models has been performed to find out the reliability in evaluating TIC. The result shows that the outcome of BRBES is better than other data-driven approaches.

  • 2.
    Huang, Mingfeng
    et al.
    School of Information Science and Engineering, Central South University, Changsha 410083, China..
    Liu, Anfeng
    School of Information Science and Engineering, Central South University, Changsha 410083, China.
    Xiong, Neal N.
    Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, USA.
    Wang, Tian
    School of Computer Science, National Huaqiao University, Quanzhou 362000, China..
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Low-Latency Communication Scheme for Mobile Wireless Sensor Control Systems2019In: IEEE Transactions on Systems, Man & Cybernetics. Systems, ISSN 2168-2216, E-ISSN 1349-2543, Vol. 49, no 2, p. 317-332Article in journal (Refereed)
    Abstract [en]

    Millions of dedicated sensors are deployed in smart cities to enhance quality of urban living. Communication technologies are critical for connecting these sensors and transmitting events to sink. In control systems of mobile wireless sensor networks (MWSNs), mobile nodes are constantly moving to detect events, while static nodes constitute the communication infrastructure for information transmission. Therefore, how to communicate with sink quickly and effectively is an important research issue for control systems of MWSNs. In this paper, a communication scheme named first relay node selection based on fast response and multihop relay transmission with variable duty cycle (FRAVD) is proposed. The scheme can effectively reduce the network delay by combining first relay node selection with node duty cycles setting. In FRAVD scheme, first, for the first relay node selection, we propose a strategy based on fast response, that is, select the first relay node from adjacent nodes in the communication range within the shortest response time, and guarantee that the remaining energy and the distance from sink of the node are better than the average. Then for multihop data transmission of static nodes, variable duty cycle is introduced novelty, which utilizes the residual energy to improve the duty cycle of nodes in far-sink area, because nodes adopt a sleep-wake asynchronous mode, increasing the duty cycle can significantly improve network performance in terms of delays and transmission reliability. Our comprehensive performance analysis has demonstrated that compared with the communication scheme with fixed duty cycle, the FRAVD scheme reduces the network delay by 24.17%, improves the probability of finding first relay node by 17.68%, while also ensuring the network lifetime is not less than the previous researches, and is a relatively efficient low-latency communication scheme.

  • 3.
    Akter, Shamima
    et al.
    International Islamic University, Chittagong, Bangladesh.
    Nahar, Nazmun
    University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A New Crossover Technique to Improve Genetic Algorithm and Its Application to TSP2019In: Proceedings of 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), IEEE, 2019, article id 18566123Conference paper (Refereed)
    Abstract [en]

    Optimization problem like Travelling Salesman Problem (TSP) can be solved by applying Genetic Algorithm (GA) to obtain perfect approximation in time. In addition, TSP is considered as a NP-hard problem as well as an optimal minimization problem. Selection, crossover and mutation are the three main operators of GA. The algorithm is usually employed to find the optimal minimum total distance to visit all the nodes in a TSP. Therefore, the research presents a new crossover operator for TSP, allowing the further minimization of the total distance. The proposed crossover operator consists of two crossover point selection and new offspring creation by performing cost comparison. The computational results as well as the comparison with available well-developed crossover operators are also presented. It has been found that the new crossover operator produces better results than that of other cross-over operators.

  • 4.
    Safkhani, Masoumeh
    et al.
    Department of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A New Secure Authentication Protocol for Telecare Medicine Information Systemand Smart Campus2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 23514-23526Article in journal (Refereed)
    Abstract [en]

    Telecare Medicine Information System (TMIS)'s security importance attracts a lot of attention these days. Whatever the security of TMIS improves, its application becomes wider. To address this requirement, recently, Li et al. proposed a new privacy-preserving RFID authentication protocol for TMIS. After that, Zhou et al. and also Benssalah et al. presented their scheme, which is not secure, and they presented their new authentication protocol and claim that their proposal can provide higher security for TMIS applications. In this stream, Zheng et al. proposed a novel authentication protocol with application in smart campus, including TMIS. In this paper, we present an efficient impersonation and replay attacks against Zheng et al. with the success probability of 1 and a desynchronization attack which is applicable against all of the rest three mentioned protocols with the success probability of 1-2^{-n} , where n is the protocols parameters length. After that, we proposed a new protocol despite these protocols can resist the attacks presented in this paper and also other active and passive attacks. Our proposed protocol's security is also done both informally and formally through the Scyther tool.

  • 5.
    Lan, Yihua
    et al.
    School of Computer and Information Technology, Nanyang Normal University, Nanyang, China.
    Bai, Kun
    School of Computer and Information Technology, Nanyang Normal University, Nanyang, China..
    Hung, Chih-Cheng
    Laboratory for Machine Vision and Security Research, College of Computing and Software Engineering, Kennesaw State University, Marietta, USA.
    Alelaiwi, Abdulhameed
    Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Novel Definition of Equivalent Uniform Dose Based on Volume Dose Curve2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 45850-45857Article in journal (Refereed)
    Abstract [en]

    With the improvement of mobile device performance, the requirement of equivalent dose description in intensity-modulated radiation therapy is increasing in mobile multimedia for health-care. The emergence of mobile cloud computing will provide cloud servers and storage for IMRT mobile applications, thus realizing visualized radiotherapy in a real sense.Equivalent uniform dose (EUD) is a biomedical indicator based on the dose measure. In this study, the dose volume histogram is used to describe the dose distribution of different tissues in target and nontarget regions. The traditional definition of equivalent uniform dose such as the exponential form and the linear form has only a few parameters in the model for fast calculation. However, there is no close relationship between this traditional definition and the dose volume histogram.In order to establish the consistency between the equivalent uniform dose and the dose volume histogram, this paper proposes a novel definition of equivalent uniform dose based on the volume dose curve, called VD-EUD. By using a unique organic volume weight curve, it is easy to calculate VD-EUD for different dose distributions. In the definition, different weight curves are used to represent the biological effects of different organs. For the target area, we should be more careful about those voxels with low dose (cold point); thus, the weight curve is monotonically decreasing. While for the nontarget area, the curve is monotonically increasing. Furthermore, we present the curves for parallel, serial and mixed organs of nontarget areas separately, and we define the weight curve form with only two parameters. Medical doctors can adjust the curve interactively according to different patients and organs. We also propose a fluence map optimization model with the VD-EUD constraint, which means the proposed EUD constraint will lead to a large feasible solution space.We compare the generalized equivalent uniform dose (gEUD) and the proposed VD-EUD by experiments, which show that the VD-EUD has a closer relationship with the dose volume histogram. If the biological survival probability is equivalent to the VD-EUD, the feasible solution space would be large, and the target areas can be covered.By establishing a personalized organic weight curve, medical doctors can have a unique VD-EUD for each patient. By using the flexible and adjustable equivalent uniform dose definition, we can establish VD-EUD-based fluence map optimization model, which will lead to a larger solution space than the traditional dose volume constraint-based model. The VD-EUD is a new definition; thus, we need more clinical testing and verification.

  • 6.
    Chowdhury, Rumman Rashid
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Sazzad
    Department of Computer Science and Engineering, University of Liberal Arts Bangladesh, Dhaka, Bangladesh.
    Bangla Handwritten Character Recognition using Convolutional Neural Network with Data Augmentation2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), 2019Conference paper (Refereed)
    Abstract [en]

    This paper proposes a process of Handwritten Character Recognition to recognize and convert images of individual Bangla handwritten characters into electronically editable format, which will create opportunities for further research and can also have various practical applications. The dataset used in this experiment is the BanglaLekha-Isolated dataset [1]. Using Convolutional Neural Network, this model achieves 91.81% accuracy on the alphabets (50 character classes) on the base dataset, and after expanding the number of images to 200,000 using data augmentation, the accuracy achieved on the test set is 95.25%. The model was hosted on a web server for the ease of testing and interaction with the model. Furthermore, a comparison with other machine learning approaches is presented.

  • 7.
    Li, Jianjiang
    et al.
    Department of Computer Science and Technology, University of Science and Technology, Beijing.
    Zhang, Kai
    Department of Computer Science and Technology, University of Science and Technology, Beijing.
    Yang, Xiaolei
    Department of Computer Science and Technology, University of Science and Technology, Beijing.
    Wei, Peng
    Department of Computer Science and Technology, University of Science and Technology, Beijing.
    Wang, Jie
    Department of Computer Science and Technology, University of Science and Technology, Beijing.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Ranjan, Rajiv
    School of Computer Science, China University of Geosciences.
    Category Preferred Canopy-K-means based Collaborative Filtering algorithm2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 93, p. 1046-1054Article in journal (Refereed)
    Abstract [en]

    It is the era of information explosion and overload. The recommender systems can help people quickly get the expected information when facing the enormous data flood. Therefore, researchers in both industry and academia are also paying more attention to this area. The Collaborative Filtering Algorithm (CF) is one of the most widely used algorithms in recommender systems. However, it has difficulty in dealing with the problems of sparsity and scalability of data. This paper presents Category Preferred Canopy-K-means based Collaborative Filtering Algorithm (CPCKCF) to solve the challenges of sparsity and scalability of data. In particular, CPCKCF proposes the definition of the User-Item Category Preferred Ratio (UICPR), and use it to compute the UICPR matrix. The results can be applied to cluster the user data and find the nearest users to obtain prediction ratings. Our experimentation results performed using the MovieLens dataset demonstrates that compared with traditional user-based Collaborative Filtering algorithm, the proposed CPCKCF algorithm proposed in this paper improved computational efficiency and recommendation accuracy by 2.81%.

