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  • 251.
    Wang, You
    et al.
    Institute for Network Sciences and Cyberspace, Tsinghua University.
    Bi, Jun
    Institute for Network Sciences and Cyberspace, Tsinghua University.
    Vasilakos, Athanasios
    University of Western Macedonia.
    An Identifier-Based Approach to Internet Mobility: A Survey2016In: IEEE Network, ISSN 0890-8044, E-ISSN 1558-156X, Vol. 30, no 1, p. 72-79Article in journal (Refereed)
  • 252.
    Nugent, Chris
    et al.
    Ulster University.
    Cleland, Ian
    Ulster University.
    Santanna, Anita
    Halmstad University.
    Espinilla, Macarena
    University of Jaén.
    Synnott, Jonathan
    Ulster University.
    Banos, Oresti
    University of Twente.
    Lundström, Jens
    Halmstad Universitet.
    Hallberg, Josef
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Calzada, Alberto
    Ulster University.
    An initiative for the creation of open datasets within pervasive healthcare2016In: Proceedings of the 10th EAI International Conference onPervasive Computing Technologies for Healthcare: 16-19 May 2016, Cancun, Mexico, ICST, the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , 2016, p. 318-321Conference paper (Refereed)
    Abstract [en]

    In this paper issues surrounding the collection, annotation, management and sharing of data gathered from pervasive health systems are presented. The overarching motivation for this work has been to provide an approach whereby annotated data sets can be made readily accessible to the research community in an effort to assist the advancement of the state-of-the-art in activity recognition and behavioural analysis using pervasive health systems. Recommendations of how this can be made a reality are presented in addition to the initial steps which have been taken to facilitate such an initiative involving the definition of common formats for data storage and a common set of tools for data processing and visualization.

  • 253.
    Klimova, Alexandra
    et al.
    ITMO University.
    Rondeau, Eric
    Université de Lorraine, Nancy.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Porras, Jari
    Lappeenranta University of Technology.
    Rybin, Andrei
    ITMO University.
    Zaslavsky, Arkady
    CSIRO, Australia.
    An international Master’s program in green ICT as a contribution to sustainable development2016In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 135, p. 223-239Article in journal (Refereed)
    Abstract [en]

    Various principles of sustainable development are currently being integrated into national policies and programs. Such principles relate to a range of aspects of human activities requiring urgent attention, including heating, mobility, food security, and sustainable agriculture. One of the fields contributing to the transition towards a sustainable society is that of green information and communication technologies (ICT). Therefore, the implementation of educational programs in green ICT is important in ensuring further ICT development around sustainability concerns. This article describes the development of an international Master's degree program named “Pervasive computing and communications for sustainable development” (PERCCOM) by an international consortium, which aimed to combine advanced ICT with environmental, economic, and social awareness. The article presents background information regarding the role of the ICT sector in environmental challenges, and a review of the literature, in order to understand what is required of ICT and green ICT graduates. The curriculum of the PERCCOM program is then described and findings on program improvement are reported. The article is aimed at academic and research professionals in the fields of sustainable development and green technologies, with the goal of improving educational initiatives to address the societal demand for sustainable development. The findings reported here contribute toward the search for a solution for sustainability, especially regarding environmental issues, among educating professionals with high expertise in networking, computing, and programming, who are able to design, develop, deploy, and maintain both pervasive computing systems and communication architectures for sustainable development.

  • 254.
    Mashayekhy, Lena
    et al.
    Department of Computer Science, Wayne State University, Detroit.
    Nejad, Mahyar Movahed
    Department of Computer Science, Wayne State University, Detroit.
    Grosu, Daniel
    Department of Computer Science, Wayne State University, Detroit.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An Online Mechanism for Resource Allocation and Pricing in Clouds2016In: I.E.E.E. transactions on computers (Print), ISSN 0018-9340, E-ISSN 1557-9956, Vol. 65, no 4, p. 1172-1184Article in journal (Refereed)
    Abstract [en]

    Cloud providers provision their various resources such as CPUs, memory, and storage in the form of virtual machine (VM) instances which are then allocated to the users. The users are charged based on a pay-as-you-go model, and their payments should be determined by considering both their incentives and the incentives of the cloud providers. Auction markets can capture such incentives, where users name their own prices for their requested VMs. We design an auction-based online mechanism for VM provisioning, allocation, and pricing in clouds that considers several types of resources. Our proposed online mechanism makes no assumptions about future demand of VMs, which is the case in real cloud settings. The proposed online mechanism is invoked as soon as a user places a request or some of the allocated resources are released and become available. The mechanism allocates VM instances to selected users for the period they are requested for, and ensures that the users will continue using their VM instances for the entire requested period. In addition, the mechanism determines the payment the users have to pay for using the allocated resources. We prove that the mechanism is incentive-compatible, that is, it

  • 255.
    Zhang, Weizhe
    et al.
    School of Computer Science and Technology, Harbin Institute of Technology.
    Li, Xiong
    School of Computer Science and Technology, Harbin Institute of Technology.
    Xiong, Naixue
    Department of Business and Computer Science, Southwestern Oklahoma State University, Oklahoma, OK.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Android platform-based individual privacy information protection system2016In: Personal and Ubiquitous Computing, ISSN 1617-4909, E-ISSN 1617-4917, Vol. 20, no 6, p. 875-884Article in journal (Refereed)
    Abstract [en]

    With the popularity of mobile phones with Android platform, Android platform-based individual privacy information protection has been paid more attention to. In consideration of individual privacy information problem after mobile phones are lost, this paper tried to use SMS for remote control of mobile phones and providing comprehensive individual information protection method for users and completed a mobile terminal system with self-protection characteristics. This system is free from the support of the server and it can provide individual information protection for users by the most basic SMS function, which is an innovation of the system. Moreover, the protection mechanism of the redundancy process, trusted number mechanism and SIM card detection mechanism are the innovations of this system. Through functional tests and performance tests, the system could satisfy user functional and non-functional requirements, with stable operation and high task execution efficiency

  • 256.
    Idowu, Samuel
    et al.
    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.
    Åhlund, Christer
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Schelén, Olov
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Applied Machine Learning: Forecasting Heat Load in District Heating System2016In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 133, p. 478-488Article in journal (Refereed)
    Abstract [en]

    Forecasting energy consumption in buildings is a key step towards the realization of optimized energy production, distribution and consumption. This paper presents a data driven approach for analysis and forecast of aggregate space and water thermal load in buildings. The analysis and the forecast models are built using district heating data unobtrusively collected from ten residential and commercial buildings located in Skellefteå, Sweden. The load forecast models are generated using supervised machine learning techniques, namely, support vector machine, regression tree, feed forward neural network, and multiple linear regression. The model takes the outdoor temperature, historical values of heat load, time factor variables and physical parameters of district heating substations as its input. A performance comparison among the machine learning methods and identification of the importance of models input variables is carried out. The models are evaluated with varying forecast horizons of every hour from 1 up to 48 hours. Our results show that support vector machine, feed forward neural network and multiple linear regression are more suitable machine learning methods with lower performance errors than the regression tree. Support vector machine has the least normalized root mean square error of 0.07 for a forecast horizon of 24 hour.

  • 257. Nanda, Rohan
    et al.
    Saguna, Saguna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Åhlund, Christer
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    BayesForSG: A Bayesian Model for Forecasting Thermal Load in Smart Grids2016In: SAC '16: Proceedings of the 31st Annual ACM Symposium on Applied Computing, New York: ACM Digital Library, 2016, p. 2135-2141Conference paper (Refereed)
    Abstract [en]

    Forecasting the thermal load demand for residential buildings assists in optimizing energy production and developing demand response strategies in a smart grid system. However, the presence of a large number of factors such as outdoor temperature, district heating operational parameters, building characteristics and occupant behavior, make thermal load forecasting a challenging task. This paper presents an efficient model for thermal load forecast in buildings with different variations of heat load consumption across both winter and spring seasons using a Bayesian Network. The model has been validated by utilizing the realistic district heating data of three residential buildings from the district heating grid of the city of Skellefteå, Sweden over a period of four months. The results from our model shows that the current heat load consumption and outdoor temperature forecast have the most influence on the heat load forecast. Further, our model outperforms state-of-the-art methods for heat load forecasting by achieving a higher average accuracy of 77.97% by utilizing only 10% of the training data for a forecast horizon of 1 hour.

