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  • 151.
    Ahmad, Iftikhar
    et al.
    Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur.
    Noor, Rafidah Md
    Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur.
    Ali, Ihsan
    Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur.
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Characterizing the role of vehicular cloud computing in road traffic management2017In: International Journal of Distributed Sensor Networks, ISSN 1550-1329, E-ISSN 1550-1477, Vol. 13, no 5Article in journal (Refereed)
    Abstract [en]

    Vehicular cloud computing is envisioned to deliver services that provide traffic safety and efficiency to vehicles. Vehicular cloud computing has great potential to change the contemporary vehicular communication paradigm. Explicitly, the underutilized resources of vehicles can be shared with other vehicles to manage traffic during congestion. These resources include but are not limited to storage, computing power, and Internet connectivity. This study reviews current traffic management systems to analyze the role and significance of vehicular cloud computing in road traffic management. First, an abstraction of the vehicular cloud infrastructure in an urban scenario is presented to explore the vehicular cloud computing process. A taxonomy of vehicular clouds that defines the cloud formation, integration types, and services is presented. A taxonomy of vehicular cloud services is also provided to explore the object types involved and their positions within the vehicular cloud. A comparison of the current state-of-the-art traffic management systems is performed in terms of parameters, such as vehicular ad hoc network infrastructure, Internet dependency, cloud management, scalability, traffic flow control, and emerging services. Potential future challenges and emerging technologies, such as the Internet of vehicles and its incorporation in traffic congestion control, are also discussed. Vehicular cloud computing is envisioned to have a substantial role in the development of smart traffic management solutions and in emerging Internet of vehicles

  • 152.
    Karvonen, Niklas
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Jimenez, Lara Lorna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Gomez Simon, Miguel
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Nilsson, Joakim
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Kikhia, Basel
    Faculty of Health and Sport Sciences, University of Agder 4879 Grimstad, Norway.
    Hallberg, Josef
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Classifier Optimized for Resource-constrained Pervasive Systems and Energy-efficiency2017In: International Journal of Computational Intelligence Systems, ISSN 1875-6891, E-ISSN 1875-6883, Vol. 10, no 1, p. 1272-1279Article in journal (Refereed)
    Abstract [en]

    Computational intelligence is often used in smart environment applications in order to determine a user’scontext. Many computational intelligence algorithms are complex and resource-consuming which can beproblematic for implementation devices such as FPGA:s, ASIC:s and low-level microcontrollers. Thesetypes of devices are, however, highly useful in pervasive and mobile computing due to their small size,energy-efficiency and ability to provide fast real-time responses. In this paper, we propose a classi-fier, CORPSE, specifically targeted for implementation in FPGA:s, ASIC:s or low-level microcontrollers.CORPSE has a small memory footprint, is computationally inexpensive, and is suitable for parallel processing.The classifier was evaluated on eight different datasets of various types. Our results show thatCORPSE, despite its simplistic design, has comparable performance to some common machine learningalgorithms. This makes the classifier a viable choice for use in pervasive systems that have limitedresources, requires energy-efficiency, or have the need for fast real-time responses.

  • 153.
    Yin, Zekun
    et al.
    Shandong University, Jinan.
    Lan, Haidong
    Shandong University, Jinan.
    Tan, Guanming
    Institute of Computing Technology, Chinese Academy of Sciences.
    Lu, Mian
    Huawei Singapore Research Centre.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Liu, Weiguo
    Shandong University, Jinan.
    Computing Platforms for Big Biological Data Analytics: Perspectives and Challenges2017In: Computational and structural biotechnology journal, E-ISSN 2001-0370, Vol. 15, p. 403-411Article in journal (Refereed)
    Abstract [en]

    The last decade has witnessed an explosion in the amount of available biological sequence data, due to the rapid progress of high-throughput sequencing projects. However, the biological data amount is becoming so great that traditional data analysis platforms and methods can no longer meet the need to rapidly perform data analysis tasks in life sciences. As a result, both biologists and computer scientists are facing the challenge of gaining a profound insight into the deepest biological functions from big biological data. This in turn requires massive computational resources. Therefore, high performance computing (HPC) platforms are highly needed as well as efficient and scalable algorithms that can take advantage of these platforms. In this paper, we survey the state-of-the-art HPC platforms for big biological data analytics. We first list the characteristics of big biological data and popular computing platforms. Then we provide a taxonomy of different biological data analysis applications and a survey of the way they have been mapped onto various computing platforms. After that, we present a case study to compare the efficiency of different computing platforms for handling the classical biological sequence alignment problem. At last we discuss the open issues in big biological data analytics.

  • 154.
    Booth, Todd
    et al.
    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.
    Critical Infrastructure Network DDoS Defense, via Cognitive Learning2017In: / [ed] Pietro Manzoni, Universitat Politècnica de València, Spain, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017Conference paper (Refereed)
    Abstract [en]

    Some public and private services are called part of the Critical Infrastructure (CI), which are considered as the most important services to protect the functioning of a society and the economy.  Many CIs provide services via the Internet and thus cyber-attacks can be performed remotely.  It is now very simple and free to find and download software, which automates performing cyber-attacks.  A recent example is that two teenagers, with close to no security knowledge, created an on-line business. They would run cyber-attacks (online booter service called vDOS, as reported by Brian Krebs) for a small fee. They reportedly earned over 600,000 USD in a short period of time by conducting a large number of automated DDoS cyber-attacks. Then Krebs was retaliated against, and the highest DDoS attack bandwidth ever recorded, 620 Gbps, was launched against Krebs. In this paper we show how cognitive learning can be used to significantly mitigate any effects of DDoS network attacks, against the critical infrastructure.

  • 155.
    Rasheed, Muhammad Babar
    et al.
    COMSATS Institute of Information Technology, Islamabad.
    Javaid, Nadeem
    COMSATS Institute of Information Technology, Islamabad.
    Imran, Muhammad Al
    College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
    Khaan, Zahoorali
    Faculty of Engineering, Dalhousie University, Halifax, NS.
    Qasim, Umar
    University of Alberta, Edmonton.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Delay and energy consumption analysis of priority guaranteed MAC protocol for wireless body area networks2017In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 23, no 4, p. 1249-1266Article in journal (Refereed)
    Abstract [en]

    Wireless body area networks are captivating growing interest because of their suitability for wide range of applications. However, network lifetime is one of the most prominent barriers in deploying these networks for most applications. Moreover, most of these applications have stringent QoS requirements such as delay and throughput. In this paper, the modified superframe structure of IEEE 802.15.4 based MAC protocol is proposed which addresses the aforementioned problems and improves the energy consumption efficiency. Moreover, priority guaranteed CSMA/CA mechanism is used where different priorities are assigned to body nodes by adjusting the data type and size. In order to save energy, a wake-up radio based mechanism to control sleep and active modes of body sensors are used. Furthermore, a discrete time finite state Markov model to find the node states is used. Analytical expressions are derived to model and analyze the behavior of average energy consumption, throughput, packet drop probability, and average delay during normal and emergency data. Extensive simulations are conducted for analysis and validation of the proposed mechanism. Results show that the average energy consumption and delay are relatively higher during emergency data transmission with acknowledgment mode due to data collision and retransmission.