  • 8.
    Alhamazani, Khalid
    et al.
    School of Computer Science and Engineering, University of New South Wales.
    Ranjan, Rajiv
    CSIRO Digital Productivity, Acton.
    Jayaraman, Prem
    CSIRO Digital Productivity, Acton.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Liu, Chang
    Sydney University of Technology.
    Rabhi, Fethi
    School of Computer Science and Engineering, University of New South Wales.
    Georgakopoulos, Dimitrios
    Royal Melbourne Institute of Technology, Melbourne.
    Wang, Lizhe
    Chinese Academy of Sciences, Beijing.
    Cross-Layer Multi-Cloud Real-Time Application QoS Monitoring and Benchmarking As-a-Service Framework2019In: I E E E Transactions on Cloud Computing, ISSN 2168-7161, Vol. 7, no 1, p. 48-61Article in journal (Refereed)
    Abstract [en]

    Cloud computing provides on-demand access to affordable hardware (e.g., multi-core CPUs, GPUs, disks, and networking equipment) and software (e.g., databases, application servers and data processing frameworks) platforms with features such as elasticity, pay-per-use, low upfront investment and low time to market. This has led to the proliferation of business critical applications that leverage various cloud platforms. Such applications hosted on single/multiple cloud provider platforms have diverse characteristics requiring extensive monitoring and benchmarking mechanisms to ensure run-time Quality of Service (QoS) (e.g., latency and throughput). This paper proposes, develops and validates CLAMBS—Cross-Layer Multi Cloud Application Monitoring and Benchmarking as-a-Service for efficient QoS monitoring and benchmarking of cloud applications hosted on multi-clouds environments. The major highlight of CLAMBS is its capability of monitoring and benchmarking individual application components such as databases and web servers, distributed across cloud layers (*-aaS), spread among multiple cloud providers. We validate CLAMBS using prototype implementation and extensive experimentation and show that CLAMBS efficiently monitors and benchmarks application components on multi-cloud platforms including Amazon EC2 and Microsoft Azure.  

  • 9.
    Synnes, Kåre
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Artopoulos, Georgios
    The Cyprus Institute, Nicosia, Cyprus.
    Smaniotto Costa, Carlos
    Universidade Lusófona, Lisbon, Portugal.
    Menezes, Marluci
    National Laboratory for Civil Engineering – LNEC, Lisbon, Portugal.
    Redaelli, Gaia
    Politecnico di Milano, Milan, Italy.
    CyberParks Songs and Stories - Enriching Public Spaces with Localized Culture Heritage Material such as Digitized Songs and Stories: Enriching Public Spaces with Localized Culture Heritage Material such as Digitized Songs and Stories2019In: CyberParks - The Interface Between People, Places and Technology: New Approaches and Perspectives / [ed] Carlos Smaniotto Costa, Springer, 2019, p. 224-237Chapter in book (Refereed)
    Abstract [en]

    This chapter offers theoretical considerations and reflections on technological solutions that contribute to digitally supported documentation, access and reuse of localised heritage content in public spaces. It addresses immaterial cultural heritage, including informal stories that could emerge and be communicated by drawing hyperlinks between digitised assets, such as songs, images, drawings, texts and more, and not yet documented metadata, as well as augmenting interaction opportunities with interactive elements that relate to multiple media stored in databases and archives across Europe. The aim is to enable cultural heritage to be experienced in novel ways, supported by the proliferation of smartphones and ubiquitous Internet access together with new technical means for user profiling, personalisation, localisation, contextawareness and gamification. The chapter considers cyberparks as digitally enhanced public spaces for accessing and analyzing European cultural heritage and for enriching the interpretation of the past, along with theoretical ramifications and technological limitations. It identifies the capacities of a proposed digital environment together with design guidelines for interaction with cultural heritage assets in public spaces. The chapter concludes with describing a taxonomy of digital content that can be used in order to enhance association and occupation conditions of public spaces, and with discussing technological challenges associated with enriching public spaces with localized cultural heritage material.

  • 10.
    Wazid, Mohammad
    et al.
    Cyber Security and Networks Lab, Innopolis University, Innopolis, Russian Federation.
    Kumar Das, Ashok
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad, India.
    Kumar, Neeraj
    Department of Computer Science and Engineering, Thapar University, Patiala, India.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Rodrigues, Joel J. P. C.
    National Institute of Telecommunications (Inatel), Brazil; Instituto de Telecomunicações, Portugal; University of Fortaleza (UNIFOR), Brazil.
    Design and Analysis of Secure Lightweight Remote User Authentication and Key Agreement Scheme in Internet of Drones Deployment2019In: IEEE Internet of Things Journal, ISSN 2327-4662Article in journal (Refereed)
    Abstract [en]

    The Internet of Drones (IoD) provides a coordinated access to Unmanned Aerial Vehicles (UAVs) that are referred as drones. The on-going miniaturization of sensors, actuators, and processors with ubiquitous wireless connectivity makes drones to be used in a wide range of applications ranging from military to civilian. Since most of the applications involved in the IoD are real-time based, the users are generally interested in accessing real-time information from drones belonging to a particular fly zone. This happens if we allow users to directly access real-time data from flying drones inside IoD environment and not from the server. This is a serious security breach which may deteriorate performance of any implemented solution in this IoD environment. To address this important issue in IoD, we propose a novel lightweight user authentication scheme in which a user in the IoD environment needs to access data directly from a drone provided that the user is authorized to access the data from that drone. The formal security verification using the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool along with informal security analysis show that our scheme is secure against several known attacks. The performance comparison demonstrates that our scheme is efficient with respect to various parameters, and it provides better security as compared to those for the related existing schemes. Finally, the practical demonstration of our scheme is done using the widely-accepted NS2 simulation.

  • 11.
    Wazid, Mohammad
    et al.
    Cyber Security and Networks Lab, Innopolis University, Innopolis, Russian Federation.
    Kumar Das, Ashok
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad, India.
    Kumar, Neeraj
    Department of Computer Science and Engineering, Thapar University, Patiala, India.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Design of secure key management and user authentication scheme for fog computing services2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 91, p. 475-492Article in journal (Refereed)
    Abstract [en]

    Fog computing (fog networking) is known as a decentralized computing infrastructure in which data, applications, compute as well as data storage are scattered in the most logical and efficient place among the data source (i.e., smart devices) and the cloud. It gives better services than cloud computing because it has better performance with reasonably low cost. Since the cloud computing has security and privacy issues, and fog computing is an extension of cloud computing, it is therefore obvious that fog computing will inherit those security and privacy issues from cloud computing. In this paper, we design a new secure key management and user authentication scheme for fog computing environment, called SAKA-FC. SAKA-FC is efficient as it only uses the lightweight operations, such as one-way cryptographic hash function and bitwise exclusive-OR (XOR), for the smart devices as they are resource-constrained in nature. SAKA-FC is shown to be secure with the help of the formal security analysis using the broadly accepted Real-Or-Random (ROR) model, the formal security verification using the widely-used Automated Validation of Internet Security Protocols and Applications (AVISPA) tool and also the informal security analysis. In addition, SAKA-FC is implemented for practical demonstration using the widely-used NS2 simulator.

  • 12.
    Xu, Xiwei
    et al.
    Data61, CSIRO, Sydney, Australia. School of Computer Science and Engineering, UNSW, Sydney, Australia.
    Lu, Qinghua
    Data61, CSIRO, Sydney, Australia. School of Computer Science and Engineering, UNSW, Sydney, Australia.
    Liu, Yue
    College of Computer and Communication Engineering, China. University of Petroleum (East China), Qingdao, China.
    Zhu, Liming
    Data61, CSIRO, Sydney, Australia. School of Computer Science and Engineering, UNSW, Sydney, Australia.
    Yao, Haonan
    College of Computer and Communication Engineering, China. University of Petroleum (East China), Qingdao, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Designing blockchain-based applications a case study for imported product traceability2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 92, p. 399-406Article in journal (Refereed)
    Abstract [en]

    Blockchain technology enables decentralization as new forms of distributed software architectures, where components can reach agreements on the shared system states without trusting on a central integration point. Since blockchain is an emerging technology which is still at an early stage of development, there is limited experience on applying blockchain to real-world software applications. We applied blockchain application design approaches proposed in software architecture community in a real-world project called originChain, which is a blockchain-based traceability system that restructures the current system by replacing the central database with blockchain. In this paper, we share our experience of building originChain. By using blockchain and designing towards security, originChain provides transparent tamper-proof traceability data with high availability and enables automated regulatory-compliance checking and adaptation in product traceability scenarios. We also demonstrate both qualitative and quantitative analysis of the software architecture of originChain. Based on our experience and analysis, we found that the structural design of smart contracts has large impact on the quality of the system.