  • 258.
    Tsai, Chun-Wei
    et al.
    Department of Computer Science and Information Engineering, National Ilan University, Yilan.
    Lai, Chin-Feng
    Institute of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi.
    Chao, Han-Chieh
    Department of Computer Science and Information Engineering, National Ilan University, Yilan.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Big Data Analytics2016In: Big Data Technologies and Applications, Springer International Publishing , 2016, p. 13-52Chapter in book (Refereed)
    Abstract [en]

    The age of big data is now coming. But the traditional data analytics may not be able to handle such large quantities of data. The question that arises now is, how to develop a high performance platform to efficiently analyze big data and how to design an appropriate mining algorithm to find the useful things from big data. To deeply discuss this issue, this paper begins with a brief introduction to data analytics, followed by the discussions of big data analytics. Some important open issues and further research directions will also be presented for the next step of big data analytics.

  • 259.
    Yaqoob, Ibrar
    et al.
    Centre for Mobile Cloud Computing Research (C4MCCR), Faculty of Computer Science and Information Technology, University of Malaya.
    Abaker Targio Hashem, Ibrahim
    Centre for Mobile Cloud Computing Research (C4MCCR), Faculty of Computer Science and Information Technology, University of Malaya.
    Gani, Abdullah
    Centre for Mobile Cloud Computing Research (C4MCCR), Faculty of Computer Science and Information Technology, University of Malaya.
    Mokhtar, Salimah
    Centre for Mobile Cloud Computing Research (C4MCCR), Faculty of Computer Science and Information Technology, University of Malaya.
    Ahmed, Ejaz
    Centre for Mobile Cloud Computing Research (C4MCCR), Faculty of Computer Science and Information Technology, University of Malaya.
    Badrul Anuar, Nor
    Centre for Mobile Cloud Computing Research (C4MCCR), Faculty of Computer Science and Information Technology, University of Malaya.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Big data: From beginning to future2016In: International Journal of Information Management, ISSN 0268-4012, E-ISSN 1873-4707, Vol. 36, no 6B, p. 1231-1247Article in journal (Refereed)
    Abstract [en]

    Big data is a potential research area receiving considerable attention from academia and IT communities. In the digital world, the amounts of data generated and stored have expanded within a short period of time. Consequently, this fast growing rate of data has created many challenges. In this paper, we use structuralism and functionalism paradigms to analyze the origins of big data applications and its current trends. This paper presents a comprehensive discussion on state-of-the-art big data technologies based on batch and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also discusses big data analytics techniques, processing methods, some reported case studies from different vendors, several open research challenges, and the opportunities brought about by big data. The similarities and differences of these techniques and technologies based on important parameters are also investigated. Emerging technologies are recommended as a solution for big data problems.

  • 260.
    Yu, Yong
    et al.
    Big Data Research Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu.
    Xue, Liang
    Department of Computing, The Hong Kong Polytechnic University.
    Au, Man Ho
    Department of Computing, The Hong Kong Polytechnic University.
    Susilo, Willy
    Center for Computer and Information Security Research, School of Computing and Information Technology, University of Wollongong.
    Ni, Jianbin
    Big Data Research Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu.
    Zhang, Yafang
    Big Data Research Center, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Shen, Jian
    School of Computer and Software at Nanjing University of Information Science and Technology, Nanjing.
    Cloud data integrity checking with an identity-based auditing mechanism from RSA2016In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 62, p. 85-91Article in journal (Refereed)
    Abstract [en]

    Cloud data auditing is extremely essential for securing cloud storage since it enables cloud users to verify the integrity of their outsourced data efficiently. The computation overheads on both the cloud server and the verifier can be significantly reduced by making use of data auditing because there is no necessity to retrieve the entire file but rather just use a spot checking technique. A number of cloud data auditing schemes have been proposed recently, but a majority of the proposals are based on Public Key Infrastructure (PKI). There are some drawbacks in these protocols: (1) It is mandatory to verify the validity of public key certificates before using any public key, which makes the verifier incur expensive computation cost. (2) Complex certificate management makes the whole protocol inefficient. To address the key management issues in cloud data auditing, in this paper, we propose ID-CDIC, an identity-based cloud data integrity checking protocol which can eliminate the complex certificate management in traditional cloud data integrity checking protocols. The proposed concrete construction from RSA signature can support variable-sized file blocks and public auditing. In addition, we provide a formal security model for ID-CDIC and prove the security of our construction under the RSA assumption with large public exponents in the random oracle model. We demonstrate the performance of our proposal by developing a prototype of the protocol. Implementation results show that the proposed ID-CDIC protocol is very practical and adoptable in real life.

  • 261.
    Wan, Jiafu
    et al.
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Tang, Shenglong
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Li, Di
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Cloud Robotics: Current Status and Open Issues2016In: IEEE Access, E-ISSN 2169-3536, Vol. 4, p. 2797-2807Article in journal (Refereed)
    Abstract [en]

    With the development of cloud computing, big data and other emerging technologies, the integration of cloud technology and multi-robot systems makes it possible to design multi-robot systems with improved energy efficiency, high real-time performance and low cost. In order to address the potential of clouds in enhancing robotics for industrial systems, this paper describes the basic concepts and development process of cloud robotics and the overall architecture of these systems. Then, the major driving forces behind the development of cloud robotics are carefully analyzed from the point of view of cloud computing, big data, open source resources, robot cooperative learning, and network connectivity. Subsequently, the key issues and challenges in the current cloud robotic systems are proposed, and some possible solutions are also given. Finally, the potential value of cloud robotic systems in different practical applications is discussed.

  • 262.
    Rizk, Aya
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Johansson, Jan-Olov
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Holst, Marita
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Heijnen, Adriënne
    Palacios, Belén
    Lynch, John
    Harderberg, Esben
    Lindstrøm, Michelle
    Christophersen, Sebastian
    Cuenca, Juan
    Gutiérrez, Veronica
    Theodoridis, Evangelos
    Etienne, Gandrille
    Co-Creating Smart Cities of the Future: First Open Call Instructions2016Report (Other academic)
  • 263.
    Khan, Zaheer
    et al.
    Centre for Wireless Communications, University of Oulu.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Barua, Bidushi
    Centre for Wireless Communications, University of Oulu.
    Shahabuddin, Shahriar
    Centre for Wireless Communications, University of Oulu.
    Ahmadi, Hamed
    CTVR, Trinity College Dublin.
    Cooperative content delivery exploiting multiple wireless interfaces: methods, new technological developments, open research issues and a case study2016In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 22, no 6, p. 1961-1983Article in journal (Refereed)
    Abstract [en]

    In this tutorial paper, we discuss and compare cooperative content delivery (CCD) techniques that exploit multiple wireless interfaces available on mobile devices to efficiently satisfy the already massive and rapidly growing user demand for content. The discussed CCD techniques include simultaneous use of wireless interfaces, opportunistic use of wireless interfaces, and aggregate use of wireless interfaces. We provide a taxonomy of different ways in which multiple wireless interfaces are exploited for CCD, and also discuss the real measurement studies that evaluate the content delivery performance of different wireless interfaces in terms of energy consumption and throughput. We describe several challenges related to the design of CCD methods using multiple interfaces, and also explain how new technological developments can help in accelerating the performance of such CCD methods. The new technological developments discussed in this paper include wireless interface aggregation, network caching, and the use of crowdsourcing. We provide a case study for selection of devices in a group for CCD using multiple interfaces. We consider this case study based on the observation that in general different CCD users can have different link qualities in terms of transmit/receive performance, and selection of users with good link qualities for CCD can accelerate the content delivery performance of wireless networks. Finally, we discuss some open research issues relating to CCD using multiple interfaces.