  • 156.
    Xiong, Naixue
    et al.
    Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK .
    Zhang, Longzhen
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai.
    Zhang, Wei
    Department of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University.
    Design and Analysis of an Efficient Energy Algorithm in Wireless Social Sensor Networks2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 10, article id 2166Article in journal (Refereed)
    Abstract [en]

    Because mobile ad hoc networks have characteristics such as lack of center nodes, multi-hop routing and changeable topology, the existing checkpoint technologies for normal mobile networks cannot be applied well to mobile ad hoc networks. Considering the multi-frequency hierarchy structure of ad hoc networks, this paper proposes a hybrid checkpointing strategy which combines the techniques of synchronous checkpointing with asynchronous checkpointing, namely the checkpoints of mobile terminals in the same cluster remain synchronous, and the checkpoints in different clusters remain asynchronous. This strategy could not only avoid cascading rollback among the processes in the same cluster, but also avoid too many message transmissions among the processes in different clusters. What is more, it can reduce the communication delay. In order to assure the consistency of the global states, this paper discusses the correctness criteria of hybrid checkpointing, which includes the criteria of checkpoint taking, rollback recovery and indelibility. Based on the designed Intra-Cluster Checkpoint Dependence Graph and Inter-Cluster Checkpoint Dependence Graph, the elimination rules for different kinds of checkpoints are discussed, and the algorithms for the same cluster checkpoints, different cluster checkpoints, and rollback recovery are also given. Experimental results demonstrate the proposed hybrid checkpointing strategy is a preferable trade-off method, which not only synthetically takes all kinds of resource constraints of Ad hoc networks into account, but also outperforms the existing schemes in terms of the dependence to cluster heads, the recovery time compared to the pure synchronous, and the pure asynchronous checkpoint advantage.

  • 157.
    Laato, Samuli
    et al.
    University of Turku.
    Sutinen, Erkki
    University of Turku.
    Laine, Teemu H.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Ajou University, Suwon.
    Seo, Jungryul
    Ajou University, Suwon.
    Ko, Wooryeon
    University of Eastern Finland, Kuopio.
    Designing a Game for Learning Math by Composing: a Finnish Primary School Case2017In: 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT) / [ed] Chang, M; Chen, NS; Huang, R; Kinshuk; Sampson, DG; Vasiu, R, New York, 2017, p. 136-138Conference paper (Refereed)
    Abstract [en]

    Music is filled with mathematical relations. When creating music, the composer must keep in mind the rhythm, the notes, and how well they ring with each other. Our aim was to design an application that teaches these relationships and allows users to compose their own songs using numbers. Our work follows the design science research method, and we have co-designed the application together with elementary school students and teachers in Finland. This paper demonstrates the design process and provides an analysis on our design based on data collected from the participants in two separate sessions.

  • 158.
    Laato, Samuli
    et al.
    University of Turku.
    Laine, Teemu H.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Seo, Jungryul
    Ajou University.
    Ko, Wooryeon
    University of Eastern Finland.
    Sutinen, Erkki
    University of Turku.
    Designing a Game for Learning Mathematics by Composing: a Case in a Finnish Primary School2017Conference paper (Refereed)
    Abstract [en]

    Music is filled with mathematical relations. When creating music, the composer must keep in mind the rhythm, the notes, and how well they ring with each other. Our aim was to design an application that teaches these relationships and allows users to compose their own songs using numbers. Our work follows the design science research method, and we have co-designed the application together with elementary school students and teachers in Finland. This paper demonstrates the design process and provides an analysis on our design based on data collected from the participants in two separate sessions.

  • 159.
    Wang, Yufeng
    et al.
    Media Lab, Waseda University, Tokyo.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Jin, Qun
    Faculty of Human Sciences, Waseda University, Tokyo.
    Device-to-device based proximity service: Architecture, issues, and applications2017Book (Refereed)
    Abstract [en]

    Abstract View references (360)

    D2D-based proximity service is a very hot topic with great commercial potential from an application standpoint. Unlike existing books which focus on D2D communications technologies, this book fills a gap by summarizing and analyzing the latest applications and research results in academic, industrial fields, and standardization. The authors present the architecture, fundamental issues, and applications in a D2D networking environment from both application and interdisciplinary points of view.

  • 160.
    Du, Wei
    et al.
    Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai.
    Leung, Sunney Yung Sun
    Institute of Textile and Clothing, The Hong Kong Polytechnic University, Hong Kong.
    Tang, Yang
    Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Differential Evolution With Event-Triggered Impulsive Control2017In: IEEE Transactions on Cybernetics, ISSN 2168-2267, E-ISSN 2168-2275, Vol. 7, no 1, p. 244-257Article in journal (Refereed)
    Abstract [en]

    Differential evolution (DE) is a simple but powerful evolutionary algorithm, which has been widely and successfully used in various areas. In this paper, an event-triggered impulsive (ETI) control scheme is introduced to improve the performance of DE. Impulsive control (IPC), the concept of which derives from control theory, aims at regulating the states of a network by instantly adjusting the states of a fraction of nodes at certain instants, and these instants are determined by event-triggered mechanism (ETM). By introducing IPC and ETM into DE, we hope to change the search performance of the population in a positive way after revising the positions of some individuals at certain moments. At the end of each generation, the IPC operation is triggered when the update rate of the population declines or equals to zero. In detail, inspired by the concepts of IPC, two types of impulses are presented within the framework of DE in this paper: 1) stabilizing impulses and 2) destabilizing impulses. Stabilizing impulses help the individuals with lower rankings instantly move to a desired state determined by the individuals with better fitness values. Destabilizing impulses randomly alter the positions of inferior individuals within the range of the current population. By means of intelligently modifying the positions of a part of individuals with these two kinds of impulses, both exploitation and exploration abilities of the whole population can be meliorated. In addition, the proposed ETI is flexible to be incorporated into several state-of-the-art DE variants. Experimental results over the IEEE Congress on Evolutionary Computation (CEC) 2014 benchmark functions exhibit that the developed scheme is simple yet effective, which significantly improves the performance of the considered DE algorithms. 

  • 161.
    Chronéer, Diana
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Johansson, Jeaneth
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Innovation and Design.
    Nilsson, Michael
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Runardotter, Mari
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Digital platform ecosystems: From information transactions to collaboration impact2017Conference paper (Refereed)
  • 162.
    Belyakhina, Tamara
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zaslavsky, Arkady
    CSIRO, Melbourne.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Saguna, Saguna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Jayaraman, Prem Prakash
    Swinburne University of Technology, Melbourne.
    DisCPAQ: Distributed Context Acquisition and Reasoning for Personalized Indoor Air Quality Monitoring in IoT-Based Systems2017In: Internet of Things, Smart Spaces, and Next Generation Networks and Systems: 17th International Conference, NEW2AN 2017, 10th Conference, ruSMART 2017, Third Workshop NsCC 2017, St. Petersburg, Russia, August 28–30, 2017, Proceedings / [ed] Galinina O., Andreev S., Balandin S., Koucheryavy Y., Cham: Springer, 2017, p. 75-86Conference paper (Refereed)
    Abstract [en]

    The rapidly emerging Internet of Things supports many diverse applications including environmental monitoring. Air quality, both indoors and outdoors, proved to be a significant comfort and health factor for people. This paper proposes a smart context-aware system for indoor air quality monitoring and prediction called DisCPAQ. The system uses data streams from air quality measurement sensors to provide real-time personalised air quality service to users through a mobile app. The proposed system is agnostic to sensor infrastructure. The paper proposes a context model based on Context Spaces Theory, presents the architecture of the system and identifies challenges in developing large scale IoT applications. DisCPAQ implementation, evaluation and lessons learned are all discussed in the paper.

