HUANG Jiwei, CHEN Guo, CHENG Bo, “A Stochastic Approach of Dependency Evaluation for IoT Devices,” Chinese Journal of Electronics, vol. 25, no. 2, pp. 209-214, 2016, doi: 10.1049/cje.2016.03.003
Citation: HUANG Jiwei, CHEN Guo, CHENG Bo, “A Stochastic Approach of Dependency Evaluation for IoT Devices,” Chinese Journal of Electronics, vol. 25, no. 2, pp. 209-214, 2016, doi: 10.1049/cje.2016.03.003

A Stochastic Approach of Dependency Evaluation for IoT Devices

doi: 10.1049/cje.2016.03.003
Funds:  This work is supported by the National Natural Science Foundation of China (No.61502043 and No.61132001), National High-tech R&D Program of China (863 Program) (No.2013AA102301), Beijing Natural Science Foundation (No.4162042), BeiJing Talents Fund (No.2015000020124G082), and the Fundamental Research Funds for the Central Universities (No.2015RC22).
  • Received Date: 2015-08-31
  • Rev Recd Date: 2015-10-28
  • Publish Date: 2016-03-10
  • Internet of things (IoT) is an emerging technique that offers advanced connectivity of devices, systems, services, and human beings. With the rapid development of hardware and network technologies, the IoT can refer to a wide variety and large number of devices, resulting in complex relationships among IoT devices. The dependencies among IoT devices, which reflect their relationships, are with reference value for the design, development and management of IoT devices. This paper proposes a stochastic model based approach for evaluating the dependencies of IoT devices. A random walk model is proposed to describe the relationships of IoT devices, and its corresponding Markov chain is obtained for dependency analysis. A framework as well as schemes and algorithms for dependency evaluation in real-world IoT are designed based on traffic measurement. Simulation experiments based on real-life data extracted from smart home environments are conducted to illustrate the efficacy of the approach.
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  • J. Höller, V. Tsiatsis, C. Mulligan, et al., From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence, Elsevier, 2014.
    M. Davoudpour, A. Sadeghian, and H. Rahnama, "CANthings (Context aware network for the design of connected things) service modeling based on Timed CPN", IEEE International Conference on Semantic Computing (ICSC 2015), pp.127-130, 2015.
    X. Li and Y. Sun, "A service mining scheme based on semantic for Internet of Things", Chinese Journal of Electronics, Vol.23, No.2, pp.236-242, 2014.
    J. Byun, S.H. Kim and D. Kim, "Lilliput: Ontology-based platform for IoT social networks", 2014 IEEE International Conference on Services Computing (SCC 2014), pp.139-146, 2014.
    J.-H. Choi, J.-H. Cho, H.-G. Ko and I.-Y. Ko, "Distributed coordination of IoT-based services by using a graph coloring algorithm", IEEE 37th Annual Computer Software and Applications Conference (COMPSAC 2013), pp.399-404, 2013.
    C. Liu, J. Cao and J. Wang, "A parallel approach for service composition with complex structures in pervasive environments", 2015 IEEE 22nd International Conference on Web Services (ICWS 2015), pp.551-558, 2015.
    L. Atzori, A. Iera and G. Morabito, "SIoT: Giving a social structure to the Internet of Things", IEEE Communications Letters, Vol.15, No.11, pp.1193-1195, 2011.
    X. Xu, S. Huang, Y. Chen, et al., "TSAaaS: Time series analytics as a service on IoT", 2014 IEEE International Conference on Web Services (ICWS 2014), pp.249-256, 2014.
    R. Albert and A. Barabasi, "Statistical mechanics of complex networks", Reviews of Modern Physics, Vol.74, No.1, pp.47-97, 2002.
    S. Thurner and C. Biely, "Two statistical mechanics aspects of complex networks", Physica A: Statistical Mechanics and Its Applications, Vol.372, No.2, pp.346-353, 2006.
    T. Wang, H. Krim and Y. Viniotis, "A generalized Markov graph model: Application to social network analysis", IEEE Journal of Selected Topics in Signal Processing, Vol.7, No.2, pp.318-332, 2013.
    T. Alinaghi, C. Ghoroghi, A. Saborui and R. Basseda, "A framework for dependency evaluation of the agent oriented methodologies work flows", Third IEEE International Symposium on Theoretical Aspects of Software Engineering (TASE 2009), pp.289-290, 2009.
    A. Callado, C. Kamienski, G. Szabo, et al., "A survey on internet traffic identification", IEEE Communications Surveys Tutorials, Vol.11, No.3, pp.37-52, 2009.
    C.D. Meyer, Matrix Analysis and Applied Linear Algebra, SIAM, Philadelphia, PA, 2000.
    I.S. Dhillon, B.N. Parlett and C. Vömel, "The design and implementation of the MRRR algorithm", ACM Transactions on Mathematical Software, Vol.32, No.4, pp.533-560, 2006.
    E.M. Tapia, et al., "Activity recognition in the home using simple and ubiquitous sensors", Pervasive Computing, Lecture Notes in Computer Science, A. Ferscha and F. Mattern, Eds. Springer Berlin Heidelberg, Vol.3001, pp.158-175, 2004.
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