  • 264.
    Kundu, Arghya
    et al.
    Lexmark International Pvt. Ltd. Kolkata, India.
    Laha, Sougata
    School of Computer Engineering Nanyang Technological University, Singapore.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Correlation-based genetic algorithm for real-parameter optimization2016In: 2016 IEEE Congress on Evolutionary Computation (CEC), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 4804-4809, article id 7744405Conference paper (Refereed)
    Abstract [en]

    We propose a genetic algorithm (GA) by taking into account the correlation between the current best candidate with the other candidates in the population. In this paper we propose a new selection operator and in addition we have designed a prediction operator which works on an archive of selected candidates. We test our proposed algorithm on the problem definitions for the CEC 2014 special session and competition on single objective real-parameter numerical optimization.

  • 265.
    Wang, Sen
    et al.
    School of Software Engineering, Chongqing University, and Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, Chongqing.
    Bi, Jun
    Institute for Network Sciences and Cyberspace, Tsinghua University.
    Wu, Jianping
    Institute for Network Sciences and Cyberspace, Tsinghua University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    CPHR: In-Network Caching for Information-Centric Networking With Partitioning and Hash-Routing2016In: IEEE/ACM Transactions on Networking, ISSN 1063-6692, E-ISSN 1558-2566, Vol. 24, no 5, p. 2742-2755Article in journal (Refereed)
    Abstract [en]

    Recently, research on Information-Centric Networking (ICN) has flourished, which attempts to shift from the current host-oriented Internet architecture to an information-oriented one. The built-in caching capability is a typical feature of ICN. In this paper, in order to fully exploit the built-in caching capability of ICN, we propose a collaborative in-network caching scheme with Content-space Partitioning and Hash-Routing, which is named as CPHR. By intelligently partitioning the content space and assigning partitions to caches, CPHR is able to constrain the path stretch incurred by hash-routing. We formulate the problem of assigning partitions to caches into an optimization problem of maximizing the overall hit ratio and propose a heuristic algorithm to solve it. We also formulate the partitioning proportion problem into a min-max linear optimization problem to balance cache workloads. By simulations with both the characteristics of real Internet traffic and traces of peer-to-peer (P2P) traffic, we show the necessity of collaborative caching since the en-route caching mode cannot yield a considerable overall hit ratio with practical cache size. It is shown as well that CPHR can significantly increase the overall hit ratio by up to about 100% with the practical cache policy Least Recently Used (LRU) while the overhead incurred is acceptable in terms of propagation latency and load on links.

  • 266.
    Rho, Seungmin
    et al.
    Department of Multimedia, Sungkyul University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Chen, Weifeng
    Department of Math, Computer Science and Information Systems, California University of Pennsylvania.
    Cyber physical systems technologies and applications2016In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 56, p. 436-437Article in journal (Other academic)
    Abstract [en]

    With the rapid progresses in ICT (Information Communication Technology), multidisciplinary research fields such as Internet of Things (IoT), Cyber-Physical System (CPS), and Social Computing have been widely explored in recent years. These research and application have been speeded up the formation of cyberspace, which will further lead to a subversive change for information science development as well as human production and living (Ma and Yang, 2015 [1]). Cyberspace is being linked to versatile individuals in physical space and social space — Cyber-Physical Society (CPSoc) (Zhuge, 2014 [2]). This special issue on new technologies and research trends for cyber physical systems technologies and application provides high quality contributions addressing related theoretical and practical aspects of CPS technologies and their applications. We have selected five research papers whose topics are strongly related to this special issue.

  • 267.
    Rho, Seungmin
    et al.
    Department of Multimedia, Sungkyul University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Chen, Weifeng
    Department of Math, Computer Science and Information Systems, California University of Pennsylvania.
    Cyber physical systems technologies and applications: Part II2016In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 61, p. 83-84Article in journal (Other academic)
    Abstract [en]

    The second part of the special issue presents more practical issues on cyber physical systems technologies and application. We have selected five research papers whose topics are strongly related to this special issue. As continued from the part 1, we have selected 5 additional papers

  • 268.
    Socievole, Annalisa
    et al.
    DIMES, Ponte P. Bucci, University of Calabria.
    Zivani, Artur
    National Laboratory for Scientific Computing (LNCC).
    de Rango, Floriano
    DIMES, Ponte P. Bucci, University of Calabria.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yoneki, Eiko
    University of Cambridge Computer Laboratory, JJ Thomson Avenue Cambridge.
    Cyber-physical systems for Mobile Opportunistic Networking in Proximity (MNP)2016In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069, Vol. 111, p. 1-5Article in journal (Refereed)
  • 269.
    Lindgren, Anders
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Abdesslem, Fehmi Ben
    SICS Swedish ICT AB.
    Ahlgren, Bengt
    SICS Swedish ICT AB.
    Schelén, Olov
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Malik, Adeel Mohammad
    Ericsson.
    Design choices for the IoT in Information-Centric Networks2016In: 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC): Las Vegas, 9-12 Jan. 2016, Piscataway, NJ: IEEE Communications Society, 2016, p. 882-888, article id 7444905Conference paper (Refereed)
    Abstract [en]

    This paper outlines the tradeoffs involved in utilizing Information-Centric Networking (ICN) for Internet of Things (IoT) scenarios. It describes contexts and applications where the IoT would benefit from ICN, and where a host-centric approach would be better. Requirements imposed by the heterogeneous nature of IoT networks are discussed in terms of connectivity, power availability, computational and storage capacity. Design choices are then proposed for an IoT architecture to handle these requirements, while providing efficiency and scalability. An objective is to not require any IoT specific changes of the ICN architecture per se, but we do indicate some potential modifications of ICN that would improve efficiency and scalability for IoT and other applications

  • 270.
    Gong, Yueyuan
    et al.
    Department of Computer and Information Science, University of Macau.
    Fong, Simon
    Department of Computer and Information Science, University of Macau.
    Wong, Raymond K.
    School of Computer Science and Engineering, University of New South Wales, Sydney.
    Mohammed, Sabah
    Department of Computer Science, Lakehead University, Thunder Bay.
    Faidhi, Jinan
    Department of Computer Science, Lakehead University, Thunder Bay.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Discovering sub-patterns from time series using a normalized cross-match algorithm2016In: Journal of Supercomputing, ISSN 0920-8542, E-ISSN 1573-0484, Vol. 72, no 10, p. 3850-3867Article in journal (Refereed)
    Abstract [en]

    Time series data stream mining has attracted considerable research interest in recent years. Pattern discovery is a challenging problem in time series data stream mining. Because the data update continuously and the sampling rates may be different, dynamic time warping (DTW)-based approaches are used to solve the pattern discovery problem in time series data streams. However, the naive form of the DTW-based approach is computationally expensive. Therefore, Toyoda proposed the CrossMatch (CM) approach to discover the patterns between two time series data streams (sequences), which requires only O(n) time per data update, where n is the length of one sequence. CM, however, does not support normalization, which is required for some kinds of sequences (e.g. stock prices, ECG data). Therefore, we propose a normalized-CrossMatch approach that extends CM to enforce normalization while maintaining the same performance capabilities.