  • 13.
    Sakr, Sherif
    et al.
    University of Taru, Estonia.
    Zomaya, Albert
    University of Sydney, Australia.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Editorial for Special issue of FGCS special issue on “Benchmarking big data systems”2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 96, p. 32-34Article in journal (Refereed)
    Abstract [en]

    Even though several big data processing and analytics systems have been introduced with various design architectures, we are still lacking a deeper understanding of the performance characteristics for the various design architectures in addition to lacking comprehensive benchmarks for the various Big Data platforms. There is a crucial need to conduct fundamental research with a more comprehensive performance evaluation for the various Big Data processing systems and architectures. We also lack the availability of validation tools, standard benchmarks, and system performance prediction methods that can help us have a deeper and more solid understanding of the strengths and weaknesses of the various Big Data processing platforms. This special issue is dedicated to original results and achievements by active researchers, designers, and developers working on various issues and challenges related to big data research.

  • 14.
    Wu, Weiwei
    et al.
    School of Computer Science, Southeast University, Nanjing, Jiangsu, China.
    Wang, Wanyuan
    School of Computer Science and Engeering, Southeast University, Nanjing, Jiangsu China.
    Fang, Xiaolin
    Computer Science and Engineering, Harbin Institute of Technology, Harbin, Heilongjiang China.
    Junzhou, Luo
    School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Electricity Price-aware Consolidation Algorithms for Time-sensitive VM Services in Cloud Systems2019In: IEEE Transactions on Services Computing, ISSN 1939-1374, E-ISSN 1939-1374Article in journal (Refereed)
    Abstract [en]

    Despite the salient feature of cloud computing, the cloud provider still suffers from electricity bill, which mainly comes from 1) the power consumption of running physical machines and 2) the dynamically varying electricity price offered by smart grids. In the literature, there exist viable solutions adaptive to electricity price variation to reduce the electricity bill. However, they are not applicable to serving time-sensitive VM requests. In serving time-sensitive VM requests, it is potential for the cloud provider to apply proper consolidation strategies to further reduce the electricity bill. In this work, to address this challenge, we develop electricity-price-aware consolidation algorithms for both the offline and online scenarios. For the offline scenario, we first develop an consolidation algorithm with constant approximation, which always approaches the optimal solution within a constant factor of 5. For the online scenario, we propose an $O(\log(\frac{L_{max}}{L_{min}}))$ -competitive algorithm that is able to approach the optimal offline solution within a logarithmic factor, where $\frac{L_{max}}{L_{min}}$ is the ratio of the longest length of the processing time requirement of VMs to the shortest one. Our trace-driven simulation results further demonstrate that the average performance of the proposed algorithms produce near-optimal electricity bill.

  • 15.
    Fu, Zhangjie
    et al.
    Department of Computer and Software, Nanjing University of Information Science and Technology.
    Huang, Fengxiao
    Department of Computer and Software, Nanjing University of Information Science and Technology.
    Sun, Xingming
    Department of Computer and Software, Nanjing University of Information Science and Technology.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Enabling Semantic Search based on ConceptualGraphs over Encrypted Outsourced Data2019In: IEEE Transactions on Services Computing, ISSN 1939-1374, E-ISSN 1939-1374Article in journal (Refereed)
    Abstract [en]

    Currently, searchable encryption is a hot topic in the field of cloud computing. The existing achievements are mainly focused on keyword-based search schemes, and almost all of them depend on predefined keywords extracted in the phases of index construction and query. However, keyword-based search schemes ignore the semantic representation information of users’ retrieval and cannot completely match users’ search intention. Therefore, how to design a content-based search scheme and make semantic search more effective and context-aware is a difficult challenge. In this paper, for the first time, we define and solve the problems of semantic search based on conceptual graphs(CGs) over encrypted outsourced data in clouding computing (SSCG).We firstly employ the efficient measure of ”sentence scoring” in text summarization and Tregex to extract the most important and simplified topic sentences from documents. We then convert these simplified sentences into CGs. To perform quantitative calculation of CGs, we design a new method that can map CGs to vectors. Next, we rank the returned results based on ”text summarization score”. Furthermore, we propose a basic idea for SSCG and give a significantly improved scheme to satisfy the security guarantee of searchable symmetric encryption (SSE). Finally, we choose a real-world dataset – ie., the CNN dataset to test our scheme. The results obtained from the experiment show the effectiveness of our proposed scheme.

  • 16.
    Sun, Gang
    et al.
    Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China. Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu, China.
    Li, Yayu
    Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China.
    Yu, Hongfang
    Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China. Center for Cyber Security, University of Electronic Science and Technology of China, Chengdu, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Du, Xiaojiang
    Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA.
    Guizani, Mohsen
    Department of Electrical and Computer Engineering, University of Idaho, Moscow, ID, USA.
    Energy-efficient and traffic-aware service function chaining orchestration in multi-domain networks2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 91, p. 347-360Article in journal (Refereed)
    Abstract [en]

    Service function chaining (SFC) provisioning is helpful not only for saving the capital expenditure (CAPEX) and operational expenditure (OPEX) of a network provider but also for reducing energy consumption in the substrate network. However, to the best of our knowledge, there has been little research on the problem of energy consumption for orchestrating online SFC requests in multi-domain networks. In this paper, we first formulate the problem of an energy-efficient online SFC request that is orchestrated across multiple clouds as an integer linear programming (ILP) model to find an optimal solution. Then, we analyze the complexity of this ILP model and prove that the problem is NP-hard. Additionally, we propose a low-complexity heuristic algorithm named energy-efficient online SFC request orchestration across multiple domains (EE-SFCO-MD) for near-optimally solving the mentioned problem. Finally, we conduct simulation experiments to evaluate the performance of our algorithm. Simulation results show that EE-SFCO-MD consumes less energy than existing approaches while the online SFC’s requirements are met and the privacy of each cloud is effectively guaranteed. The low computational complexity of the heuristic approach makes it applicable for quickly responding to online SFC requests.

  • 17.
    Uddin Ahmed, Tawsin
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Bangladesh.
    Hossain, Sazzad
    Department of Computer Science and Engineering, University of Liberal Arts Bangladesh, Dhaka, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Facial Expression Recognition using Convolutional Neural Network with Data Augmentation2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), 2019Conference paper (Refereed)
    Abstract [en]

    Detecting emotion from facial expression has become an urgent need because of its immense applications in artificial intelligence such as human-computer collaboration, data-driven animation, human-robot communication etc. Since it is a demanding and interesting problem in computer vision, several works had been conducted regarding this topic. The objective of this research is to develop a facial expression recognition system based on convolutional neural network with data augmentation. This approach enables to classify seven basic emotions consist of angry, disgust, fear, happy, neutral, sad and surprise from image data. Convolutional neural network with data augmentation leads to higher validation accuracy than the other existing models (which is 96.24%) as well as helps to overcome their limitations.

  • 18.
    Makkie, Milad
    et al.
    Computer Science Department, University of Georgia, Athens, GA, USA.
    Huang, Heng
    School of Automation, Northwestern Polytechnical University, Xi'an, China.
    Zhao, Yu
    Computer Science Department, University of Georgia, Athens, GA, USA.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Liu, Tianming
    Harvard Center for Neurodegeneration and Repair, Boyd GSRC 420, Athens, GA 30602, United States.
    Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics2019In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 325, p. 20-30Article in journal (Refereed)
    Abstract [en]

    In recent years, analyzing task-based fMRI (tfMRI) data has become an essential tool for understanding brain function and networks. However, due to the sheer size of tfMRI data, its intrinsic complex structure, and lack of ground truth of underlying neural activities, modeling tfMRI data is hard and challenging. Previously proposed data modeling methods including Independent Component Analysis (ICA) and Sparse Dictionary Learning only provided shallow models based on blind source separation under the strong assumption that original fMRI signals could be linearly decomposed into time series components with corresponding spatial maps. Given the Convolutional Neural Network (CNN) successes in learning hierarchical abstractions from low-level data such as tfMRI time series, in this work we propose a novel scalable distributed deep CNN autoencoder model and apply it for fMRI big data analysis. This model aims to both learn the complex hierarchical structures of the tfMRI big data and to leverage the processing power of multiple GPUs in a distributed fashion. To deploy such a model, we have created an enhanced processing pipeline on the top of Apache Spark and Tensorflow, leveraging from a large cluster of GPU nodes over cloud. Experimental results from applying the model on the Human Connectome Project (HCP) data show that the proposed model is efficient and scalable toward tfMRI big data modeling and analytics, thus enabling data-driven extraction of hierarchical neuroscientific information from massive fMRI big data.