  • 163.
    Cheng, Jie
    et al.
    Shannon Cognitive Computing Laboratory, Huawei Technologies Company.
    Liu, Yaning
    Harbin Institute of Technology Shenzhen Graduate School,.
    Ye, Qiang
    University of Prince Edward Island, Charlottetown.
    Du, Hongwei
    Harbin Institute of Technology Shenzhen Graduate School,.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    DISCS: a distributed coordinate system based on robust nonnegative matrix completion2017In: IEEE/ACM Transactions on Networking, ISSN 1063-6692, E-ISSN 1558-2566, Vol. 25, no 2, p. 934-947Article in journal (Refereed)
    Abstract [en]

    Many distributed applications, such as BitTorrent, need to know the distance between each pair of network hosts in order to optimize their performance. For small-scale systems, explicit measurements can be carried out to collect the distance information. For large-scale applications, this approach does not work due to the tremendous amount of measurements that have to be completed. To tackle the scalability problem, network coordinate system (NCS) was proposed to solve the scalability problem by using partial measurements to predict the unknown distances. However, the existing NCS schemes suffer seriously from either low prediction precision or unsatisfactory convergence speed. In this paper, we present a novel distributed network coordinate system (DISCS) that utilizes a limited set of distance measurements to achieve high-precision distance prediction at a fast convergence speed. Technically, DISCS employs the innovative robust nonnegative matrix completion method to improve the prediction accuracy. Through extensive experiments based on various publicly-available data sets, we found that DISCS outperforms the state-of-the-art NCS schemes in terms of prediction precision and convergence speed, which clearly shows the high usability of DISCS in real-life Internet applications.

  • 164.
    Booth, Todd
    et al.
    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.
    DNS DDoS Mitigation, via DNS Timer Design Changes2017In: Future Network Systems and Security: Third International Conference, FNSS 2017, Gainesville, FL, USA, August 31 - September 2, 2017, Proceedings / [ed] Robin Doss, Welwyn Piramuthu, Wei Zhou, Springer, 2017, p. 43-55Conference paper (Refereed)
    Abstract [en]

    DDoS attacks have been a problem since 2000. In October 2016, there was a major DDoS attack against the service provider Dyn’s DNS service, which took the service down. This was one of the largest bandwidth DDoS attack ever documented, with attack bandwidth over 650 Gbps. By taking down just Dyn’s DNS service, clients could not obtain the IP addresses, of the organizations hosting their DNS with Dyn, such as Twitter. Our contribution is that we have found a way to mitigate the effect of DDoS attacks against DNS services. We only require some very small algorithm changes, in the DNS protocol. More specifically, we propose to add two additional timers. Even if the end DNS clients don’t support these timers, they will receive our new functionality via the DNS resolvers and recursive servers. In summary, our contributions give much more control to the organizations, as to under which specific conditions the DNS cache entries should be aged or used. This allows the organization to (1) much more quickly expire client DNS caches and (2) to mitigate the DDoS DNS attack effects. Our contributions are also helpful to organizations, even if there are no DDoS DNS attack.

  • 165.
    Bansal, Shubham
    et al.
    NEC Laboratories Europe, Heidelberg.
    Schmidt, Mischa
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Energy Disaggregation Methods for Commercial Buildingsusing Smart Meter and Operational data2017In: The Workshops of the Thirty-First AAAI Conference on Artificial Intelligence: Artificial Intelligence for Smart Grids and Smart Buildings, AI Access Foundation , 2017, p. 325-329Conference paper (Refereed)
    Abstract [en]

    One of the key information pieces in improving energy efficiency of buildings is the appliance level breakdown of energy consumption. Energy disaggregation is the process of obtaining this breakdown from a building level aggregate data using computational techniques. Most of the current research focuses on residential buildings, obtaining this information from a single smart meter and often relying on high frequency data. This work is directed at commercial buildings equipped with building management and automation systems providing low frequency operational and contextual data. This paper presents a machine learning method to disaggregate energy consumption of the building using this operational data as input features. Experimental results on two publicly available datasets demonstrate the effectiveness of the approach, which surpasses existing methods. For all but one appliance of House 2 of the publicly available REDD dataset, improvements in normalized error in assigned power range between 20% (Lighting) and 220% (Stove). For another dataset from an educational facility in Singapore, disaggregation accuracy of 92% is reported for the facility’s cooling system.

  • 166.
    Ghulam, Muhammad
    et al.
    Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh .
    Alhamid, Mohammed F
    Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh .
    Hossain, M. Shamim
    Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh .
    Almogren, Ahmad S.
    Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh .
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Enhanced Living by Assessing Voice Pathology Using a Co-Occurrence Matrix2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 2, article id 267Article in journal (Refereed)
    Abstract [en]

    large number of the population around the world suffers from various disabilities. Disabilities affect not only children but also adults of different professions. Smart technology can assist the disabled population and lead to a comfortable life in an enhanced living environment (ELE). In this paper, we propose an effective voice pathology assessment system that works in a smart home framework. The proposed system takes input from various sensors, and processes the acquired voice signals and electroglottography (EGG) signals. Co-occurrence matrices in different directions and neighborhoods from the spectrograms of these signals were obtained. Several features such as energy, entropy, contrast, and homogeneity from these matrices were calculated and fed into a Gaussian mixture model-based classifier. Experiments were performed with a publicly available database, namely, the Saarbrucken voice database. The results demonstrate the feasibility of the proposed system in light of its high accuracy and speed. The proposed system can be extended to assess other disabilities in an ELE.

  • 167.
    Xia, Zhihua
    et al.
    Jiangsu Engineering Center of Network Monitoring, Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, College of Computer and Software, Nanjing University of Information Science & Technology.
    Xiong, Neal N.
    Department of Business and Computer Science, Southwestern Oklahoma State University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Sun, Xingming
    Jiangsu Engineering Center of Network Monitoring, Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, College of Computer and Software, Nanjing University of Information Science & Technology.
    EPCBIR: An efficient and privacy-preserving content-based image retrieval scheme in cloud computing2017In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 387, p. 195-204Article in journal (Refereed)
    Abstract [en]

    The content-based image retrieval (CBIR) has been widely studied along with the increasing importance of images in our daily life. Compared with the text documents, images consume much more storage and thus are very suitable to be stored on the cloud servers. The outsourcing of CBIR to the cloud servers can be a very typical service in cloud computing. For the privacy-preserving purposes, sensitive images, such as medical and personal images, need to be encrypted before being outsourced, which will cause the CBIR technologies in plaintext domain unusable. In this paper, we propose a scheme that supports CBIR over the encrypted images without revealing the sensitive information to the cloud server. Firstly, the feature vectors are extracted to represent the corresponding images. Then, the pre-filter tables are constructed with the locality-sensitive hashing to increase the search efficiency. Next, the feature vectors are protected by the secure k-nearest neighbor (kNN) algorithm. The security analysis and experiments show the security and efficiency of the proposed scheme.

  • 168.
    Liu, Yongxin
    et al.
    South China University of Technology.
    Wang, Xiaoxiong
    South China University of Technology.
    Wan, Jiafu
    South China University of Technology.
    Xue, Xuejun
    South China Agricultural University.
    Song, Houbing
    West Virginia University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Exploring data validity in transportation systems for smart cities2017In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 55, no 5, p. 26-33, article id 7926913Article in journal (Refereed)
    Abstract [en]

    Efficient urban transportation systems are widely accepted as essential infrastructure for smart cities, and they can highly increase a city°s vitality and convenience for residents. The three core pillars of smart cities can be considered to be data mining technology, IoT, and mobile wireless networks. Enormous data from IoT is stimulating our cities to become smarter than ever before. In transportation systems, data-driven management can dramatically enhance the operating efficiency by providing a clear and insightful image of passengers° transportation behavior. In this article, we focus on the data validity problem in a cellular network based transportation data collection system from two aspects: Internal time discrepancy and data loss. First, the essence of time discrepancy was analyzed for both automated fare collection (AFC) and automated vehicular location (AVL) systems, and it was found that time discrepancies can be identified and rectified by analyzing passenger origin inference success rate using different time shift values and evolutionary algorithms. Second, the algorithmic framework to handle location data loss and time discrepancy was provided. Third, the spatial distribution characteristics of location data loss events were analyzed, and we discovered that they have a strong and positive relationship with both high passenger volume and shadowing effects in urbanized areas, which can cause severe biases on passenger traffic analysis. Our research has proposed some data-driven methodologies to increase data validity and provided some insights into the influence of IoT level data loss on public transportation systems for smart cities.