  • 271.
    Xie, Yao
    et al.
    Shanghai Jiao Tong University.
    Liu, Xiao-Yang
    Shanghai Jiao Tong University.
    Kong, Linghe
    Shanghai Jiao Tong University.
    Wu, Fan
    Shanghai Jiao Tong University.
    Chen, Guihai
    Shanghai Jiao Tong University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Drone-Based Wireless Relay using Online Tensor Update2016In: 2016 IEEE 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS) / [ed] Liao, X; Lovas, R; Shen, X; Zheng, R, Piscataway, NJ: IEEE Computer Society, 2016, p. 48-55, article id 7823731Conference paper (Refereed)
    Abstract [en]

    In the wireless communication, there are many cases where the transmission path is obstructed by unknown objects. With the rapid development of the drone technology in recent years, the drones are advocated to serve as mobile relays to forward data streams. However, the challenges are that data transmission may suffer severe signal attenuation due to the existence of the obstructions and it is challenging to find the best location for mobile relays due to the dynamic environment and unpredictable interference. To address the problem, this paper proposes an approach that a drone can automatically find the location with the optimal link quality. We design a novel algorithm, named Path-sampling Online Tensor Update (POTU), to estimate the link quality in the space and find the optimal location. Furthermore, the algorithm is practical to the real applications due to the simplicity of implementation. In the experiment, we construct a realistic scene and compare the performance of our algorithm with the classic and the state-of-the-art algorithms. As a result, POTU outperforms existing methods in achieving the trade-off between time cost and estimation accuracy.

  • 272.
    Akbar, Mariam
    et al.
    COMSATS Institute of Information Technology, Islamabad.
    Javaid, Nadeem
    COMSATS Institute of Information Technology, Islamabad.
    Kahn, Ayesha Hussain
    COMSATS Institute of Information Technology, Islamabad.
    Imran, Muhammad Al
    College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
    Shoaib, Muhammad
    College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Efficient Data Gathering in 3D Linear Underwater Wireless Sensor Networks Using Sink Mobility2016In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 16, no 3, article id 404Article in journal (Refereed)
    Abstract [en]

    Due to the unpleasant and unpredictable underwater environment, designing an energy-efficient routing protocol for underwater wireless sensor networks (UWSNs) demands more accuracy and extra computations. In the proposed scheme, we introduce a mobile sink (MS), i.e., an autonomous underwater vehicle (AUV), and also courier nodes (CNs), to minimize the energy consumption of nodes. MS and CNs stop at specific stops for data gathering; later on, CNs forward the received data to the MS for further transmission. By the mobility of CNs and MS, the overall energy consumption of nodes is minimized. We perform simulations to investigate the performance of the proposed scheme and compare it to preexisting techniques. Simulation results are compared in terms of network lifetime, throughput, path loss, transmission loss and packet drop ratio. The results show that the proposed technique performs better in terms of network lifetime, throughput, path loss and scalability

  • 273.
    Zhang, Baoxian
    et al.
    Research Center of Ubiquitous Sensor Networks, University of Chinese Academy of Sciences, Beijing.
    Jiao, Shenzhen
    Research Center of Ubiquitous Sensor Networks, University of Chinese Academy of Sciences, Beijing.
    Li, Cheng
    Electrical and Computer Engineering, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's.
    Jiao, Zheng
    Research Center of Ubiquitous Sensor Networks, University of Chinese Academy of Sciences, Beijing.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Efficient location-based topology control algorithms for wireless ad hoc and sensor networks2016In: Wireless Communications & Mobile Computing, ISSN 1530-8669, E-ISSN 1530-8677, Vol. 16, no 14, p. 1943-1955Article in journal (Refereed)
    Abstract [en]

    Topology control is an efficient strategy for improving the performance of wireless ad hoc and sensor networks by building network topologies with desirable features. In this process, location information of nodes can be used to improve the performance of a topology control algorithm and also ease its operations. Many location-based topology control algorithms have been proposed. In this paper, we propose two location-assisted grid-based topology control (GBP) algorithms. The design objective of our algorithm is to effectively reduce the number of active nodes required to keep global network connectivity. In grid-based topology control, a network is divided into equally spaced squares (called grids). We accordingly design cross-sectional topology control algorithm and diagonal topology control algorithm based on different network parameter settings. The key idea is to build near-minimal connected dominating set for the network at the grid level. Analytical and simulation results demonstrate that our designed algorithms outperform existing work. Furthermore, the diagonal algorithm outperforms the cross-sectional algorithm

  • 274.
    Zhu, Nanhao
    et al.
    CETC Group, GCI Science and Technology Co.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    EMrise: An Energy Management Platform for WSNs/WBANs2016In: Energy Management in Wireless Cellular and Ad-hoc Networks, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 367-395Chapter in book (Refereed)
    Abstract [en]

    Due to reliance on batteries, energy consumption has always been of significant concern for sensor node networks. This work presents the design and implementation of a house-build experimental platform, named EMrise (Energy Management System for Wireless Sensor Networks) for the energy management and exploration on wireless sensor networks. Consisting of three parts, the SystemC-based simulation environment of EMrise enables the HW/SW co-simulation for energy evaluation on heterogeneous sensor networks. The hardware platform of EMrise is further designed to facilitate the realistic energy consumption measurement and calibration as well as accurate energy exploration. In the meantime, a generic GA (genetic algorithm) based optimization framework of EMrise is also implemented to automatically, quickly and intelligently fine tune hundreds of possible solutions for the given task to find the best suitable energy-aware tradeoffs.

  • 275.
    Vinel, Alexey
    et al.
    School of Information Technology, Halmstad University.
    Chen, Wen-Shyen Eric
    ProphetStor.
    Xiong, Neal N.
    Department of Business and Computer Science, Southwestern Oklahoma State University.
    Rho, Seungmin
    Department of Media Software at Sungkyul University.
    Chilamkurti, Naveen
    Department of Computer Science and Telecommunications, La Trobe University, Melbourne.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Enabling wireless communication and networking technologies for the internet of things: Guest editorial2016In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 23, no 5, p. 8-9Article in journal (Other academic)
    Abstract [en]

    The Internet of Things (IoT) is enabling ubiquitous computing with a novel design paradigm to integrate global physical objects, cyber and social spaces, and machines. It may be envisaged as a web of trillions of machines that will communicate with each other. The major enabling technologies that are giving a flying kickstart to IoT are ad hoc and wireless sensor networks, short-range wireless communications, real-time systems, low power and energy harvesting, radio frequency identification, machine type communication, resource-constrained networks, and embedded software.

  • 276.
    Yan, Zheng
    et al.
    State Key Laboratory on Integrated Services Networks, Xidian University.
    Wang, Mingjun
    State Key Laboratory on Integrated Services Networks, Xidian University.
    Li, Yuxian
    State Key Laboratory on Integrated Services Networks, Xidian University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Encrypted Data Management with Deduplication in Cloud Computing2016In: I E E E Cloud Computing, ISSN 2325-6095, Vol. 3, no 2, p. 28-35Article in journal (Refereed)
    Abstract [en]

    Cloud computing plays an important role in supporting data storage, processing, and management in the Internet of Things (IoT). To preserve cloud data confidentiality and user privacy, cloud data are often stored in an encrypted form. However, duplicated data that are encrypted under different encryption schemes could be stored in the cloud, which greatly decreases the utilization rate of storage resources, especially for big data. Several data deduplication schemes have recently been proposed. However, most of them suffer from security weakness and lack of flexibility to support secure data access control. Therefore, few can be deployed in practice. This article proposes a scheme based on attribute-based encryption (ABE) to deduplicate encrypted data stored in the cloud while also supporting secure data access control. The authors evaluate the scheme's performance based on analysis and implementation. Results show the efficiency, effectiveness, and scalability of the scheme for potential practical deployment.

  • 277.
    Hu, Jiankun
    et al.
    University of New South Wales, Canberra.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Energy Big Data Analytics and Security: Challenges and Opportunities2016In: IEEE Transactions on Smart Grid, ISSN 1949-3053, E-ISSN 1949-3061, Vol. 7, no 5, p. 2423-2436Article in journal (Refereed)
    Abstract [en]

    The limited available fossil fuels and the call for sustainable environment have brought about new technologies for the high efficiency in the use of fossil fuels and introduction of renewable energy. Smart grid is an emerging technology that can fulfill such demands by incorporating advanced information and communications technology (ICT). The pervasive deployment of the advanced ICT, especially the smart metering, will generate big energy data in terms of volume, velocity, and variety. The generated big data can bring huge benefits to the better energy planning, efficient energy generation and distribution. As such data involve end users’ privacy and secure operation of the critical infrastructure, there will be new security issues. This paper is to survey and discuss new findings and developments in the existing big energy data analytics and security. Several taxonomies have been proposed to express the intriguing relationships of various variables in the field.