  • 19.
    Dadhich, Siddharth
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Sandin, Fredrik
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Bodin, Ulf
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Ulf
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Martinsson, Torbjörn
    Volvo CE, Bolindervägen 5, 63185 Eskilstuna, Sweden.
    Field test of neural-network based automatic bucket-filling algorithm for wheel-loaders2019In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 97, p. 1-12Article in journal (Refereed)
    Abstract [en]

    Automation of earth-moving industries (construction, mining and quarry) require automatic bucket-filling algorithms for efficient operation of front-end loaders. Autonomous bucket-filling is an open problem since three decades due to difficulties in developing useful earth models (soil, gravel and rock) for automatic control. Operators make use of vision, sound and vestibular feedback to perform the bucket-filling operation with high productivity and fuel efficiency. In this paper, field experiments with a small time-delayed neural network (TDNN) implemented in the bucket control-loop of a Volvo L180H front-end loader filling medium coarse gravel are presented. The total delay time parameter of the TDNN is found to be an important hyperparameter due to the variable delay present in the hydraulics of the wheel-loader. The TDNN network successfully performs the bucket-filling operation after an initial period (100 examples) of imitation learning from an expert operator. The demonstrated solution show only 26% longer bucket-filling time, an improvement over manual tele-operation performance.

  • 20.
    Yang, Chao-Tung
    et al.
    Department of Computer Science, Tunghai University, Taichung City, Taiwan, ROC.
    Chen, Shuo-Tsung
    Artificial Intelligence Recognition Industry Service Research Center (AIR-IS Research Center), National Yunlin University of Science and Technology, Yunlin, Taiwan, ROC. College of Future, Bachelor Program in Interdisciplinary Studies, National Yunlin University of Science and Technology, Taiwan, ROC.
    Liu, Jung-Chun
    Department of Computer Science, Tunghai University, Taichung City, Taiwan, ROC.
    Yang, Yao-Yu
    Department of Computer Science, Tunghai University, Taichung City, Taiwan, ROC.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Ranjan, Rajiv
    School of Computer, China University of Geosciences, China. School of Computing Science, Newcastle University, United Kingdom.
    Implementation of a real-time network traffic monitoring service with network functions virtualization2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 93, p. 687-701Article in journal (Refereed)
    Abstract [en]

    The Network Functions Virtualization (NFV) extends the functionality provided by Software-Defined Networking (SDN). It is a virtualization technology that aims to replace the functionality provided by traditional networking hardware using software solutions. Thereby, enabling cheaper and efficient network deployment and management. The use of NFV and SDN is anticipated to enhance the performance of Infrastructure-as-a-Service (IaaS) clouds. However, due to the presence of a large number of network devices in IaaS clouds offering a plethora of networked services, there is need to develop a traffic monitoring system for the efficient network. This paper proposes and validates an extensible SDN and NFV-enabled network traffic monitoring system. Using extensive experiments, we show that the proposed system can closely match the performance of traditional networks at cheaper costs and by adding more flexibility to network management tasks.

  • 21.
    Liu, Xiao
    et al.
    School of Information Science and Engineering, Central South University, ChangSha .
    Zhao, Shaona
    School of Information Science and Engineering, Central South University, ChangSha .
    Liu, Anfeng
    School of Information Science and Engineering, Central South University, ChangSha .
    Xiong, Naixue
    Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK .
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Knowledge-aware Proactive Nodes Selection approach for energy management in Internet of Things2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 92, p. 1142-1156Article in journal (Refereed)
    Abstract [en]

    Internet of Things will serve communities across the different domains of life. Tracking mobile targets is one important system engineering application in IOT, and the resource of embedded devices and objects working under IoT implementation are constrained. Thus, building a scheme to make full use of energy is key issue for mobile target tracking applications. To achieve both energy efficiency and high monitoring performance, an effective Knowledge-aware Proactive Nodes Selection (KPNS) system is proposed in this paper. The innovations of KPNS are as follows: 1) the number of proactive nodes are dynamically adjusted based on prediction accuracy of target trajectory. If the prediction accuracy is high, the number of proactive nodes in the non-main predicted area will be decreased. If prediction accuracy of moving trajectory is low, large number of proactive nodes will be selected to enhance monitoring quality. 2) KPNS takes full advantage of energy to further enhance target tracking performance by properly selecting more proactive nodes in the network. We evaluated the efficiency of KPNS with both theory analysis and simulation based experiments. The experimental results demonstrate that compared with Probability-based target Prediction and Sleep Scheduling strategy (PPSS), KPNS scheme improves the energy efficiency by 60%, and can reduce target missing rate and tracking delay to 66%, 75% respectively.

  • 22.
    Song, Qiang
    et al.
    Henan University of Technology, College of Electrical Engineering, Zhengzhou, China.
    Liu, Fang
    Huanghuai University, Zhumadian, China.
    Cao, Jinde
    Southeast University, Research Center for Complex Systems and Network Sciences, Nanjing, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Tang, Yang
    East China University of Science and Technology, Institute of Physics, Berlin, Germany.
    Leader-following synchronization of coupled homogeneous and heterogeneous harmonic oscillators based on relative position measurements2019In: IEEE Transactions on Control of Network Systems, ISSN 2325-5870, Vol. 6, no 1, p. 13-23Article in journal (Refereed)
    Abstract [en]

    This paper considers the leader-following synchronization problem for a network of coupled harmonic oscillators by utilizing the relative position measurements between neighboring nodes, where the node dynamics can be either identical or nonidentical. For a homogeneous network with the same node dynamics, two types of first-order observer-based protocols are proposed to achieve leader-following synchronization in the network under some necessary and sufficient conditions, including some synchronization criteria for the homogeneous network subject to parameter uncertainty. For a heterogeneous network with different node dynamics, an output regulation approach is applied to solve the leader-following synchronization problem for the nominal network, based on which the robust synchronization of the uncertain network is investigated with an allowable bound being estimated for parameter uncertainties. Numerical examples are given to illustrate the correctness and the feasibility of the theoretical analysis. 

  • 23.
    Seo, Jungryul
    et al.
    Ajou University.
    Laine, Teemu H.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Sohn, Kyung-Ah
    Ajou University.
    Machine learning approaches for boredom classification using EEG2019In: Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, E-ISSN 1868-5145Article in journal (Refereed)
    Abstract [en]

    Recently, commercial physiological sensors and computing devices have become cheaper and more accessible, while computer systems have become increasingly aware of their contexts, including but not limited to users’ emotions. Consequently, many studies on emotion recognition have been conducted. However, boredom has received relatively little attention as a target emotion due to its diverse nature. Moreover, only a few researchers have tried classifying boredom using electroencephalogram (EEG). In this study, to perform this classification, we first reviewed studies that tried classifying emotions using EEG. Further, we designed and executed an experiment, which used a video stimulus to evoke boredom and non-boredom, and collected EEG data from 28 Korean adult participants. After collecting the data, we extracted its absolute band power, normalized absolute band power, differential entropy, differential asymmetry, and rational asymmetry using EEG, and trained these on three machine learning algorithms: support vector machine, random forest, and k-nearest neighbors (k-NN). We validated the performance of each training model with 10-fold cross validation. As a result, we achieved the highest accuracy of 86.73% using k-NN. The findings of this study can be of interest to researchers working on emotion recognition, physiological signal processing, machine learning, and emotion-aware system development.

  • 24.
    Li, He
    et al.
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Ota, Kaoru
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Dong, Mianxiong
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Nagano, Koji
    Department of Information and Electronic Engineering, Muroran Institute of Technology, Muroran, Hokkaido.
    Multimedia Processing Pricing Strategy in GPU-accelerated Cloud Computing2019In: IEEE Transactions on Cloud Computing, E-ISSN 2168-7161Article in journal (Refereed)
    Abstract [en]

    Graphics processing unit (GPU) accelerated processing performs significant efficiency in many multimedia applications. With the development of GPU cloud computing, more and more cloud providers focus on GPU-accelerated services. Since the high maintenance cost and different speedups for various applications, GPU-accelerated services still need a different pricing strategy. Thus, in this paper, we propose an optimal GPU-accelerated multimedia processing service pricing strategy for maximize the profits of both cloud provider and users. We first analyze the revenues and costs of the cloud provider and users when users adopt GPU-accelerated multimedia processing services then state the profit functions of both the cloud provider and users. With a game theory based method, we find the optimal solutions of both the cloud provider’s and users’ profit functions. Finally, through large scale simulations, our pricing strategy brings higher profit to the cloud provider and users compared to the original pricing strategy of GPU cloud services.