  • 169.
    Deng, Ruilong
    et al.
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton.
    Xiao, Gaoxi
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
    Lu, Rongxing
    Faculty of Computer Science, University of New Brunswick,.
    Liang, Hao
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    False data injection on state estimation in power systems - attacks, impacts, and defense: a survey2017In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 13, no 2, p. 411-423, article id 7579185Article in journal (Refereed)
    Abstract [en]

    The accurately estimated state is of great importance for maintaining a stable running condition of power systems. To maintain the accuracy of the estimated state, bad data detection (BDD) is utilized by power systems to get rid of erroneous measurements due to meter failures or outside attacks. However, false data injection (FDI) attacks, as recently revealed, can circumvent BDD and insert any bias into the value of the estimated state. Continuous works on constructing and/or protecting power systems from such attacks have been done in recent years. This survey comprehensively overviews three major aspects: constructing FDI attacks; impacts of FDI attacks on electricity market; and defending against FDI attacks. Specifically, we first explore the problem of constructing FDI attacks, and further show their associated impacts on electricity market operations, from the adversary's point of view. Then, from the perspective of the system operator, we present countermeasures against FDI attacks. We also outline the future research directions and potential challenges based on the above overview, in the context of FDI attacks, impacts, and defense.

  • 170.
    Lindgren, Anders
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Åkerberg, Johan
    Björkman, Mats
    Feasibility of ICN in Automation Networks2017Conference paper (Refereed)
  • 171.
    Yan, Zheng
    et al.
    State Key Laboratory on Integrated Services Networks, Xidian University.
    Li, Xueyun
    Department of Communications and Networking, Aalto University.
    Wang, Mingjun
    State Key Laboratory of Integrated Services Networks, Xidian University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Flexible Data Access Control based on Trust and Reputation in Cloud Computing2017In: I E E E Transactions on Cloud Computing, E-ISSN 2168-7161, Vol. 5, no 3, p. 485-498, article id 7208817Article in journal (Refereed)
    Abstract [en]

    Cloud computing offers a new way of services and has become a popular service platform. Storing user data at a cloud data center greatly releases storage burden of user devices and brings access convenience. Due to distrust in cloud service providers, users generally store their crucial data in an encrypted form. But in many cases, the data need to be accessed by other entities for fulfilling an expected service, e.g., an eHealth service. How to control personal data access at cloud is a critical issue. Various application scenarios request flexible control on cloud data access based on data owner policies and application demands. Either data owners or some trusted third parties or both should flexibly participate in this control. However, existing work hasn’t yet investigated an effective and flexible solution to satisfy this demand. On the other hand, trust plays an important role in data sharing. It helps overcoming uncertainty and avoiding potential risks. But literature still lacks a practical solution to control cloud data access based on trust and reputation. In this paper, we propose a scheme to control data access in cloud computing based on trust evaluated by the data owner and/or reputations generated by a number of reputation centers in a flexible manner by applying Attribue-Based Encryption and Proxy Re-Encryption. We integrate the concept of context-aware trust and reputation evaluation into a cryptographic system in order to support various control scenarios and strategies. The security and performance of our scheme are evaluated and justified through extensive analysis, security proof, comparison and implementation. The results show the efficiency, flexibility and effectiveness of our scheme for data access control in cloud computing

  • 172.
    Perera, Charith
    et al.
    The Open University, UK.
    Qin, Yongrui
    University of Huddersfield, UK.
    Estrella, Julio C.
    University of Sao Paulo.
    Reiff-Marganiec, Stephan
    University of Leicester, UK.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Fog Computing for Sustainable Smart Cities: A Survey2017In: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 50, no 3, article id 32Article in journal (Refereed)
    Abstract [en]

    The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, especially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g., network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build a sustainable IoT infrastructure for smart cities. In this article, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges toward implementing them, to shed light on future research directions on realizing Fog computing for building sustainable smart cities.

  • 173.
    Wei, Wei
    et al.
    School of Computer Science and Engineering, Xi’an University of Technology.
    Song, Houbing
    Department of Electrical and Computer Engineering, West Virginia University, Montgomery, WV .
    Li, Wei
    Centre for Distributed and High Performance Computing, School of Information Technologies, The University of Sydney.
    Shen, Peiyi
    National school of Software, Xidian University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network2017In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 408, p. 100-114Article in journal (Refereed)
    Abstract [en]

    Wireless sensor networks can support building and transportation system automation in numerous ways. An emerging application is to guide drivers to promptly locate vacant parking spaces in large parking structures during peak hours. This paper proposes efficient parking navigation via a continuous information potential field and gradient ascent method. Our theoretical analysis proves the convergence of a proposed algorithm and efficient convergence during the first and second steps of the algorithm to effectively prevent parking navigation from a gridlock situation. The empirical study demonstrates that the proposed algorithm performs more efficiently than existing algorithms.

  • 174.
    Liu, Jun
    et al.
    Xi’an Jiaotong University, Xi’an, China.
    Yan, Zheng
    Xidian University, Xi’an, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Laurence T.
    Department of Computer Science, St. Francis Xavier University, Antigonish, Canada.
    Guest Editorial Data Mining in Cyber, Physical, and Social Computing2017In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 11, no 1, p. 194-196Article in journal (Refereed)
    Abstract [en]

    Presents an introduction to the issue which focuses on data mining in cyber, physical, and social computing

  • 175.
    Wan, Jiafu
    et al.
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Zhang, Daqiang
    School of Software Engineering, Tongji University, Shanghai.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Lloret, Jaime
    Department of Communications Polytechnic University of Valencia.
    Guest Editorial Special Issue on Cloud-Integrated Cyber-Physical Systems2017In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 11, no 1, p. 84-87Article in journal (Other academic)
    Abstract [en]

    The advances in wireless sensor devices, big data, mobile computing, and cloud computing offer tremendous opportunities to realize the seamless integration between the physical world and the cyber space. The cloud-integrated cyberphysical system (CCPS) refers to virtually representing physical system components, such as sensors, actuators, robots, and other devices in clouds, accessing (e.g., monitoring, actuating and navigating) those physical components through their virtual representations, and processing/managing/controlling the large amount of data collected from physical components in clouds in a scalable, real-time, efficient, and reliable manner. Particularly, integrating cloud computing techniques (e.g., virtualization, elastic re-configuration, and multi-tenancy of resources) with CPS techniques (e.g., real-time scheduling, adaptive resource management and control, and embedded system design) will bring hope to advance the state of the art, and allow previously unachievable systems such as cloud-integrated internet of vehicles to be built, deployed, managed, and controlled effectively. This Special Issue on CCPS solicits the manuscripts on rigorous research on theories, methodologies, tools, and testbeds for CCPS. In this special issue, we selected ten papers. Each paper was carefully reviewed by peer review and guest editors. In the following, we will overview the accepted papers that reflect recent advances.