  • 278.
    Shakir, Muhammad Zeeshan
    et al.
    Department of Systems and Computer Carleton University, Ottawa.
    Imran, Muhammad AliCenter for Communication, University of Surrey.Qaraqe, Khalid A,Department of Electrical and Computer, Texas A&M University.Alouini, Mohamed-SlimScience and Technology, King Abdallah University.Vasilakos, AthanasiosLuleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Energy Management in Wireless Cellular and Ad-hoc Networks2016Collection (editor) (Refereed)
  • 279.
    Wang, Yufeng
    et al.
    Nanjing University of Posts and Telecommunications, Nanjing.
    Bu, Yuanting
    Nanjing University of Posts and Telecommunications, Nanjing.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Jin, Qun
    Waseda University.
    Energy-Efficient Localization and Tracking on Smartphones: Design Principle and Solutions2016In: CFI '16: Proceedings of the 11th International Conference on Future Internet Technologies, New York: ACM Digital Library, 2016, p. 29-35Conference paper (Refereed)
    Abstract [en]

    In recent years, various location based services (LBS) have witnessed great development and are being prevalently used in our life. However, as the foundation of various LBS applications, localization consumes large energy of resource-constraint mobile terminals, especially on smartphones. This paper explicitly proposes three technical principles, substitution, adaption and collaboration to guide energy-efficient localization and tracking schemes on smartphones. Then several typical schemes in indoor or outdoor environments are respectively summarized and compared under the umbrella of those three principles. Moreover, the context-assisting techniques are also discussed to design energy-efficient LBS applications. Finally, the quantitative metrics to measure the tradeoff between energy and localization performance are summarized. The primary goal of this paper is to comprehensively classify and provide a summary on the sporadic localization schemes (with energy-efficiency as main concern), possible solutions and tradeoffs, and facilitate to develop and deploy the energy-efficient LBS applications.

  • 280.
    Solaiman, Ellis
    et al.
    Newcastle University, UK.
    Ranjan, Rajiv
    Newcastle University, UK.
    Jayaraman, Prem Prakash
    Swinburne University of Technology, Australia.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Failure Monitoring in the Internet of Things Application Ecosystems2016In: IT Professional Magazine, ISSN 1520-9202, E-ISSN 1941-045X, Vol. 18, no 5, p. 8-11, article id 7579107Article in journal (Refereed)
    Abstract [en]

    For Internet of Things (IoT) application ecosystems to excel, end-to-end components including the cloud, network, and edge devices must be highly dependable and resilient. This dependability must be verifiable by continuously monitoring the constituent components for conformance to defined behavior in terms of functional and nonfunctional requirements. However, the authors contend that current techniques and frameworks for monitoring the performance of hardware and application resources in distributed systems are not capable of monitoring and detecting root causes of failure and performance degradation for entire end-to-end IoT ecosystems. Motivated by this finding, they discuss their vision of future research into developing formal approaches for monitoring end-to-end IoT ecosystems.

  • 281.
    Vasilakos, Athanasios
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Duan, Qiang
    Pennsylvania State University.
    Federated selection of network and cloud services for high-performance software-defined cloud computing2016In: International Journal of High Performance Computing and Networking, ISSN 1740-0562, E-ISSN 1740-0570, Vol. 9, no 4, p. 316-327Article in journal (Refereed)
    Abstract [en]

    The crucial role of networking in cloud service provisioning calls for federated selection of network and cloud services in order to guarantee the service performance required by diverse applications. In order to address the new challenges brought in by the software-defined cloud environment (SDCE) to service selection, we develop an approach for performance-based federated selection of network and cloud services in this paper. The main contributions we make in this paper include an abstract profile for network/cloud service capability that is agnostic to service implementations, a general demand profile applicable to diverse applications, an analysis technique for evaluating achievable performance of composite network-cloud services, and a scheme for federated selection of network and cloud services based on performance evaluation. The technique and method developed in this paper enable service selection with a holistic vision across the networking and computing domains, which may greatly facilitate high-performance cloud service provisioning

  • 282.
    Alam, Quratulain
    et al.
    Department of Computer Sciences, Institute of Management Sciences, Peshawar.
    Tabbasum, Saher
    Department of Computer Sciences, COMSATS Institute of Information Technology, Islamabad.
    Malik, Saif U.R.
    Department of Computer Sciences, COMSATS Institute of Information Technology, Islamabad.
    Malik, Masoom
    Department of Computer Sciences, COMSATS Institute of Information Technology, Islamabad.
    Ali, Tamleek
    Department of Computer Sciences, Institute of Management Sciences, Peshawar.
    Akhunzada, Adnan
    Center for Mobile Cloud Computing Research (C4MCCR), University of Malaya, 50603 Kuala Lumpur.
    Khan, Samee U.
    Department of electrical and computer engineering, North Dakota State University, Fargo, ND.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Buyya, Rajkumar
    Cloud Computing and Distributed Systems, (CLOUDS) Laboratory, Department of Computing and Information Systems, The University of Melbourne.
    Formal Verification of the xDAuth Protocol2016In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 11, no 9, p. 1956-1969Article in journal (Refereed)
    Abstract [en]

    Service Oriented Architecture (SOA) offers a flexible paradigm for information flow among collaborating organizations. As information moves out of an organization boundary, various security concerns may arise, such as confidentiality, integrity, and authenticity that needs to be addressed. Moreover, verifying the correctness of the communication protocol is also an important factor. This paper focuses on the formal verification of the xDAuth protocol, which is one of the prominent protocols for identity management in cross domain scenarios. We have modeled the information flow of xDAuth protocol using High Level Petri Nets (HLPN) to understand protocol information flow in a distributed environment. We analyze the rules of information flow using Z language while Z3 SMT solver is used for verification of the model. Our formal analysis and verification results reveal the fact that the protocol fulfills its intended purpose and provides the security for the defined protocol specific properties, e.g. secure secret key authentication, Chinese wall security policy and secrecy specific properties, e.g. confidentiality, integrity, authenticity.

  • 283.
    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.
    Från idé till prototyp med hjälp av modern teknik i skolan2016In: Sinus, Vol. 2016, no 2, p. 22-23Article in journal (Other (popular science, discussion, etc.))
  • 284.
    Zhang, Zhongshan
    et al.
    University of Science and Technology, Beijing, Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services, University of Science and Technology Beijing (USTB).
    Long, Keping
    University of Science and Technology, Beijing, Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services, University of Science and Technology Beijing (USTB).
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hanzo, Lajos
    University of Southampton, School of Electronics and Computer Science, University of Southanpton.
    Full-Duplex Wireless Communications: Challenges, Solutions, and Future Research Directions2016In: Proceedings of the IEEE, ISSN 0018-9219, E-ISSN 1558-2256, Vol. 104, no 7, p. 1369-1409Article in journal (Refereed)
    Abstract [en]

    The family of conventional half-duplex (HD) wireless systems relied on transmitting and receiving in different time slots or frequency subbands. Hence, the wireless research community aspires to conceive full-duplex (FD) operation for supporting concurrent transmission and reception in a single time/frequency channel, which would improve the attainable spectral efficiency by a factor of two. The main challenge encountered in implementing an FD wireless device is the large power difference between the self-interference (SI) imposed by the device’s own transmissions and the signal of interest received from a remote source. In this survey, we present a comprehensive list of the potential FD techniques and highlight their pros and cons. We classify the SI cancellation techniques into three categories, namely passive suppression, analog cancellation and digital cancellation, with the advantages and disadvantages of each technique compared. Specifically, we analyze the main impairments (e.g., phase noise, power amplifier nonlinearity, as well as in-phase and quadrature-phase (I/Q) imbalance, etc.) that degrading the SI cancellation. We then discuss the FD-based media access control (MAC)-layer protocol design for the sake of addressing some of the critical issues, such as the problem of hidden terminals, the resultant end-to-end delay and the high packet loss ratio (PLR) due to network congestion. After elaborating on a variety of physical/MAC-layer techniques, we discuss potential solutions conceived for meeting the challenges imposed by the aforementioned techniques. Furthermore, we also discuss a range of critical issues related to the implementation, performance enhancement and optimization of FD systems, including important topics such as hybrid FD/HD scheme, optimal relay selection and optimal power allocation, etc. Finally, a variety of new directions and open problems associated with FD technology are pointed out. Our hope is that this treatise will stimul- te future research efforts in the emerging field of FD communications.