  • 25.
    Dong, Pingping
    et al.
    Hunnan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, China.
    Xie, Jingyun
    Hunnan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, China.
    Tang, Wensheng
    Hunnan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, China.
    Xiong, Naixue
    College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China.
    Zhong, Hua
    Hunnan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, Hunan Normal University, Changsha, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Performance Evaluation of Multipath TCP Scheduling Algorithms2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 29818-29825Article in journal (Refereed)
    Abstract [en]

    One of the goals of 5G is to provide enhanced mobile broadband and enable low latency in some use cases. To achieve this aim, the Internet Engineering Task Force (IETF) has proposed the Multipath TCP (MPTCP) by utilizing the feature of dual connectivity in 5G, where a 5G device can be served by two different base stations. However, the path heterogeneity between the 5G device to the server may cause packet out-of-order problem. The researchers proposed a number of scheduling algorithms to tackle this issue. This paper introduces the existing algorithms, and with the aim to make a thorough comparison between the existing scheduling algorithms and provide guidelines for designing new scheduling algorithms in 5G, we have conducted an extensive set of emulation studies based on the real Linux experimental platform. The evaluation covers a wide range of network scenarios to investigate the impact of different network metrics, namely, RTT, buffer size and file size on the performance of existing widely-deployed scheduling algorithms.

  • 26. de Lange, Michiel
    et al.
    Synnes, Kåre
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Leindecker, Gerald
    Smart Citizens in the Hackable City: On the Datafication, Playfulness, and Making of Urban Public Spaces Through Digital Art2019In: CyberParks – The Interface Between People, Places and Technology: New Approaches and Perspectives / [ed] Carlos Smaniotta Costa, Springer, 2019, p. 157-166Chapter in book (Refereed)
    Abstract [en]

    This contribution explores concepts, approaches and technologies used to make urban public spaces more playful and artful. Through a variety of compelling narratives involving play and art it assists in the design of new cyberparks, public spaces where digitally mediated interactions are an inherent part. How can play and interactive art be used to strengthen urban public spaces by fostering citizen engagement and participation? We propose to not only utilise interactive media for designing urban (public) spaces, but also for social innovation for the benefit of citizens. in cyberparks. The contribution connects urbanity, play and games, as well as concepts of active and passive interactive digital art as part of trends towards pervasive urban interaction, gameful design and artification. We position this as an important part of developing human-centred smart cities where social capital is central, and where citizens engaging in play and art are prerequisites for sustainable communities. Using art, play and games to foster citizen engagement and collaboration is a means to develop social technologies and support the development of collective intelligence in cyberparks. This is studied in concrete cases, such as the Ice Castle in Luleå, Sweden and the Ars Electronica in Linz, from a multi-disciplinary stance involving interaction design, digital art, landscape design, architecture, and health proficiencies. We will analyse two cases of gameful design and one case of digital interactive art being used to address urban issues. Rezone the game is an interactive multimedia game developed to tackle vacancy in the city of Den Bosch in the Netherlands. The Neighbourhood is a board game developed to involve various stakeholders in making their neighbourhood using water as a collective resource.

  • 27.
    Lemlouma, T.
    et al.
    University of Rennes 1, Rennes, France.
    Laborie, S.
    University of Pau and Adour Countries, Anglet, France.
    Rachedi, A.
    University of Paris-Est Marne la Vallée, Champs-sur-Marne, France.
    Santos, A.
    Vestas, Leça do Balio, Porto, Portugal.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Special issue on selected papers from e-health pervasive wireless applications and services 20172019In: Information Science and Technology, ISSN 2078-2489, E-ISSN 2078-2489, Vol. 10, no 2, article id 52Article in journal (Refereed)
  • 28.
    Islam, Md. Zahirul
    et al.
    Department of Computer Science and Engineering University of Chittagong, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Static Hand Gesture Recognition using Convolutional Neural Network with Data Augmentation2019In: Proceedings of the Joint 2019 8th International Conference on Informatics, Electronics & Vision (ICIEV), IEEE, 2019Conference paper (Refereed)
    Abstract [en]

    Computer is a part and parcel in our day to day life and used in various fields. The interaction of human and computer is accomplished by traditional input devices like mouse, keyboard etc. Hand gestures can be a useful medium of human-computer interaction and can make the interaction easier. Gestures vary in orientation and shape from person to person. So, non-linearity exists in this problem. Recent research has proved the supremacy of Convolutional Neural Network (CNN) for image representation and classification. Since, CNN can learn complex and non-linear relationships among images, in this paper, a static hand gesture recognition method using CNN was proposed. Data augmentation like re-scaling, zooming, shearing, rotation, width and height shifting was applied to the dataset. The model was trained on 8000 images and tested on 1600 images which were divided into 10 classes. The model with augmented data achieved accuracy 97.12% which is nearly 4% higher than the model without augmentation (92.87%).

  • 29.
    Liu, Ling
    et al.
    Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;University of Chinese Academy of Sciences, Beijing, China.
    Zhou, Yiqing
    Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;University of Chinese Academy of Sciences, Beijing, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Tian, Lin
    Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;University of Chinese Academy of Sciences, Beijing, China.
    Shi, Jinglin
    Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;University of Chinese Academy of Sciences, Beijing, China.
    Time-domain ICIC and optimized designs for 5G and beyond: a survey2019In: Science China Information Sciences, ISSN 1674-733X, E-ISSN 1869-1919, Vol. 62, no 2, article id 21302Article in journal (Refereed)
    Abstract [en]

    Time-domain enhanced inter-cell interference coordination (eICIC) is an effective technique to reduce the cross-tier inter-cell interference (ICI) in long term evolution (LTE)-based heterogeneous small cell networks (HetSCNs). This paper first clarifies two main communication scenarios in HetSCNs, i.e., macrocells deployed with femtocells (macro-femto) and with picocells (macro-pico). Then, the main challenges in HetSCNs, particularly the severe cross-tier ICI in macro-femto caused by femtocells with closed subscribe group (CSG) access or in macro-pico caused by picocells with range expansion are analyzed. Based on the prominent feature of dominant interference in HetSCNs, the main idea of time-domain interference coordination and two basic schemes in the eICIC standardization, i.e., almost blank subframe (ABS) and orthogonal frequency division multiplexing symbol shift are presented, with a systematic introduction to the interactions of these techniques with other network functions. Then, given macro-femto and macro-pico HetSCNs, an overview is provided on the advanced designs of ABS-based eICIC, including self-optimized designs with regard to key parameters such as ABS muting ratio, and joint optimized designs of ABS-based eICIC and other radio resource management techniques, such as user association and power control. Finally, the open issues and future research directions are discussed.

  • 30.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Al Hasan, Abdullah
    University of Chittagong, Bangladesh.
    Guha, Sunanda
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Expert System to Predict Earthquake under Uncertainty2018In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, ISSN 2093-5374, E-ISSN 2093-5382, Vol. 9, no 2, p. 26-41Article in journal (Refereed)
    Abstract [en]

    The impact of earthquake is devastating, which has the capability to stop the socio-economic activities of a region within a short span of time. Therefore, an earlier prediction of earthquake could play an important role to save human lives as well as socio-economic activities. The signs of animal behavior along with environmental and chemical changes in nature could be considered as a way to predict the earthquake. These factors cannot be determined accurately because of the presence of different categories of uncertainties. Therefore, this article presents a belief rule based expert system (BRBES) which has the capability to predict earthquake under uncertainty. Historical data of various earthquakes of the world with specific reference to animal behavior as well as environmental and chemical changes have been considered in validating the BRBES. The reliability of our proposed BRBES’s output is measured in comparison with Fuzzy Logic Based Expert System (FLBES) and Artificial Neural Networks (ANN) based system, whereas our BRBES’s results are found more reliable than that of FLBES and ANN. Therefore, this BRBES can be considered to predict the occurrence of an earthquake in a region by taking account of the data, related to the animal, environmental and chemical changes.

  • 31.
    Monrat, Ahmed Afif
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Flood Risk Assessment Expert System using Real Time Sensor Data Streaming2018In: Proveedings of the 43nd IEEE Conference on Local Computer Networks Workshops (LCN Workshops), IEEE Computer Society, 2018Conference paper (Refereed)
    Abstract [en]

    Among the various natural calamities, flood is considered one of the most catastrophic natural hazards, which has a significant impact on the socio-economic lifeline of a country. The Assessment of flood risks facilitates taking appropriate measures to reduce the consequences of flooding. The flood risk assessment requires Big data which are coming from different sources, such as sensors, social media, and organizations. However, these data sources contain various types of uncertainties because of the presence of incomplete and inaccurate information. This paper presents a Belief rule-based expert system (BRBES) which is developed in Big data platform to assess flood risk in real time. The system processes extremely large dataset by integrating BRBES with Apache Spark while a web-based interface has developed allowing the visualization of flood risk in real time. Since the integrated BRBES employs knowledge driven learning mechanism, it has been compared with other data-driven learning mechanisms to determine the reliability in assessing flood risk. The integrated BRBES produces reliable results in comparison to other data-driven approaches. Data for the expert system has been collected by considering different case study areas of Bangladesh to validate the system.