  • 176.
    Tahira, Shireen
    et al.
    Department of Computer Science and Software Engineering, International Islamic University, Islamabad.
    Sher, Muhammad
    Department of Computer Science and Software Engineering, International Islamic University, Islamabad.
    Ullah, Ata
    Department of Computer Science, National University of Modern Languages, Islamabad .
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Handover Based IMS Registration Scheme for Next Generation Mobile Networks2017In: Wireless Communications & Mobile Computing, ISSN 1530-8669, E-ISSN 1530-8677, Vol. 2017, article id 8789513Article in journal (Refereed)
    Abstract [en]

    Next generation mobile networks aim to provide faster speed and more capacity along with energy efficiency to support video streaming andmassive data sharing in social and communication networks. In these networks, user equipment has to register with IPMultimedia Subsystem (IMS) which promises quality of service to the mobile users that frequently move across different access networks. After each handover caused due to mobility, IMS provides IPSec Security Association establishment and authentication phases. The main issue is that unnecessary reregistration after every handover results in latency and communication overhead. To tackle these issues, this paper presents a lightweight Fast IMS Mobility (FIM) registration scheme that avoids unnecessary conventional registration phases such as security associations, authentication, and authorization. FIM maintains a flag to avoid deregistration and sends a subsequent message to provide necessary parameters to IMS servers after mobility. It also handles the change of IP address for user equipment and transferring the security associations from old to new servers. We have validated the performance of FIM by developing a testbed consisting of IMS servers and user equipment. The experimental results demonstrate the performance supremacy of FIM. It reduces media disruption time, number of messages, and packet loss up to 67%, 100%, and 61%, respectively, as compared to preliminaries.

  • 177.
    Ul Islam, Raihan
    et al.
    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, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Heterogeneous Wireless Sensor Networks Using CoAP and SMS to Predict Natural Disasters2017In: Proceedings of the 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS): The 8th IEEE INFOCOM International Workshop on Mobility Management in the Networks of the Future World (MobiWorld'17),, Piscataway, NJ: IEEE Communications Society, 2017, p. 30-35Conference paper (Refereed)
    Abstract [en]

    Even in the 21 st century human is still handicapped with natural disaster. Flood is one of the most catastrophic natural disasters. Early warnings help people to take necessary steps to save human lives and properties. Sensors can be used to provide more accurate early warnings due to possibilities of capturing more detail data of surrounding nature. Recent advantages in protocol standardization and cost effectiveness of sensors it is possible to easily deploy and manage sensors in large scale. In this paper, a heterogeneous wireless sensor network is proposed and evaluated to predict natural disaster like flood. In this network CoAP is used as a unified application layer protocol for exchanging sensor data. Therefore, CoAP over SMS protocol is used for exchanging sensor data. Furthermore, the effectiveness of the heterogeneous wireless sensor network for predicting natural disaster is presented in this paper.

  • 178.
    Li, Yuhong
    et al.
    State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing.
    Wang, Ji
    State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing.
    Lindgren, Anders
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Su, Xiang
    Centre for Ubiquitous Computing, University of Oulu.
    Riekki, Jukka
    Centre for Ubiquitous Computing, University of Oulu.
    Implicit Cooperative Caching based on Information Popularity for Vehicular Networks2017In: CHANTS 2017: Proceedings of the 12th Workshop on Challenged Networks, co-located with MobiCom 201720 October 2017, New York: ACM Digital Library, 2017, p. 51-56Conference paper (Refereed)
    Abstract [en]

    Information dissemination is one of the most important tasks of vehicular networks. Therefore, information-centric networking (ICN) technology is being more and more widely used in vehicular networks due to the connectionless and lightweight characteristics of this networking paradigm. Caching plays an essential role in information-centric networks, but current caching techniques for ICN are not ideal for use in vehicular networks on account of the dynamicity and wireless transmission of vehicular networks. This paper presents a caching approach for ICN-based vehicular networks that takes into account both the dynamicity of vehicular networks and the popularity of the information to be distributed. By introducing the “interval” metric and estimating the popularity of information and current networking conditions of the vehicles on road, cooperative caching among nodes can be realized without exchanging cache management information among them. Simulation results show that the proposed approach can increase the storage space utilization and has low data response time for vehicular networks.

  • 179.
    Zhai, Haoyang
    et al.
    University of Electronic Science and Technology of China, Chengdu.
    Nakano, Tadashi
    Osaka University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Kun
    University of Essex, Colchest.
    Liu, Qiang
    University of Electronic Science and Technology of China, Chengdu.
    Increase detection algorithm for concentration-encoded diffusion-based molecular communication2017In: Proceedings of the 4th ACM International Conference on Nanoscale Computing and Communication, NanoCom 2017, New York: ACM Digital Library, 2017, article id 10Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a demodulation technique, the increase detection algorithm (IDA), to improve the reliability of concentration-encoded diffusion-based molecular communication. The proposed demodulation technique detects an increase (i.e., a relative concentration value) in molecule concentration to demodulate information as opposed to detecting an absolute concentration value. We evaluate the proposed demodulation technique in terms of bit error rate (BER) and demonstrate that the proposed demodulation technique successfully isolates ISI from concentration-encoded diffusion-based molecular communication to achieve a lower BER than a commonly used demodulation technique.

  • 180.
    Xu, Changqiao
    et al.
    State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing.
    Quan, Wei
    National Engineering Laboratory for Next Generation Internet Technologies, School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Hongke
    National Engineering Laboratory for Next Generation Internet Technologies, School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing.
    Muntean, Gabriel-Miro
    School of Electronic Engineering, Network Innovations Centre, Rince Institute, Dublin City University.
    Information-centric cost-efficient optimization for multimedia content delivery in mobile vehicular networks2017In: Computer Communications, ISSN 0140-3664, E-ISSN 1873-703X, Vol. 99, p. 93-106Article in journal (Refereed)
    Abstract [en]

    Providing high-quality multimedia services is a challenging and high-cost task in mobile vehicular networks due to intermittent connectivity, highly dynamic capacity, mostly associated to heterogeneous hosts distribution and their high mobility. Information-centric networking (ICN), which adopts novel content-based dissemination instead of the traditional host-based one, has great potential to accomplish cost-efficient quality-oriented multimedia delivery. This paper proposes a novel cost-Efficient Multimedia content Delivery approach (EcoMD) in vehicular networks leveraging the ICN features. In EcoMD, two essential factors are first analyzed and modeled: content mobility and supply-demand balance, and then, a mixed integer programming (MIP) optimization is formulated to minimize the economic cost associated to guaranteed the quality level of multimedia services. To resolve this NP-hard problem, heuristic mechanisms are proposed covering three aspects: priority-based path selection, least-required source maintaining and on-demand caching enhancement. By comparison with existing state-of-the-art solutions, simulation results demonstrate how EcoMD provides an improved performance in terms of start-up delay, jitter, playback continuity, and Quality of Experience (QoE) while particularly reduces the economic cost.

  • 181.
    Oyelere, Solomon Sunday
    et al.
    University of Eastern Finland, Joensuu, Finland.
    Suhonen, Jarkko
    University of Eastern Finland, Joensuu, Finland.
    Laine, Teemu H.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Integrating parson's programming puzzles into a game-based mobile learning application2017In: Koli Calling '17: Proceedings of the 17th Koli Calling Conference on Computing Education Research, New York: ACM Digital Library, 2017, p. 158-162Conference paper (Refereed)
    Abstract [en]

    Understanding of elementary programming concepts, logic, and syntax is a vital part of learning to program. Unfortunately, learning programming is found to be difficult and boring, especially for novices. For example, drill type of exercises designed for learning elementary programming can be very tedious, making it hard to motivate learners. This study focused on the development of a mobile application, which integrates puzzle-based Parson's programming exercises into a strategy board game with the aim of facilitating the teaching and learning of programming. With the mobile application, learners play Ayo, a variant of the famous traditional African strategy board game Mancala. In each round of the game, the learners will solve a Parson's puzzle, which consist of small programming tasks where students are required to build programs by drag and drop, selection, indenting and ordering code fragments. The proposed solution of integrating the Parson's puzzles to Ayo game provides a new perspective on how to use mobile devices in programming education. The long-term aim of our work is to create a framework for integrating board games into computing education. The study reported in the article is the first step towards creating the framework.