  • 285.
    Fan, Qingfeng
    et al.
    Laboratoire DAVID, University of Versailles-Saint-Quentin.
    Xiong, Naixue
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Department of Business and Computer Science, Southwestern Oklahoma State University.
    Zeitouni, Karine
    Laboratoire DAVID, University of Versailles-Saint-Quentin.
    Wu, Qiongli
    Laboratory Applied Mathematics and Systems, Ecole Centrale de Paris.
    Tian, Yu-Chu
    School of Electrical Engineering and Computer Science, Queensland University of Technology.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Game Balanced Multi-factor Multicast Routing in Sensor Grid Networks2016In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 367-368, p. 550-572Article in journal (Refereed)
    Abstract [en]

    In increasingly important sensor grid networks, multicast routing is widely used in date aggregation and distributed query processing. It requires multicast trees for efficient data transmissions. However, sensor nodes in such networks typically have limited resources and computing power. Efforts have been made to consider the space, energy and data factors separately to optimize the network performance. Considering these factors simultaneously, this paper presents a game balance based multi-factor multicast routing approach for sensor grid networks. It integrates the three factors into a unified model through a linear combination. The model is standardized and then solved theoretically by using the concept of game balance from game theory. The solution gives Nash equilibrium, implying a well balanced result for all the three factors. The theoretic results are implemented in algorithms for cluster formation, cluster core selection, cluster tree construction, and multicast routing. Extensive simulation experiments show that the presented approach gives mostly better overall performance than benchmark methods

  • 286.
    Mehboob, Usama
    et al.
    School of EE and CS, National University of Sciences and Technology (NUST), Islamabad.
    Qadir, Junaid
    Department of Electrical Engineering, Information Technology University (ITU), Punjab.
    Ali, Salman
    School of EE and CS, National University of Sciences and Technology (NUST), Islamabad.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Genetic algorithms in wireless networking: techniques, applications, and issues2016In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 20, no 6, p. 2467-2501Article in journal (Refereed)
    Abstract [en]

    In recent times, wireless access technology is becoming increasingly commonplace due to the ease of operation and installation of untethered wireless media. The design of wireless networking is challenging due to the highly dynamic environmental condition that makes parameter optimization a complex task. Due to the dynamic, and often unknown, operating conditions, modern wireless networking standards increasingly rely on machine learning and artificial intelligence algorithms. Genetic algorithms (GAs) provide a well-established framework for implementing artificial intelligence tasks such as classification, learning, and optimization. GAs are well known for their remarkable generality and versatility and have been applied in a wide variety of settings in wireless networks. In this paper, we provide a comprehensive survey of the applications of GAs in wireless networks. We provide both an exposition of common GA models and configuration and provide a broad-ranging survey of GA techniques in wireless networks. We also point out open research issues and define potential future work. While various surveys on GAs exist in the literature, our paper is the first paper, to the best of our knowledge, which focuses on their application in wireless networks.

  • 287.
    Chen, Yifan
    et al.
    Southern University of Science and Technology.
    Nakano, Tadashi
    Osaka University.
    Kosmas, Panagiotis
    King’s College London.
    Yuen, Chau
    Singapore University of Technology and Design.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Asvial, Muhamad
    University of Indonesia.
    Green Touchable Nanorobotic Sensor Networks2016In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 54, no 11, p. 136-142Article in journal (Refereed)
    Abstract [en]

    Recent advancements in biological nanomachineshave motivated the research on nanoroboticsensor networks (NSNs), where thenanorobots are green (i.e., biocompatible andbiodegradable) and touchable (i.e., externallycontrollable and continuously trackable). In theformer aspect, NSNs will dissolve in an aqueousenvironment after finishing designated tasksand are harmless to the environment. In the latteraspect, NSNs employ cross-scale interfacesto interconnect the in vivo environment and itsexternal environment. Specifically, the in-messagingand out-messaging interfaces for nanorobotsto interact with a macro-unit are defined.The propagation and transient characteristicsof nanorobots are described based on the existingexperimental results. Furthermore, planningof nanorobot paths is discussed by taking intoaccount the effectiveness of region-of-interestdetection and the period of surveillance. Finally,a case study on how NSNs may be applied tomicrowave breast cancer detection is presented

  • 288.
    Zhou, Biyu
    et al.
    Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Bejing.
    Zhang, Fa
    Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing.
    Wang, Lin
    SnT, University of Luxembourg.
    Hou, Chenying
    Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Bejing.
    Anta, Antonio Fernández
    IMDEA Networks Institute.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Wang, Youshi
    Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Bejing.
    Wu, Jie
    Department of Computer and Information Sciences, Temple University, Philadephia.
    Liu, Zhiyong
    State Key Laboratory for Computer Architecture, Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing.
    HDEER: A Distributed Routing Scheme for Energy-Efficient Networking2016In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 34, no 5, p. 1713-1727Article in journal (Refereed)
    Abstract [en]

    The proliferation of new online Internet services has substantially increased the energy consumption in wired networks, which has become a critical issue for Internet service providers. In this paper, we target the network-wide energy-saving problem by leveraging speed scaling as the energy-saving strategy. We propose a distributed routing scheme-HDEER-to improve network energy efficiency in a distributed manner without significantly compromising traffic delay. HDEER is a two-stage routing scheme where a simple distributed multipath finding algorithm is firstly performed to guarantee loop-free routing, and then a distributed routing algorithm is executed for energy-efficient routing in each node among the multiple loop-free paths. We conduct extensive experiments on the NS3 simulator and simulations with real network topologies in different scales under different traffic scenarios. Experiment results show that HDEER can reduce network energy consumption with a fair tradeoff between network energy consumption and traffic delay.

  • 289.
    Nugent, Chris
    et al.
    School of Computing and Mathematics, Ulster University.
    Synnott, Jonathan
    School of Computing and Mathematics, Ulster University .
    Celeste, Gabrielle
    Dipartimento dell’ingegneria dell’informazione, Universita Politecnica Delle Marche, Ancona, .
    Zhang, Shuai
    School of Computing and Mathematics, Ulster University.
    Espinella, Macarena
    Department of Computer Sciences, University of Jaen, .
    Calzada, Alberto
    School of Computing and Mathematics, Ulster University.
    Lundström, Jens
    School of Information Technology, Halmstad University, Halmstad, Sweden.
    Cleland, Ian
    School of Computing and Mathematics, Ulster University.
    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.
    Spinsante, Susanna
    Dipartimento dell’ingegneria dell’informazione, Universita Politecnica Delle Marche, Ancona.
    Ortiz Barrios, Miguel Angel
    Industrial Engineering Department, Universidad de La Costa CUC, Barranquilla, .
    Improving the Quality of User Generated Data Sets for Activity Recognition2016In: Ubiquitous Computing and Ambient Intelligence: 10th International Conference, UCAmI 2016, San Bartolomé de Tirajana, Gran Canaria, Spain, November 29 – December 2, 2016, Part II / [ed] Carmelo R. García, Pino Caballero-Gil, Mike Burmester, Alexis Quesada-Arencibia, Springer, 2016, Vol. 2, p. 104-110Conference paper (Refereed)
    Abstract [en]

    It is fully appreciated that progress in the development of data driven approaches to activity recognition are being hampered due to the lack of large scale, high quality, annotated data sets. In an effort to address this the Open Data Initiative (ODI) was conceived as a potential solution for the creation of shared resources for the collection and sharing of open data sets. As part of this process, an analysis was undertaken of datasets collected using a smart environment simulation tool. A noticeable difference was found in the first 1–2 cycles of users generating data. Further analysis demonstrated the effects that this had on the development of activity recognition models with a decrease of performance for both support vector machine and decision tree based classifiers. The outcome of the study has led to the production of a strategy to ensure an initial training phase is considered prior to full scale collection of the data.