  • 32.
    Hossain, Mohammad Shahadat
    et al.
    University of Chittagong, Bangladesh.
    Rahaman, Saifur
    International Islamic University Chittagong.
    Mustafa, Rashed
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A belief rule-based expert system to assess suspicion of acute coronary syndrome (ACS) under uncertainty2018In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 22, no 22, p. 7571-7586Article in journal (Refereed)
    Abstract [en]

    Acute coronary syndrome (ACS) is responsible for the obstruction of coronary arteries, resulting in the loss of lives. The onset of ACS can be determined by looking at the various signs and symptoms of a patient. However, the accuracy of ACS determination is often put into question since there exist different types of uncertainties with the signs and symptoms. Belief rule-based expert systems (BRBESs) are widely used to capture uncertain knowledge and to accomplish the task of reasoning under uncertainty by employing belief rule base and evidential reasoning. This article presents the process of developing a BRBES to determine ACS predictability. The BRBES has been validated against the data of 250 patients suffering from chest pain. It is noticed that the outputs created from the BRBES are more dependable than that of the opinion of cardiologists as well as other two expert system tools, namely artificial neural networks and support vector machine. Hence, it can be argued that the BRBES is capable of playing an important role in decision making as well as in avoiding costly laboratory investigations. A procedure to train the system, allowing its enhancement of performance, is also presented.

  • 33.
    Yin, Lihua
    et al.
    State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, .
    Guo, Yunchuan
    State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing.
    Li, Fenghua
    State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing.
    Sun, Yanwei
    State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing .
    Qian, Junyan
    Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A game-theoretic approach to advertisement dissemination in ephemeral networks2018In: World wide web (Bussum), ISSN 1386-145X, E-ISSN 1573-1413, Vol. 21, no 2, p. 241-260Article in journal (Refereed)
    Abstract [en]

    In ephemeral networks, disseminating advertisements faces two dilemmatic problems: on the one hand, disseminators own the limited resources and have privacy concerns, thus, often preferring to avoid disseminating advertisements without enough incentives; Even if advertisements are disseminated, their dissemination accuracy is lower. On the other hand, false advertisements may flood in ephemeral networks if too many incentives but no punishments are given. Thus, it is a challenge to design an effective scheme to guarantee rational disseminators have sufficient impetus to forward true advertisements to the interested consumers and report false advertisements, despite facing the limitation of resources and the risk of privacy leakage. To solve this problem, in this paper, a bargaining-based scheme is proposed to motive disseminators to forward the true advertisements to the interested node and a semi-grim policy is designed for punishing the disseminators who releases and disseminates false advertisements. Acknowledging the assumption of incomplete information, a repeated dissemination game is proposed to help disseminators to decide whether to forward advertisements or report false advertisements. Simulation results demonstrate that our scheme not only provides disseminators a strong impetus to disseminate the advertisements with higher dissemination accuracy, but also effectively prevents disseminators from forwarding false advertisements.

  • 34.
    Espinilla, Macarena
    et al.
    Department of Computer Science, University of Jaén, Jaén, Spain.
    Medina, Javier
    Department of Computer Science, University of Jaén, Jaén, Spain.
    Hallberg, Josef
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Nugent, Chris
    School of Computing and Mathematics, Ulster University, Coleraine, UK.
    A new approach based on temporal sub-windows for online sensor-based activity recognition2018In: Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, E-ISSN 1868-5145Article in journal (Refereed)
    Abstract [en]

    Usually, approaches driven by data proposed in literature for sensor-based activity recognition use the begin label and the end label of each activity in the dataset, fixing a temporal window with sensor data events to identify the activity carried out in this window. This type of approach cannot be carried out in real time because it is not possible to predict the start time of an activity, i.e., the class of the future activity that an inhabitant will perform, neither when he/she will begin to carry out this activity. However, an activity can be marked as finished in real time only with the previous observations. Therefore, there is a need of online activity recognition approaches that classify activities using only the end label of the activity. In this paper, we propose and evaluate a new approach for online activity recognition with three temporal sub-windows that uses only the end label of the activity. The advantage of our approach is that the temporal sub-windows keep a partial order in the sensor data stream from the end time of the activity in a short-term, medium-term, long-term. The experiments conducted to evaluate our approach suggest the importance of the use of temporal sub-windows versus a single temporal window in terms of accuracy, using only the end time of the activity. The use of temporal sub-windows has improved the accuracy in the 98.95% of experiments carried out.

  • 35.
    Islam, Raihan Ul
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering, University of Chittagong, Chittagong 4331, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A novel anomaly detection algorithm for sensor data under uncertainty2018In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 22, no 5, p. 1623-1639Article in journal (Refereed)
    Abstract [en]

    It is an era of Internet of Things, where various types of sensors, especially wireless, are widely used to collect huge amount of data to feed various systems such as surveillance, environmental monitoring, and disaster management. In these systems, wireless sensors are deployed to make decisions or to predict an event in a real-time basis. However, the accuracy of such decisions or predictions depends upon the reliability of the sensor data. Unfortunately, erroneous data are received from the sensors. Consequently, it hampers the appropriate operations of the mentioned systems, especially in making decisions and prediction. Therefore, the detection of anomaly that exists with the sensor data drew significant attention and hence, it needs to be filtered before feeding a system to increase its reliability in making decisions or prediction. There exists various sensor anomaly detection algorithms, but few of them are able to address the uncertain phenomenon, associated with the sensor data. If these uncertain phenomena cannot be addressed by the algorithms, the filtered data into the system will not be able to increase the reliability of the decision-making process. These uncertainties may be due to the incompleteness, ignorance, vagueness, imprecision and ambiguity. Therefore, in this paper we propose a new belief-rule-based association rule (BRBAR) with the ability to handle the various types of uncertainties as mentioned.The reliability of this novel algorithm has been compared with other existing anomaly detection algorithms such as Gaussian, binary association rule and fuzzy association rule by using sensor data from various domains such as rainfall, temperature and cancer cell data. Receiver operating characteristic curves are used for comparing the performance of our proposed BRBAR with the aforementioned algorithms. The comparisons demonstrate that BRBAR is more accurate and reliable in detecting anomalies from sensor data under uncertainty. Hence, the use of such algorithm to feed the decision-making systems could be beneficial. Therefore, we have used this algorithm to feed appropriate sensor data to our recently developed belief-rule-based expert system to predict flooding in an area. Consequently, the reliability and the accuracy of the flood prediction system increase significantly. Such novel algorithm (BRBAR) can be used in other areas of applications. 

  • 36.
    Wazid, Mohammad
    et al.
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad, Hyderabad India 500032 .
    Kumar Das, Ashok
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad, Hyderabad India 500032 .
    Kumar, Neeraj
    Department of Computer Science and Engineering, Thapar University, Patiala, Patiala, Punjab India .
    Conti, Mauro
    Department of Mathematics, University of Padua, Padua, Padua Italy .
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Novel Authentication and Key Agreement Scheme for Implantable Medical Devices Deployment2018In: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208, Vol. 2, no 4, p. 1299-1309Article in journal (Refereed)
    Abstract [en]

    Implantable medical devices (IMDs) are man-made devices, which can be implanted in the human body to improve the functioning of various organs. The IMDs monitor and treat physiological condition of the human being (for example, monitoring of blood glucose level by insulin pump). The advancement of information and communication technology (ICT) enhances the communication capabilities of IMDs. In healthcare applications, after mutual authentication, a user (for example, doctor) can access the health data from the IMDs implanted in a patient's body. However, in this kind of communication environment, there are always security and privacy issues such as leakage of health data and malfunctioning of IMDs by an unauthorized access.

  • 37.
    Lee, Cheng-Chi
    et al.
    Department of Library and Information Science, Fu Jen Catholic University, New Taipei City, Taiwan, Republic of China; Department of Photonics and Communication Engineering, Asia University, Taichung, Taiwan, Republic of China.
    Li, Chun-Ta
    Department of Information Management, Tainan University of Technology, Tainan, Taiwan, Republic of China.
    Cheng, Chung-Lun
    Department of Library and Information Science, Fu Jen Catholic University, New Taipei City, Taiwan, Republic of China.
    Lai, Yan-Ming
    Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, Republic of China.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Novel Group Ownership Delegate Protocol for RFID Systems2018In: Information Systems Frontiers, ISSN 1387-3326, E-ISSN 1572-9419Article in journal (Refereed)
    Abstract [en]

    In recent years, Radio Frequency Identification (RFID) applications of various kinds have been blooming. However, along with the stunning advancement have come all sorts of security and privacy issues, for RFID tags oftentimes store private data and so the permission to read a tag or any other kind of access needs to be carefully controlled. Therefore, of all the RFID-related researches released so far, a big portion focuses on the issue of authentication. There have been so many cases where the legal access to or control over a tag needs to be switched from one reader to another, which has encouraged the development of quite a number of different kinds of ownership transfer protocols. On the other hand, not only has the need for ownership transfer been increasing, but a part of it has also been evolving from individual ownership transfer into group ownership transfer. However, in spite of the growing need for practical group ownership transfer services, little research has been done to offer an answer to the need. In this paper, we shall present a new RFID time-bound group ownership delegate protocol based on homomorphic encryption and quadratic residues. In addition, in order to provide more comprehensive service, on top of mutual authentication and ownership delegation, we also offer options for the e-th time verification as well as the revocation of earlier delegation.