  • 182.
    Heintz, Fredrik
    et al.
    Linköping University.
    Mannila, Linda
    Linköping University.
    Nordén, Lars-Åke
    Uppsala University.
    Parnes, Peter
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Regnell, Björn
    Lund University.
    Introducing Programming and Digital Competence in Swedish K-9 Education2017In: Informatics in Schools: Focus on Learning Programming. ISSEP 2017 / [ed] Valentina Dagienė, Arto Hellas, Cham: Springer, 2017, p. 117-128Conference paper (Refereed)
    Abstract [en]

    The role of computer science and IT in Swedish schools has varied throughout the years. In fall 2014, the Swedish government gave the National Agency for Education (Skolverket) the task of preparing a proposal for K–9 education on how to better address the competences required in a digitalized society. In June 2016, Skolverket handed over a proposal introducing digital competence and programming as interdisciplinary traits, also providing explicit formulations in subjects such as mathematics (programming, algorithms and problem-solving), technology (controlling physical artifacts) and social sciences (fostering aware and critical citizens in a digital society). In March 2017, the government approved the new curriculum, which needs to be implemented by fall 2018 at the latest. We present the new K–9 curriculum and put it in a historical context. We also describe and analyze the process of developing the revised curriculum, and discuss some initiatives for how to implement the changes.

  • 183.
    Cai, Hongming
    et al.
    School of Software, Shanghai Jiao Tong University.
    Xu, Boyi
    College of Economics and Management, Shanghai Jiao Tong University.
    Jiang, Lihong
    School of Software, Shanghai Jiao Tong University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    IoT-Based Big Data Storage Systems in Cloud Computing: Perspectives and Challenges2017In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 4, no 1, p. 75-87, article id 7600359Article in journal (Refereed)
    Abstract [en]

    Internet of Things (IoT) related applications have emerged as an important field for both engineers and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations especially in cloud computing. This paper first provides a functional framework that identifies the acquisition, management, processing and mining areas of IoT big data, and several associated technical modules are defined and described in terms of their key characteristics and capabilities. Then current research in IoT application is analyzed, moreover, the challenges and opportunities associated with IoT big data research are identified. We also report a study of critical IoT application publications and research topics based on related academic and industry publications. Finally, some open issues and some typical examples are given under the proposed IoT-related research framework

  • 184.
    Parnes, Peter
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hedenström, Agneta
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Läroplanen öppnar för nya möjligheter2017In: Slöjd i en digital skola / [ed] Rylander Lundström, Martina, Stockholm: Lärarförlaget , 2017, p. 39-53Chapter in book (Other (popular science, discussion, etc.))
  • 185.
    Zhou, Lina
    et al.
    Information Systems Department, UMBC, Baltimore.
    Pan, Shimei
    Information Systems Department, UMBC, Baltimore.
    Wang, Jianwu
    Information Systems Department, UMBC, Baltimore.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Machine Learning on Big Data: Opportunities and Challenges2017In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 237, p. 350-361Article in journal (Refereed)
    Abstract [en]

    Machine learning (ML) is continuously unleashing its power in a wide range of applications. It has been pushed to the forefront in recent years partly owing to the advert of big data. ML algorithms have never been better promised while challenged by big data. Big data enables ML algorithms to uncover more fine-grained patterns and make more timely and accurate predictions than ever before; on the other hand, it presents major challenges to ML such as model scalability and distributed computing. In this paper, we introduce a framework of ML on big data (MLBiD) to guide the discussion of its opportunities and challenges. The framework is centered on ML which follows the phases of preprocessing, learning, and evaluation. In addition, the framework is also comprised of four other components, namely big data, user, domain, and system. The phases of ML and the components of MLBiD provide directions for the identification of associated opportunities and challenges and open up future work in many unexplored or under explored research areas.

  • 186.
    Chude-Okonkwo, Uche A.K.
    et al.
    Department of Electrical, Electronic & Computer Engineering, University of Pretoria.
    Malekian, Reza
    Department of Electrical, Electronic & Computer Engineering, University of Pretoria.
    Maharaj, B.T.
    Department of Electrical, Electronic & Computer Engineering, University of Pretoria.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Molecular Communication and Nanonetwork for Targeted Drug Delivery: a survey2017In: IEEE Communications Surveys and Tutorials, ISSN 1553-877X, E-ISSN 1553-877X, Vol. 19, no 4, p. 3046-3096Article in journal (Refereed)
    Abstract [en]

    Molecular communication (MC) and molecular network (MN) are communication paradigms that use biochemical signalling to achieve information exchange among naturally and artificially synthesized nanosystems. Among the envisaged application areas of MC and MN is the field of nanomedicine where the subject of targeted drug delivery (TDD) is at the forefront. Typically, when someone gets sick, therapeutic drugs are administered to the person for healing purpose. Since no therapeutic drug can be effective until it is delivered to the target site in the body, different modalities to improve the delivery of drugs to the targeted sites are being explored in contemporary research. The most promising of these modalities is TDD. TDD modality promises a smart localization of appropriate dose of therapeutic drugs to the targeted part of the body at reduced system toxicity. Research in TDD has been going on for many years in the field of medical science; however, the translation of expectations and promises to clinical reality has not been satisfactorily achieved because of several challenges. The exploration of TDD ideas under the MC and MN paradigms is considered as an option to addressing these challenges and to facilitate the translation of TDD from the bench to the patients’ bedsides. Over the past decade, there have been some research efforts made in exploring the ideas of TDD on the MC and MN platforms. While the number of research output in terms of scientific articles is few at the moment, the desire in the scientific community to participate in realizing the goal of TDD is quite high as is evidence from the rise in research output over the last few years. To increase awareness and provide the multidisciplinary research community with the necessary background information on TDD, this paper presents a visionary survey of this subject within the domain of MC and MN. We start by introducing in an elaborate manner, the motivation behind the application of MC and MN paradigms to the study and implementation of TDD. Specifically, an explanation on how MC-based TDD concepts differ from traditional TDD being explored under the field of medical science is provided. We also summarize the taxonomy of the different perspectives through which MC-based TDD research can be viewed. System models and design challenges/requirements for developing MC-based TDD are discussed. Various metrics that can be used to evaluate the performance of MC-based TDD systems are highlighted. We also provide a discussion on the envisaged path from contemporary research activities to clinical implementation of the MC-based TDD. Finally, we discuss issues such as informatics and software tools, as well as issues that border on the requirement for standards and regulatory policies in MC-based TDD research and practice.

  • 187.
    Saxena, Neetesh
    et al.
    Georgia Institute of Technology.
    Grijalva, Santiago
    Georgia Institute of Technology.
    Chukwuka, Victor
    Georgia Institute of Technology.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Network Security and Privacy Challenges in Smart Vehicle-to-Grid2017In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 24, no 4, p. 88-98Article in journal (Refereed)
    Abstract [en]

    Smart vehicle-to-grid (V2G) involves intelligent charge and discharge decisions based on user operational energy requirements, such as desired levels of charging and waiting time. V2G is also supported by information management capabilities enabled by a secure network, such as a reliable privacy-preserving payment system. In this article, we describe the network security and privacy requirements and challenges of V2G applications. We present a new network security architecture to support V2G. We propose a scheme with the following security and privacy-preserving features: anonymous authentication, fine-grained access control, anonymous signatures, information confidentiality, message integrity, remote attestation, and a payment system. This article is oriented toward practitioners interested in designing and implementing secure and privacy-preserving networks for smart V2G applications.