  • 290.
    Amadeo, Marcia
    et al.
    Universita Mediterranea di Reggio Calabria.
    Campolo, Claudia
    Universita Mediterranea di Reggio Calabria. Telecommunications.
    Quevedo, Jose
    Universidade de Aveiro, Inst Telecomunicacoes.
    Corujo, Daniel
    Universidade de Aveiro, Inst Telecomunicacoes.
    Molinaro, Antonella
    Universita Mediterranea di Reggio Calabria. Telecommunications.
    Iera, Antonio
    Universita Mediterranea di Reggio Calabria.
    Aguiar, Rui L.
    Universidade de Aveiro, Inst Telecomunicacoes.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Information-Centric Networking for the Internet of Things: Challenges and Opportunities2016In: IEEE Network, ISSN 0890-8044, E-ISSN 1558-156X, Vol. 30, no 2, p. 92-100, article id 7437030Article in journal (Refereed)
    Abstract [en]

    In view of evolving the Internet infrastructure, ICN is promoting a communication model that is fundamentally different from the traditional IP address-centric model. The ICN approach consists of the retrieval of content by (unique) names, regardless of origin server location (i.e., IP address), application, and distribution channel, thus enabling in-network caching/replication and content-based security. The expected benefits in terms of improved data dissemination efficiency and robustness in challenging communication scenarios indicate the high potential of ICN as an innovative networking paradigm in the IoT domain. IoT is a challenging environment, mainly due to the high number of heterogeneous and potentially constrained networked devices, and unique and heavy traffic patterns. The application of ICN principles in such a context opens new opportunities, while requiring careful design choices. This article critically discusses potential ways toward this goal by surveying the current literature after presenting several possible motivations for the introduction of ICN in the context of IoT. Major challenges and opportunities are also highlighted, serving as guidelines for progress beyond the state of the art in this timely and increasingly relevant topic.

  • 291.
    Pavone, Mario
    et al.
    Department of Mathematics and Computer Science, University of Catania.
    Ramadan, Rabie A.
    Computer Engineering Department, Faculty of Engineering, Cairo University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Intelligent cloud computing2016In: Memetic Computing, ISSN 1865-9284, E-ISSN 1865-9292, Vol. 8, no 4, p. 253-254Article in journal (Refereed)
  • 292.
    Thombre, Sumeet
    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.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    Hossain, Mohammad Shahadat
    University of Chittagong, Bangladesh.
    IP based Wireless Sensor Networks: performance Analysis using Simulations and Experiments2016In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, ISSN 2093-5374, E-ISSN 2093-5382, Vol. 7, no 3, p. 53-76Article in journal (Refereed)
    Abstract [en]

    Wireless sensor networks are at the crux of the Internet of Things applications. At the current state, there exist several technologies competing against each other in the IoT space. These proprietary technologies and hardware pose a serious problem of interoperability, which is vital to unleash the vision of the Internet of Things. Moreover, the traditional approach towards wireless sensor networks was to be unlike the internet, primarily because of the power and memory constraints posed by the tiny sensor nodes. The IETF 6LoWPAN technology facilitates the usage of IPv6 communications in sensor networks, which helps solve the problem of interoperability, enabling low power, low cost micro-controllers to be globally connected to the internet. Another IETF technology, CoAP allows interactive communication over the internet for these resource constrained devices. Along with 802.15.4, 6LoWPAN and CoAP, an open, standardized WSN stack for resource constrained devices and environments becomes available. The Contiki OS, touted as the open source OS for IoT, provides low power IPv6 communications and supports the 6LoWPAN and CoAP protocols, along with mesh routing using RPL. Along with these, a CoAP framework, Californium (Cf) provides a scalable and RESTful API to handle IoT devices. These open tools and technologies are employed in this work to form an open, inter-operable, scalable, reliable and low power WSN stack. This stack is then simulated using Contiki's default network simulator Cooja, to conduct performance analysis in varying conditions such as noise, topology, traffic etc. Finally, as a proof of concept and a validation of the simulated stack, physical deployment is carried out, using a Raspberry Pi as a border router, which connects the wireless sensor network to the global internet along with the T-mote sky sensor motes. Therefore, this work develops and demonstrates an open, interoperable, reliable, scalable, low power, low cost WSN stack, both in terms of simulations and physical deployments, and carries out performance evaluation of the stack in terms of throughput, latency and packet loss.

  • 293. Ngo, Khoi
    et al.
    Saguna, Saguna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mitra, Karan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Åhlund, Christer
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    IReHMo: An efficient IoT-Based Remote health Monitoring System for Smart Regions2016In: 2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015: Boston, United States, 13 - 17 October 2015, Piscataway, NJ: IEEE Communications Society, 2016, p. 563-568, article id 7454565Conference paper (Refereed)
    Abstract [en]

    The ageing population worldwide is constantly rising, both in urban and regional areas. There is a need for IoT-based remote health monitoring systems that take care of the health of elderly people without compromising their convenience and preference of staying at home. However, such systems may generate large amounts of data. The key research challenge addressed in this paper is to efficiently transmit healthcare data within the limit of the existing network infrastructure, especially in remote areas. In this paper, we identified the key network requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, we studied the network communication protocols such as CoAP, MQTT and HTTP to understand the needs of such a system, in particular the bandwidth requirements and the volume of generated data. Subsequently, we have proposed IReHMo - an IoT-based remote health monitoring architecture that efficiently delivers healthcare data to the servers. The CoAP-based IReHMo implementation helps to reduce up to 90% volume of generated data for a single sensor event and up to 56% required bandwidth for a healthcare scenario. Finally, we conducted a scalability analysis to determine the feasibility of deploying IReHMo in large numbers in regions of north Sweden.

  • 294.
    Dadhich, Siddharth
    et al.
    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.
    Key challenges in automation of earth-moving machines2016In: Automation in Construction, ISSN 0926-5805, E-ISSN 1872-7891, Vol. 68, p. 212-222Article in journal (Refereed)
    Abstract [en]

    A wheel loader is an earth-moving machine used in construction sites, gravel pits and mining to move blasted rock, soil and gravel. In the presence of a nearby dump truck, the wheel loader is said to be operating in a short loading cycle. This paper concerns the moving of material (soil, gravel and fragmented rock) by a wheel loader in a short loading cycle with more emphasis on the loading step. Due to the complexity of bucket-environment interactions, even three decades of research efforts towards automation of the bucket loading operation have not yet resulted in any fully autonomous system. This paper highlights the key challenges in automation and tele-remote operation of earth-moving machines and provides a survey of different areas of research within the scope of the earth-moving operation. The survey of publications presented in this paper is conducted with an aim to highlight the previous and ongoing research work in this field with an effort to strike a balance between recent and older publications. Another goal of the survey is to identify the research areas in which knowledge essential to automate the earth moving process is lagging behind. The paper concludes by identifying the knowledge gaps to give direction to future research in this field.