  • 38.
    Zhang, Shengzhi
    et al.
    Florida Institute of Technology, Melbourne, FL.
    Makke, Omar
    Ford Motor, Detroit, MI.
    Gusikhin, Oleg Yu
    Ford Motor, Detroit, MI.
    Shah, Ayush
    Ford Motor, Detroit, MI.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A security model for dependable vehicle middleware and mobile applications connection2018In: VEHITS 2018: Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems / [ed] Gusikhin O.,Helfert M., 2018, p. 379-386Conference paper (Refereed)
    Abstract [en]

    Nowadays automotive industry has been working on the connectivity between automobile and smartphones, e.g., Ford’s SmartDeviceLink, MirrorLink, etc. However, as the interoperability between the smartphone and automotive system increase, the security concern of the increased attack surface bothers the automotive industry as well as the security community. In this paper, we thoroughly study the attack vectors against the novel connection framework between automobile and smartphones, and propose a generic security model to implement a dependable connection to eliminate the summarized attack vectors. Finally, we present how our proposed model can be integrated into existing automotive framework, and discuss the security benefits of our model. Copyright

  • 39.
    Seo, Jungryul
    et al.
    Ajou University.
    Laine, Teemu H.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Accurate position and orientation independent step counting algorithm for smartphones2018In: Journal of Ambient Intelligence and Smart Environments, ISSN 1876-1364, E-ISSN 1876-1372, Vol. 10, no 6, p. 481-495Article in journal (Refereed)
    Abstract [en]

    Step counting (SC) algorithms can be applied to different areas such as well-being applications, games, and indoor navigation. Many existing SC algorithms for smartphones use data from inertial sensors to infer the number of steps taken, but their usefulness in real-life situations is limited since typically only a few positions and orientations are supported. Moreover, the algorithms may suffer from dynamic orientation and position changes during walking. To alleviate these shortcomings, we propose the Position and Orientation Independent Step Counting Algorithm (POISCA), which uses an accelerometer and a gyroscope to count the number of steps while allowing the smartphone’s position and orientation to change dynamically. In a nutshell, the algorithm first determines the orientation of the smartphone, and then detects zero crossings with a predetermined buffer range. 48 young adults (36 males, 12 females) participated in an experiment that simulated a real-life scenario to evaluate the performance of POISCA against three other step counting algorithms. The data from 24 participants were randomly assigned to a training group, which was then used to establish threshold parameters for POISCA. The remaining 24 participants’ data were used for accuracy measurement. The results show that POISCA outperforms the other algorithms with a Symmetric Mean Absolute Percentage Error of 4.54%, which can be lower if the algorithm is calibrated for each user. The results suggest that POISCA has potential for use in real-life situations where changes in position and orientation of the smartphone are dynamic.

  • 40.
    Johansson, Ingemar
    et al.
    Ericsson AB, Luleå.
    Dadhich, Siddharth
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Bodin, Ulf
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Jönsson, Tomas
    Ericsson AB, Luleå.
    Adaptive Video with SCReAM over LTE for Remote-Operated Working Machines2018In: Wireless Communications & Mobile Computing, ISSN 1530-8669, E-ISSN 1530-8677, Vol. 2018, article id 3142496Article in journal (Refereed)
    Abstract [en]

    Remote operation is a step toward the automation of mobile working machines. Safe and efficient teleremote operation requires good-quality video feedback. Varying radio conditions make it desirable to adapt the video sending rate of cameras to make the best use of the wireless capacity. The adaptation should be able to prioritize camera feeds in different directions depending on motion, ongoing tasks, and safety concerns. Self-Clocked Rate Adaptation for Multimedia (SCReAM) provides a rate adaptation algorithm for these needs. SCReAM can control the compression used for multiple video streams using differentiating priorities and thereby provide sufficient congestion control to achieve both low latency and high video throughput. We present results from the testing of prioritized adaptation of four video streams with SCReAM over LTE and discuss how such adaptation can be useful for the teleremote operation of working machines.

  • 41.
    Khan, Zaheer
    et al.
    Centre for Wireless Communications, University of Oulu.
    Lehtomäki, Janne
    Centre for Wireless Communications, University of Oulu.
    Vasilakos, Athanasios V.
    Centre for Wireless Communications, University of Oulu.
    MacKenzie, Allen B.
    Centre for Wireless Communications, University of Oulu.
    Juntti, Markku
    Centre for Wireless Communications, University of Oulu.
    Adaptive wireless communications under competition and jamming in energy constrained networks2018In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 24, no 1, p. 151-171Article in journal (Refereed)
    Abstract [en]

    We propose a framed slotted Aloha-based adaptive method for robust communication between autonomous wireless nodes competing to access a channel under unknown network conditions such as adversarial disruptions. With energy as a scarce resource, we show that in order to disrupt communications, our method forces the reactive adversary to incur higher energy cost relative to a legitimate node. Consequently, the adversary depletes its energy resources and stops attacking the network. Using the proposed method, a transmitter node changes the number of selected time slots and the access probability in each selected time slot based on the number of unsuccessful transmissions of a data packet. On the receiver side, a receiver node changes the probability of listening in a time slot based on the number of unsuccessful communication attempts of a packet. We compare the proposed method with two other framed slotted Aloha-based methods in terms of average energy consumption and average time required to communicate a packet. For performance evaluation, we consider scenarios in which: (1) Multiple nodes compete to access a channel. (2) Nodes compete in the presence of adversarial attacks. (3) Nodes compete in the presence of channel errors and capture effect.

  • 42.
    Dinh, Thanh
    et al.
    School of Electronic Engineering, Soongsil University, Seoul 06978, South Korea.
    Kim, Younghan
    School of Electronic Engineering, Soongsil University, Seoul 06978, South Korea.
    Gu, Tau
    School of Computer Science, Royal Melbourne Institute of Technology University, Melbourne.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An Adaptive Low-Power Listening Protocol for Wireless Sensor Networks in Noisy Environments2018In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 2, no 3, p. 2162-2173Article in journal (Refereed)
    Abstract [en]

    This paper investigates the energy consumption minimizationproblem for wireless sensor networks running low-powerlistening (LPL) protocols in noisy environments. We observe thatthe energy consumption by false wakeups (i.e., wakeup without receivingany packet) of a node in noisy environments can be a dominantfactor in many cases while the false wakeup rate is spatiallyand temporarily dynamic. Based on this observation, without carefullyconsidering the impact of false wakeups, the energy efficientperformance of LPL nodes in noisy environments may significantlydeviate from the optimal performance. To address this problem,we propose a theoretical framework incorporating LPL temporalparameters with the false wakeup rate and the data rate. We thenformulate an energy consumption minimization problem of LPLin noisy environments and address the problem by a simplifiedand practical approach. Based on the theoretical framework, wedesign an efficient adaptive protocol for LPL (APL) in noisy environments.Through extensive experimental studies with Telosbnodes in real environments, we show that APL achieves 20%–40%energy efficient improvement compared to existing LPL protocolsunder various network conditions.

  • 43.
    Alam, Md. Eftekhar
    et al.
    International Islamic University Chittagong, Bangladesh.
    Kaiser, M. Shamim
    Jahangirnagar University, Dhaka, Bangladesh.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An IoT-Belief Rule Base Smart System to Assess Autism2018In: Proceedings of the 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT 2018), IEEE, 2018, p. 671-675Conference paper (Refereed)
    Abstract [en]

    An Internet-of-Things (IoT)-Belief Rule Base (BRB) based hybrid system is introduced to assess Autism spectrum disorder (ASD). This smart system can automatically collect sign and symptom data of various autistic children in realtime and classify the autistic children. The BRB subsystem incorporates knowledge representation parameters such as rule weight, attribute weight and degree of belief. The IoT-BRB system classifies the children having autism based on the sign and symptom collected by the pervasive sensing nodes. The classification results obtained from the proposed IoT-BRB smart system is compared with fuzzy and expert based system. The proposed system outperformed the state-of-the-art fuzzy system and expert system.