  • 188.
    Wang, Qiu
    et al.
    Faculty of Information Technology, Macau University of Science and Technology, Macau.
    Dai, Hong-Ning
    Faculty of Information Technology, Macau University of Science and Technology, Macau.
    Zheng, Zibin
    School of Data and Computer Science, Sun Yat-Sen University, Guangzhou .
    Imran, Muhammad
    College of Computer and Information Sciences, King Saud University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    On Connectivity of Wireless Sensor Networks with Directional Antennas2017In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 1, article id E134Article in journal (Refereed)
    Abstract [en]

    In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

  • 189.
    Chen, Lin
    et al.
    Laboratory Recherche Informatique (LRI-CNRS UMR 8623), Université Paris-Sud.
    Li, Yong
    Department of Electronic Engineering, Tsinghua University, Bejing.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    On Oblivious Neighbor Discovery in Distributed Wireless Networks With Directional Antennas: Theoretical Foundation and Algorithm Design2017In: IEEE/ACM Transactions on Networking, ISSN 1063-6692, E-ISSN 1558-2566, Vol. 25, no 4, p. 1982-1993Article in journal (Refereed)
    Abstract [en]

    Neighbor discovery, one of the most fundamental bootstrapping networking primitives, is particularly challenging in decentralized wireless networks where devices have directional antennas. In this paper, we study the following fundamental problem, which we term oblivious neighbor discovery: How can neighbor nodes with heterogeneous antenna configurations discover each other within a bounded delay in a fully decentralised manner without any prior coordination or synchronisation? We establish a theoretical framework on the oblivious neighbor discovery and the performance bound of any neighbor discovery algorithm achieving oblivious discovery. Guided by the theoretical results, we then devise an oblivious neighbor discovery algorithm, which achieves guaranteed oblivious discovery with order-minimal worst case discovery delay in the asynchronous and heterogeneous environment. We further demonstrate how our algorithm can be configured to achieve a desired tradeoff between average and worst case performance.

  • 190.
    Rondeau, Éric
    et al.
    University of Lorraine.
    Khouki, Lyes
    University of Technology of Troyes.
    Georges, Jean-Philippe
    University of Lorraine.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Cherkaoui, Soumaya
    Sherbrooke University.
    On-Move 2016: Message from the Chairs2017In: Proceedings - Conference on Local Computer Networks, LCN, Piscataway, NJ, 2017, Vol. F126504, p. xxiv-, article id 7856126Conference paper (Refereed)
  • 191.
    Cherkaoui, Soumaya
    et al.
    Sherbrooke University.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Khoukhi, Lyes
    University of Technology of Troyes.
    Sahoo, Jagruti
    South Carolina State University.
    Johansson, Dan
    Umeå universitet.
    On-Move 2017 Message from the Chairs2017In: Proceedings: 2017 IEEE 42nd Conference on Local Computer Networks Workshops, LCN Workshops 2017, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. xv-, article id 8110191Conference paper (Refereed)
  • 192.
    Zhalgasbekova, Aigerim
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zaslavsky, Arkady
    CSIRO, Melbourne.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Saguna, Saguna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Jayaraman, Prem Prakash
    Swinburne University of Technology, Melbourne.
    Opportunistic Data Collection for IoT-Based Indoor Air Quality Monitoring2017In: Internet of Things, Smart Spaces, and Next Generation Networks and Systems: 17th International Conference, NEW2AN 2017, 10th Conference, ruSMART 2017, Third Workshop NsCC 2017, St. Petersburg, Russia, August 28–30, 2017, Proceedings / [ed] Galinina O., Andreev S., Balandin S., Koucheryavy Y., Cham: Springer, 2017, p. 53-65Conference paper (Refereed)
    Abstract [en]

    Opportunistic sensing advance methods of IoT data collection using the mobility of data mules, the proximity of transmitting sensor devices and cost efficiency to decide when, where, how and at what cost collect IoT data and deliver it to a sink. This paper proposes, develops, implements and evaluates the algorithm called CollMule which builds on and extends the 3D kNN approach to discover, negotiate, collect and deliver the sensed data in an energy- and cost-efficient manner. The developed CollMule software prototype uses Android platform to handle indoor air quality data from heterogeneous IoT devices. The CollMule evaluation is based on performing rate, power consumption and CPU usage of single algorithm cycle. The outcomes of these experiments prove the feasibility of CollMule use on mobile smart devices.

  • 193.
    Siddiquee, Kazy Noor E Alam
    et al.
    University of Science and Technology Chittagong.
    Khan, Faria Farjana
    University of Science and Technology Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Optimal Dynamic Routing Protocols for Agro-Sensor Communication in MANETs2017Conference paper (Refereed)
    Abstract [en]

    Recent developments in the area of Wireless sensor networks and Mobile ad hoc networks provide flexible and easy- to-deploycommunication means for a wide range of appli- cations without any need for an infrastructure being pre-con- figured. Our paper studies performance of proactive and reactive routing protocols in a scenario with agro-sensors. Our results, achieved by simulating a network both in OPNET Modeler and NS2, show that the AODV routing protocol performs better for a large-scale network (where node density is higher) while the DSR routing protocol performs better in a small-scale network given the particular scenario we studied.

  • 194.
    Schmidt, Mischa
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. NEC Laboratories Europe, Heidelberg.
    Moreno, M. Victoria
    Research Institute of Energy and Environment of Heidelberg (ifeu), Germany.
    Schülke, Anett
    NEC Laboratories Europe, Heidelberg, Germany.
    Macek, Karel
    Honeywell ACS Global Labs, Prague, Czech Republic.
    Mařik, Karel
    Honeywell ACS Global Labs, Prague, Czech Republic.
    Pastor, Alfonso Gordaliza
    Department of Technical Studies, Veolia Servicios LECAM, Valladolid, Spain.
    Optimizing legacy building operation: the evolution into data-driven predictive cyber-physical systems2017In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 148, p. 257-279Article in journal (Refereed)
    Abstract [en]

    Fossil fuels serve a substantial fraction of global energy demand, and one major energy consumer is the global building stock. In this work, we propose a framework to guide practitioners intending to develop advanced predictive building control strategies. The framework provides the means to enhance legacy and modernized buildings regarding energy efficiency by integrating their available instrumentation into a data-driven predictive cyber-physical system. For this, the framework fuses two highly relevant approaches and embeds these into the building context: the generic model-based design methodology for cyber-physical systems and the cross-industry standard process for data mining. A Spanish school's heating system serves to validate the approach. Two different data-driven approaches to prediction and optimization are used to demonstrate the methodological flexibility: (i) a combination of Bayesian regularized neural networks with genetic algorithm based optimization, and (ii) a reinforcement learning based control logic using fitted Q-iteration are both successfully applied. Experiments lasting a total of 43 school days in winter 2015/2016 achieved positive effects on weather-normalized energy consumption and thermal comfort in day-to-day operation. A first experiment targeting comfort levels comparable to the reference period lowered consumption by one-third. Two additional experiments raised average indoor temperatures by 2 K. The better of these two experiments only consumed 5% more energy than the reference period. The prolonged experimentation period demonstrates the cyber-physical system-based approach's suitability for improving building stock energy efficiency by developing and deploying predictive control strategies within routine operation of typical legacy buildings.

