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Probabilistic Model for M2M in IoT networking and communication

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Abstract

In this paper, a probabilistic model for M2M in IoT networking and communication mode is presented with mobile and dynamic machines in the network. The scenario is considered stochastic and thus probability distribution describing the times between successive machines entry in to the network is predicted by means of a graph. A graph based model is also presented to find the shortest path and lowest cost between machines. For large scale network, parallel M2M establish connection inside a network and are partitioned and dynamically refigured such as IoT. Simulation were performed for multiple M2M array for different state, timing and power consumption along with the scheduling scheme are considered.

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References

  1. Anand, P., Jhing-Fa, W., Jia-Ching, W., An-chao, T., & Jang-Ting, C. (2006). Projection based adaptive window size selection for efficient motion estimation. IEICE Transaction on Fundamentals of Electronics, Communication and Computer Science, 89(11), 2970–2976.

    Google Scholar 

  2. Blum, J. J., Eskandaran, A., & Hoffman, L. J. (2004). Challenges of inter-vehicle ad hoc network. IEEE Transaction on Intelligent Transportation Systems, 5(4), 347–351.

    Article  Google Scholar 

  3. Broto, L., Hagimont, D., Stolf, P., de Palma, N., & Temate, S. (2008). Autonomic management policy specification in tune. In ACM Symposium on Applied Computing, Fortaleza, Ceara, Brazil (pp. 1658–1663).

  4. Chen, J.-T., Wang, J.-C., Wang, J.-F., Tsai, A.-C., & Paul, A. (2006). A novel dominant edge strength algorithm for intra prediction in H.264/AVC encoder. In Proceeding Picture Coding Symposium (PCS), China, Beijing.

  5. Eichler, C., Gharbi, G., Guermouche, N., & Monteil, T. (2013). Graph-Based formalism for machine-to-machine self-managed communications. EPURE les Publications de la recherché de l’ Universitie de Toulouse.

  6. ETSI M2M functional architecture technical. Report http://www.etsi.org/deliver/etsi_ts/102600_102699/102690/01.01.01_60/ts_102690v010101p.pdf

  7. Ferreira, A. (2004). Building a reference combinatorial model for MANETs. IEEE Network Magazine, 18(5), 24–29.

    Article  Google Scholar 

  8. Eiza, M. H., & Ni, Q. (2013). An evolving graph-based reliable routing scheme for VANETs. IEEE Transaction on Vehicular Technology, 62(4), 1493–1504.

    Article  Google Scholar 

  9. Kand’e, M. M., & Strohmeier, A. (2000) Towards a uml profile for software architecture descriptions. In Proceedings of the 3rd international conference on The unified modeling language: advancing the standard, UML’00, Springer-Verlag, Berlin, Heidelberg (pp. 513–527). URL http://dl.acm.org/citation.cfm?id=1765175.1765230

  10. Le, V. D., Hans, S., & Paul, H. (2012). Unified routing for data dissemination in smart city networks. 3rd International Conference on the Internet of Things (IoT), (pp. 24–26).

  11. Medvidovic, N., Rosenblum, D. S., Redmiles, D. F., & Robbins, J. E. (2002). Modeling software architectures in the unified modelinglanguage. ACM Transactions on Software Engineering and Methodology, 11, 2–57. doi:10.1145/504087.504088.

    Article  Google Scholar 

  12. Pandey, S., Mup, M.-S., C, M.-H., & Hong, J. W. (2011). Towards management of machine to machine networks. Network operation and management symposium (APNOMS) 13th Asia-Pacific (pp. 1–7)

  13. Paul, A. (2003) TAA Victoire AE Jeyakumar. 2003. Particle swarm approach for retiming in VLSI. In Proceedings of the 46th Midwest Symposium on Circuits and Systems (pp. 27–30) Cairo, Egypt.

  14. Paul, A. (2013). Graph based M2M optimization in an IoTEnviroment. Proceedings of Research in Adaptive and Convergent Systems, ACM RACS.

  15. Paul, A., & Chin, Y. H. (2013). Graph based orange computing architecture for Cyber-physical being, ASPSIPA ASC 2013, October 29–November 1, 2013.