  • 295.
    Dinh, Thanh
    et al.
    School of Electronic Engineering, Soongsil University.
    Kim, Younghan
    School of Electronic Engineering, Soongsil University.
    Gu, Tao
    School of Computer Science, RMIT University, Melbourne.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    L-MAC: A Wake-up Time Self-learning MAC Protocol for Wireless Sensor Networks2016In: Computer Networks, ISSN 1389-1286, E-ISSN 1872-7069, Vol. 105, p. 33-46Article in journal (Refereed)
    Abstract [en]

    This paper analyzes the trade-off issue between energy efficiency and packet delivery latency among existing duty-cycling MAC protocols in wireless sensor networks for low data-rate periodic-reporting applications. We then propose a novel and practical wake-up time self-Learning MAC (L-MAC) protocol in which the key idea is to reuse beacon messages of receiver-initiated MAC protocols to enable nodes to coordinate their wakeup time with their parent nodes without incurring extra communication overhead. Based on the self-learning mechanism we propose, L-MAC builds an on-demand staggered scheduler to allow any node to forward packets continuously to the sink node. We present an analytical model, and conduct extensive simulations and experiments on Telosb sensors to show that L-MAC achieves significant higher energy efficiency compared to state-of-the-art asynchronous MAC protocols and a similar result of latency compared to synchronous MAC protocols. In particular, under QoS requirements with an upper bound value for one-hop packet delivery latency within 1 s and a lower bound value for packet delivery ratio within 95%, results show that the duty cycle of L-MAC is improved by more than 3.8 times and the end-to-end packet delivery latency of L-MAC is reduced by more than 7 times compared to those of AS-MAC and other state-of-the-art MAC protocols, respectively, in case of the packet generation interval of 1 minute. L-MAC hence achieves high performance in both energy efficiency and packet delivery latency.

  • 296.
    Dadhich, Siddharth
    et al.
    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.
    Sandin, Fredrik
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Andersson, Ulf
    Machine Learning approach to Automatic Bucket Loading2016In: 24th Mediterranean Conference on Control and Automation (MED): June 21-24, Athens, Greece, 2016, Piscataway, NJ: IEEE Communications Society, 2016, p. 1260-1265, article id 7535925Conference paper (Refereed)
    Abstract [en]

    The automation of bucket loading for repetitive tasks of earth-moving operations is desired in several applications at mining sites, quarries and construction sites where larger amounts of gravel and fragmented rock are to be moved. In load and carry cycles the average bucket weight is the dominating performance parameter, while fuel efficiency and loading time also come into play with short loading cycles. This paper presents the analysis of data recorded during loading of different types of gravel piles with a Volvo L110G wheel loader. Regression models of lift and tilt actions are fitted to the behavior of an expert driver for a gravel pile. We present linear regression models for lift and tilt action that explain most of the variance in the recorded data and outline a learning approach for solving the automatic bucket loading problem. A general solution should provide good performance in terms of average bucket weight, cycle time of loading and fuel efficiency for different types of material and pile geometries. We propose that a reinforcement learning approach can be used to further refine models fitted to the behavior of expert drivers, and we briefly discuss the scooping problem in terms of a Markov decision process and possible value functions and policy iteration schemes.

  • 297.
    Wan, Jiafu
    et al.
    School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou.
    Liu, Jianqi
    School of Information Engineering, Guangdong Mechanical & Electrical College, Guangzhou.
    Shao, Zehio
    School of Information Science and Technology, Chengdu University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Imran, Muhammad Al
    College of Computer and Information Sciences, Almuzahmiyah, King Saud University.
    Zhou, Keliang
    School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou.
    Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles2016In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 16, no 1, article id 88Article in journal (Refereed)
    Abstract [en]

    The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the vehicle routing problem from a calculation based on static data towards real-time traffic prediction. In this paper, we first address the taxonomy of cloud-assisted IoV from the viewpoint of the service relationship between cloud computing and IoV. Then, we review the traditional traffic prediction approached used by both Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications. On this basis, we propose a mobile crowd sensing technology to support the creation of dynamic route choices for drivers wishing to avoid congestion. Experiments were carried out to verify the proposed approaches. Finally, we discuss the outlook of reliable traffic prediction.

  • 298.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Tang, Yu
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Yao, Yuanzhe
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
    Neural Networks for Computer-Aided Diagnosis in Medicine: a review2016In: Neurocomputing, ISSN 0925-2312, E-ISSN 1872-8286, Vol. 216, p. 700-708Article in journal (Refereed)
    Abstract [en]

    This survey makes an overview of the most recent applications on the neural networks for the computer-aided medical diagnosis (CAMD) over the past decade. CAMD can facilitate the automation of decision making, extraction and visualization of complex characteristics for clinical diagnosis purposes. Over the past decade, neural networks have attained considerable research interest and are widely employed to complex CAMD systems in diverse clinical application domains, such as detecting diseases, classification of diseases, testing the compatibility of new drugs, etc. Overall, this paper reviews the state-of-the-art of neural networks for CAMD. It helps the readers understand the topic of neural networks for CAMD by summarizing the findings addressed in recent academic papers as well as presenting a few open issues of developing the research on this topic.

  • 299.
    Yang, Helin
    et al.
    Chongqing Key Laboratory of Mobile Communications Technology and Institute of Personal Communication, Chongqing University of Posts & Telecommunications, Chongqing.
    Xie, Xianzhong
    Chongqing Key Laboratory of Mobile Communications Technology and Institute of Personal Communication, Chongqing University of Posts & Telecommunications, Chongqing.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Noncooperative and Cooperative Optimization of Electric Vehicle Charging Under Demand Uncertainty: A Robust Stackelberg Game2016In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 65, no 3, p. 1043-1058Article in journal (Refereed)
    Abstract [en]

    This paper studies the problem of energy charging using a robust Stackelberg game approach in a power system composed of an aggregator and multiple electric vehicles (EVs) in the presence of demand uncertainty, where the aggregator and EVs are considered to be a leader and multiple followers, respectively. We propose two different robust approaches under demand uncertainty: a noncooperative optimization and a cooperative design. In the robust noncooperative approach, we formulate the energy charging problem as a competitive game among self-interested EVs, where each EV chooses its own demand strategy to maximize its own benefit selfishly. In the robust cooperative model, we present an optimal distributed energy scheduling algorithm that maximizes the sum benefit of the connected EVs. We theoretically prove the existence and uniqueness of robust Stackelberg equilibrium for the two approaches and develop distributed algorithms to converge to the global optimal solution that are robust against the demand uncertainty. Moreover, we extend the two robust models to a time-varying power system to handle the slowly varying environments. Simulation results show the effectiveness of the robust solutions in uncertain environments.

  • 300.
    Gong, Xueyuan
    et al.
    Department of Computer and Information Science, University of Macau.
    Fong, Simon
    Department of Computer and Information Science, University of Macau.
    Si, Yainwhar
    Department of Computer and Information Science, University of Macau.
    Biuk-Agha, Robert P.
    School of Computer Science and Engineering, University of New South Wales, Sydney.
    Wong, Raymond K.
    School of Computer Science and Engineering, University of New South Wales, Sydney.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Normalized Cross-Match: Pattern Discovery Algorithm from Biofeedback Signals2016In: Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2016 Workshops, BDM, MLSDA, PACC, WDMBF, Auckland, New Zealand, April 19, 2016, Revised Selected Papers, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 169-180Conference paper (Refereed)
    Abstract [en]

    Biofeedback signals are important elements in critical care applications, such as monitoring ECG data of a patient, discovering patterns from large amount of ECG data sets, detecting outliers from ECG data, etc. Because the signal data update continuously and the sampling rates may be different, time-series data stream is harder to be dealt with compared to traditional historical time-series data. For the pattern discovery problem on time-series streams, Toyoda proposed the CrossMatch (CM) approach to discover the patterns between two time-series data streams (sequences), which requires only O(n) time per data update, where n is the length of one sequence. CM, however, does not support normalization, which is required for some kinds of sequences (e.g. EEG data, ECG data). Therefore, we propose a normalized-CrossMatch approach (NCM) that extends CM to enforce normalization while maintaining the same performance capabilities

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