  • 195.
    Siddiquee, Kazy Noor E. Alam
    et al.
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Sarma, Dhiman
    Rangamati Science & Technology University, Department of Computer Science & Engineering, Rangamati.
    Nandi, Avijit
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Akhter, Sharmin
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Hossain, Sohrab
    University of Science & Technology Chittagong, Department of Computer Science & Engineering, Foys Lake, Chittagong.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Department of Computer Science & Engineering, Chittagong.
    Performance Analysis of a Surveillance System to Detect and Track Vehicles using Haar Cascaded Classifiers and Optical Flow method2017In: Proceedings of the 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), New York: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 258-263Conference paper (Refereed)
    Abstract [en]

    This paper presents the real time vehicle detection and tracking system, based on data, collected from a single camera. In this system, vehicles are detected by using Haar Feature-based Cascaded Classifier on static images, extracted from the video file. The advantage of this classifier is that, it uses floating numbers in computations and hence, 20% more accuracy can be achieved in comparison to other classifiers and features of classifiers such as LBP (Local Binary Pattern). Tracking of the vehicles is carried out using Lucas-Kanade and Horn Schunk Optical Flow method because it performs better than other methods such as Morphological and Correlation Transformations. The proposed system consists of vehicle detection and tracking; and it is evaluated by using real data, collected from the route networks of Chittagong City of Bangladesh.

  • 196.
    Siddiquee, Kazy Noor E Alam
    et al.
    University of Science and Technology Chittagong.
    Dhiman, Sarma
    Department of Computer Science and Engineering, Rangamati Science and Technology University, Rangamati.
    Nandi, Avijit
    Department of Computer Science and Engineering, University of Science and Technology Chittagong Foy's Lake, Chittagong, Bangladesh.
    Akhter, Sharmin
    Department of Computer Science and Engineering, University of Science and Technology Chittagong Foy's Lake, Chittagong, Bangladesh.
    Hossain, Sohrab
    Department of Computer Science and Engineering, University of Science and Technology Chittagong, Foy's Lake, Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    Performance analysis of a surveillance system to detect and track vehicles using Haar cascaded classifiers and optical flow method2017In: 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 258-263, article id 17595122Conference paper (Refereed)
    Abstract [en]

    This paper presents the real time vehicle detection and tracking system, based on data, collected from a single camera. In this system, vehicles are detected by using Haar Feature-based Cascaded Classifier on static images, extracted from the video file. The advantage of this classifier is that, it uses floating numbers in computations and hence, 20% more accuracy can be achieved in comparison to other classifiers and features of classifiers such as LBP (Local Binary Pattern). Tracking of the vehicles is carried out using Lucas-Kanade and Horn Schunk Optical Flow method because it performs better than other methods such as Morphological and Correlation Transformations. The proposed system consists of vehicle detection and tracking; and it is evaluated by using real data, collected from the route networks of Chittagong City of Bangladesh.

  • 197.
    Valenza, Gaetano
    et al.
    University of Pisa.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Perspective: It's All About Time2017In: IEEE Transactions on Nanobioscience, ISSN 1536-1241, E-ISSN 1558-2639, Vol. 16, no 4, p. 309-310Article in journal (Refereed)
    Abstract [en]

    New knowledge on multi-scale temporal dynamics linking nanobio-time series, seasonal changes, immune response, and gut mictobiota can milestone (neuro) science soon.

  • 198.
    Fan, Ye
    et al.
    Department of Information and Communication Engineering, Xi’an Jiaotong University, Xi’an, China.
    Liao, Xuewen
    Department of Information and Communication Engineering, Xi’an Jiaotong University, Xi’an, China.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Physical Layer Security Based on Interference Alignment in K-User MIMO Y Wiretap Channels2017In: IEEE Access, E-ISSN 2169-3536, Vol. 5, p. 5747-5759Article in journal (Refereed)
    Abstract [en]

    This paper studies the secure degree of freedom (SDOF) of the multiway relay wiretap system K -user MIMO Y wiretap channel, where each legitimate user equipped with M antennas intends to convey independent signals via an intermediate relay with N antennas. There exists an eavesdropper which is equipped with Neantennas close to the legitimate users. In order to eliminate the multiuser interference and keep the system security, interference alignment is mainly utilized in the proposed broadcast wiretap channel (BWC) and multi-access BWC (MBWC), and cooperative jamming is adopted as a supplementary approach in the MBWC model. The general feasibility conditions of the interference alignment are deduced asM≥K−1,2M>N and N≥((K(K−1))/2) . In the BWC model, we have deduced the secure degrees of freedom (SDOF) asKmin{M,N}−min{Ne,K(K−1)/2} , which is always a positive value. While in the MBWC model, the SDOF is given by Kmin{M,N} . Finally, since the relay transmits the synthesized signals of the legal signal and the jamming signal in the MBWC model, we propose a power allocation scheme to maximize the secrecy rate. Simulation results demonstrate that our proposed power allocation scheme can improve secrecy rate under various antenna configurations.

  • 199.
    Gao, Deyun
    et al.
    School of Electronic and Information Engineering, Beijing Jiaotong University.
    Rao, Ying
    China Academy of Electronics and Information Technology, Beijing.
    Foh, Huang Chen
    5GIC, Institute for Communication Systems, Department of Electrical and Electronic Engineering, University of Surrey.
    Zhang, Hongke
    School of Electronic and Information Engineering, Beijing Jiaotong University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    PMNDN: Proxy Based Mobility Support Approach in Mobile NDN Environment2017In: IEEE Transactions on Network and Service Management, ISSN 1932-4537, E-ISSN 1932-4537, Vol. 14, no 1, p. 191-203Article in journal (Refereed)
    Abstract [en]

    In this paper, we study the source mobility problem that exists in the current named data networking (NDN) architecture and propose a proxy-based mobility support approach named PMNDN to overcome the problem. PMNDN proposes using a proxy to efficiently manage source mobility. Besides, functionalities of the NDN access routers are extended to track the mobility status of a source and signal Proxy about a handoff event. With this design, a mobile source does not need to participate in handoff signaling which reduces the consumption of limited wireless bandwidth. PMNDN also features an ID that is structurally similar to the content name so that routing scalability of NDN architecture is maintained and addressing efficiency of Interest packets is improved. We illustrate the performance advantages of our proposed solution by comparing the handoff performance of the mobility support approaches with that in NDN architecture and current Internet architecture via analytical and simulation investigation. We show that PMNDN offers lower handoff cost, shorter handoff latency, and less packet losses during the handoff process

  • 200.
    Luo, Hongmin
    et al.
    School of Computer Science and Engineering, Beihang University, Beijing.
    Chen, Zhe
    Huawei Technologies.
    Li, Jiawei
    School of Electronic and Information Engineering, Beijing Jiaotong University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Preventing Distributed Denial-of-Service Flooding Attacks with Dynamic Path Identifiers2017In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 12, no 8, p. 1801-1805, article id 7888484Article in journal (Refereed)
    Abstract [en]

    In recent years, there are increasing interests in using path identifiers (PIDs) as inter-domain routing objects. However, the PIDs used in existing approaches are static, which makes it easy for attackers to launch distributed denial-ofservice (DDoS) flooding attacks. To address this issue, in this paper, we present the design, implementation, and evaluation of D-PID, a framework that uses PIDs negotiated between neighboring domains as inter-domain routing objects. In DPID, the PID of an inter-domain path connecting two domains is kept secret and changes dynamically. We describe in detail how neighboring domains negotiate PIDs, how to maintain ongoing communications when PIDs change. We build a 42-node prototype comprised by six domains to verify D-PID’s feasibility and conduct extensive simulations to evaluate its effectiveness and cost. The results from both simulations and experiments show that D-PID can effectively prevent DDoS attacks.

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