  • 44.
    alam, M.E.
    et al.
    Electrical Electronic Engineering, International Islamic University, Chittagong, Bangladesh.
    Kaiser, M. Shamim
    Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh.
    Hossain, M.S.
    Computer Science Engineering, University of Chittagong, Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An IoT-belief rule base smart system to assess autism2018Conference paper (Refereed)
    Abstract [en]

    An Internet-of-Things (IoT)-Belief Rule Base (BRB) based hybrid system is introduced to assess Autism spectrum disorder (ASD). This smart system can automatically collect sign and symptom data of various autistic children in real-time and classify the autistic children. The BRB subsystem incorporates knowledge representation parameters such as rule weight, attribute weight and degree of belief. The IoT-BRB system classifies the children having autism based on the sign and symptom collected by the pervasive sensing nodes. The classification results obtained from the proposed IoT-BRB smart system is compared with fuzzy and expert based system. The proposed system outperformed the state-of-the-art fuzzy system and expert system.

  • 45.
    Zhai, Haoyang
    et al.
    School of Communication Information Engineering, University of Electronic Science and Technology of China.
    Liu, Qiang
    School of Communication Information Engineering, University of Electronic Science and Technology of China..
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Anti-ISI Demodulation Scheme and Its Experiment-based Evaluation for Diffusion-based Molecular Communication2018In: IEEE Transactions on Nanobioscience, ISSN 1536-1241, E-ISSN 1558-2639, Vol. 17, no 2, p. 126-133Article in journal (Refereed)
    Abstract [en]

    In diffusion-based molecular communication (MC), the most common modulation technique is based on the concentration of information molecules. However, the random delay of molecules due to the channel with memory causes severe inter-symbol interference (ISI) among consecutive signals. In this paper, we propose a detection technique for demodulating signals, the increase detection algorithm (IDA), to improve the reliability of concentration-encoded diffusion-based molecular communication. The proposed IDA detects an increase (i.e., a relative concentration value) in molecule concentration to extract the information instead of detecting an absolute concentration value. To validate the availability of IDA, we establish a real physical tabletop testbed. And we evaluate the proposed demodulation technique using bit error rate (BER) and demonstrate by the tabletop molecular communication platform that the proposed IDA successfully minimizes and even isolates ISI so that a lower BER is achieved than the common demodulation technique.

  • 46.
    Idowu, Samuel O.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Applied Machine Learning in District Heating System2018Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    In an increasingly applied domain of pervasive computing, sensing devices are being deployed progressively for data acquisition from various systems through the use of technologies such as wireless sensor networks. Data obtained from such systems are used analytically to advance or improve system performance or efficiency. The possibility to acquire an enormous amount of data from any target system has made machine learning a useful approach for several large-scale analytical solutions. Machine learning has proved viable in the area of the energy sector, where the global demand for energy and the increasingly accepted need for green energy is gradually challenging energy supplies and the efficiency in its consumption.

    This research, carried out within the area of pervasive computing, aims to explore the application of machine learning and its effectiveness in the energy sector with dependency on sensing devices. The target application area readily falls under a multi-domain energy grid which provides a system across two energy utility grids as a combined heat and power system. The multi-domain aspect of the target system links to a district heating system network and electrical power from a combined heat and power plant. This thesis, however, focuses on the district heating system as the application area of interest while contributing towards a future goal of a multi-domain energy grid, where improved efficiency level, reduction of overall carbon dioxide footprint and enhanced interaction and synergy between the electricity and thermal grid are vital goals. This thesis explores research issues relating to the effectiveness of machine learning in forecasting heat demands at district heating substations, and the key factors affecting domestic heat load patterns in buildings.

    The key contribution of this thesis is the application of machine learning techniques in forecasting heat energy consumption in buildings, and our research outcome shows that supervised machine learning methods are suitable for domestic thermal load forecast. Among the examined machine learning methods which include multiple linear regression, support vector machine,  feed forward neural network, and regression tree, the support vector machine performed best with a normalized root mean square error of 0.07 for a 24-hour forecast horizon. In addition, weather and time information are observed to be the most influencing factors when forecasting heat load at heating network substations. Investigation on the effect of using substation's operational attributes, such as the supply and return temperatures, as additional input parameters when forecasting heat load shows that the use of substation's internal operational attributes has less impact.

  • 47.
    Wazid, Mohammad
    et al.
    Cyber Security and Networks Lab, Innopolis University, Innopolis, Russia.
    Kumar Das, Ashok
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad, India.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Authenticated key management protocol for cloud-assisted body area sensor networks2018In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 123, p. 112-126Article in journal (Refereed)
    Abstract [en]

    Due to recent advances in various technologies such as integrated circuit, embedded systems and wireless communications, the wireless body area network (WBAN) becomes a propitious networking paradigm. WBANs play a very important role in modern medical systems as the real-time biomedical data through intelligent medical sensors in or around the patients' body can be collected and sent the data to remote medical personnel for clinical diagnostics. However, wireless nature of communication makes an adversary to intercept or modify the private and secret data collected by the sensors in WBANs. In critical applications of WBANs, there is a great requirement to access directly the sensing information collected by the body sensors by an external user (e.g., a doctor) in order to monitor the health condition of a patient. In order to do so, the user needs to first authenticate with the accessed body sensors, and only after mutual authentication between that user and the body sensors the real-time data can be directly accessed securely by the user.

    In this paper, we propose a new user authentication and key management scheme for this purpose. The proposed scheme allows mutual authentication between a user and personal server connected to WBAN via the healthcare server situated at the cloud, and once the mutual authentication is successful, both user and personal server are able to establish a secret session key for their future communication. In addition, key management process is provided for establishment of secret keys among the sensors and personal server for their secure communication. The formal security based on broadly-accepted Real-Or-Random (ROR) model and informal security give confidence that the proposed scheme can withstand several known attacks needed for WBAN security. A detailed comparative analysis among the proposed scheme and other schemes shows that the proposed scheme provides better security & functionality features, low computation and comparable communication costs as compared to recently proposed related schemes. Finally, the practical demonstration using the NS2 based simulation is shown for the proposed scheme and also for other schemes.

  • 48.
    Cruciani, Frederico
    et al.
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    Cleland, Ian
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    Nugent, Chris
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    McCullagh, Paul
    Computer Science Research Institute, Ulster University, Newtownabbey BT370QB, UK.
    Synnes, Kåre
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hallberg, Josef
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Automatic annotation for human activity recognition in free living using a smartphone2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 7, article id 2203Article in journal (Refereed)
    Abstract [en]

    Data annotation is a time-consuming process posing major limitations to the development of Human Activity Recognition (HAR) systems. The availability of a large amount of labeled data is required for supervised Machine Learning (ML) approaches, especially in the case of online and personalized approaches requiring user specific datasets to be labeled. The availability of such datasets has the potential to help address common problems of smartphone-based HAR, such as inter-person variability. In this work, we present (i) an automatic labeling method facilitating the collection of labeled datasets in free-living conditions using the smartphone, and (ii) we investigate the robustness of common supervised classification approaches under instances of noisy data. We evaluated the results with a dataset consisting of 38 days of manually labeled data collected in free living. The comparison between the manually and the automatically labeled ground truth demonstrated that it was possible to obtain labels automatically with an 80–85% average precision rate. Results obtained also show how a supervised approach trained using automatically generated labels achieved an 84% f-score (using Neural Networks and Random Forests); however, results also demonstrated how the presence of label noise could lower the f-score up to 64–74% depending on the classification approach (Nearest Centroid and Multi-Class Support Vector Machine).

  • 49.
    Yi,, J.-H.
    et al.
    School of Mathematics and Big Data, Foshan University, Foshan, China; School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China.
    Xing, L. -N.
    School of Mathematics and Big Data, Foshan University, Foshan, China.
    Wang, G.-G.
    Department of Computer Science and Technology, Ocean University of China, Qingdao, China.
    Dong, J.
    Department of Computer Science and Technology, Ocean University of China, Qingdao, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Alavi, A.H.
    Department of Civil and Environmental Engineering, University of Missouri, Columbia, United States.
    Wang, L.
    Department of Automation, Tsinghua University, Beijing, China.
    Behavior of crossover operators in NSGA-III for large-scale optimization problems2018In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291Article in journal (Refereed)
    Abstract [en]

    Traditional multi-objective optimization evolutionary algorithms (MOEAs) do not usually meet the requirements for online data processing because of their high computational costs. This drawback has resulted in difficulties in the deployment of MOEAs for multi-objective, large-scale optimization problems. Among different evolutionary algorithms, non-dominated sorting genetic algorithm-the third version (NSGA-III) is a fairly new method capable of solving large-scale optimization problems with acceptable computational requirements. In this paper, the performance of three crossover operators of the NSGA-III algorithm is benchmarked using a large-scale optimization problem based on human electroencephalogram (EEG) signal processing. The studied operators are simulated binary (SBX), uniform crossover (UC), and single point (SI) crossovers. Furthermore, enhanced versions of the NSGA-III algorithm are proposed through introducing the concept of Stud and designing several improved crossover operators of SBX, UC, and SI. The performance of the proposed NSGA-III variants is verified on six large-scale optimization problems. Experimental results indicate that the NSGA-III methods with UC and UC-Stud (UCS) outperform the other developed variants.

  • 50.
    Shitiri, Ethungshan