  16. Paul, A., Jiang, Y. C., & Jeong, J. (2010). Parallel reconfigurable computing and its application to hidden markov model. IET International conference on Frontier ComputingAugust 4–6 Taichung, Taiwan (pp. 82–91).

  17. Paul, A., Jiang, Y. C., Wang, J. F., & Yang, J. F. (2012). Parallel reconfigurable computing-based mapping algorithm for motion estimation in advance video coding. ACM Transaction on Embedded Computing Systems 11(Issue S2):40.

  18. Paul, A., Rho, S., & Bharanitharan, K. (2013). Interactive scheduling for mobile multimedia services in M2M environment. Multimedia Tools and Application. Published online May \(29{\rm th}\), 2013.

  19. Paul, A., Wang, J.F., & Wang, J.F. (2008). Adaptive search range selection for scalable video coding extension of H.264/AVC. In Proceeding of TENCON 2008 IEEE Region 10 conference in Hyderabad, India.

  20. Paul, A., & Wang, J.-F. (2010). Computation aware scheme for visual signal processing. Journal of Software, 5(6), 573–578.

    Article  Google Scholar 

  21. Paul, A. (2013). Dynamic power management for ubiquitous network devices. Advance Science Letters, 19(7), 2046–2049.

    Article  Google Scholar 

  22. Paul, A. (2013). High performance adaptive deblocking filter for H.264/AVC. IETE Technical Review, 30(2), 157–161.

    Article  Google Scholar 

  23. Selonen, P., & Xu, J. (2003). Validating uml models against architectural profiles. SIGSOFT Software Engineering Notes, 28, 58–67. doi:10.1145/949952.940081.

    Article  Google Scholar 

  24. Thilagavathe, V., & Duraiswamy, K. (2011). Prediction based reliability estimation in MANETs with weibull nodes. European Journal of Scientific Research, 64(2), 325–329.

    Google Scholar 

  25. Tsai, A.-C., Paul, A., Wang, J.-C., & Wang, J.-F. (2006). Programmable logic array design for H.264 context-based adaptive variable length coding. In Proceeding of TENCON 2006, IEEE Region 10 conference in Hongkong (pp. 14–17).

  26. Tsai, A. C., Paul, A, Wang, J. C., & Wang, J. F. (2007). Efficient intra prediction in H.264 based on intensity gradient approach. Proceedings of ISCAS 2007. International Symposium on Circuits and Systems (pp. 3952–3955).

  27. Wan, J., Zhang, D., Zhao, S., Shengjie, Y., Laurence, T., & Lloret, J. (2014). Context-aware vehicular cyber-physical systems with cloud support: Architecture, challenges and solutions. IEEE Communication Magazine, 52(8), 106–113.

    Article  Google Scholar 

  28. Wu, J., Paul, A., Xing, Y., Fang, Y., Jeong, J., Jiao, L., et al. (2010). Morphological dilation image coding with context weights prediction. Signal Processing Image Communication, 25(10), 717–728. Elsevier publication.

    Article  Google Scholar 

  29. Zhang, D., Yang, L. T., Chen, M., Zhao, S., Guo, M., & Zhang, Yin A real-time locating system using active RFID for internet of things. IEEE Systems Journal. doi:10.1109/JSYST.2014.2346625.

  30. Zhang, D., Zou, Q., & Xiong, H. (2013) CRUC: Cold-start recommendation using collaborative filtering in internet of things, CORR abs/1306.0165.

  31. Zhang, D., Zhang, D., Xiong, H., Hsu, C.-H., & Vasilakos, A. V. (2014). BASA: Building mobile ad-hoc social networks on top of android. IEEE Networks, 28(1), 4–9.

    Article  Google Scholar 

  32. Zhang, Y., Chen, M., Mao, S., Hu, L., & Leung, V. (2014). CAP: Crowd activity prediction based on big data analysis. IEEE Network, 28(4), 52–57.

    Article  Google Scholar 

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Acknowledgments

This research is supported by Kyungpook National University and this research was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A1A2061978).

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Correspondence to Seungmin Rho.

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Paul, A., Rho, S. Probabilistic Model for M2M in IoT networking and communication. Telecommun Syst 62, 59–66 (2016). https://doi.org/10.1007/s11235-015-9982-z

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