SMIER: An SVM and MCDA Based, Intelligent Approach for Enhanced Reliability in Wireless Sensor Networks

Mohammad Samadi Gharajeh*, Maryam Askari Zivayeki**, Sareh Askari***
* Young Researchers and Elite Club, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
** Department of Computer Engineering, Bostanabad Branch, Islamic Azad University, Bostanabad, Iran.
*** Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
Periodicity:May - July'2017
DOI : https://doi.org/10.26634/jcs.6.3.13611

Abstract

Reliability is one of the big challenges in Wireless Sensor Networks (WSNs). It can be improved by using some of the intelligent and knowledge-based mechanisms, such as Support Vector Machine (SVM) and Multiple Criteria Decision Analysis (MCDA). This paper proposes an SVM and MCDA based, intelligent approach for enhanced reliability in WSNs, called SMIER. It is considered for a cluster-based sensor network in a way that every Cluster-Head (CH) selects one of its Non Cluster-Head (NCH) nodes as a backup node in a period of time. Initially, the suggested SVM algorithm determines failure probability of each NCH node based on number of events and average distance to events. Afterward, the suggested MCDA controller calculates success rate of the NCH node by using three parameters, including remaining energy, distance, and failure probability. Simulation results show that the proposed approach surpasses some of the existing works in terms of packet delivery ratio, number of alive nodes, and average remaining energy.

Keywords

Wireless Sensor Networks (WSNs), Reliability, Intelligent Mechanism, Support Vector Machine (SVM), Multiple Criteria Decision Analysis (MCDA)

How to Cite this Article?

Gharajeh, M. S., Zivayeki, M. A., Askari, S. (2017). SMIER: An SVM and MCDA Based, Intelligent Approach For Enhanced Reliability In Wireless Sensor Networks. i-manager’s Journal on Communication Engineering and Systems, 6(3), 1-8. https://doi.org/10.26634/jcs.6.3.13611

References

[1]. Akyildiz, I. F., & Vuran, M. C. (2010). Wireless sensor networks (Vol. 4). John Wiley & Sons.
[2].Alfadhly, A., Baroudi, U., & Younis, M. (2011, July). Least distance movement recovery approach for large scale wireless sensor and actor networks. In Wireless Communications and Mobile Computing Conference (IWCMC), 2011 7th International (pp. 2058-2063). IEEE.
[3].Ben-Hur, A., & Weston, J. (2010). A user’s guide to support vector machines. Data mining techniques for the life sciences, 223-239.
[4].Chen, X., Kim, Y. A., Wang, B., Wei, W., Shi, Z. J., & Song, Y. (2012). Fault-tolerant monitor placement for out-of-band wireless sensor network monitoring. Ad Hoc Networks, 10(1), 62-74.
[5].Cheng, P., Qi, Y., Xin, K., Chen, J., & Xie, L. (2016). Energy-efficient data forwarding for state estimation in multi-hop wireless sensor networks. IEEE Transactions on Automatic Control, 61(5), 1322-1327.
[6].Cheraghlou, M. N., Babaie, S., & Samadi, M. (2012). LRC: Novel fault tolerant local re-clustering protocol for wireless sensor network. Journal of Computing, 4(8), 99-104.
[7].Dong, M., Ota, K., Liu, A., & Guo, M. (2016). Joint optimization of lifetime and transport delay under reliability constraint wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 27(1), 225-236.
[8].Fadel, E., Gungor, V. C., Nassef, L., Akkari, N., Malik, M. A., Almasri, S., & Akyildiz, I. F. (2015). A survey on wireless sensor networks for smart grid. Computer Communications, 71, 22-33.
[9].Geeta, D. D., Nalini, N., & Biradar, R. C. (2013). Fault tolerance in wireless sensor network using hand-off and dynamic power adjustment approach. Journal of Network and Computer Applications, 36(4), 1174-1185.
[10].Gharajeh, M. S. (2016). Avoidance of the energy hole in wireless sensor networks using a layered-based routing tree. International Journal of Systems, Control and Communications, 7(2), 116-131.
[11].Gharajeh, M. S. (2016). SFRRP: 3D Fuzzy Routing for Wireless Sensor Networks”, in: Advances in Control and Mechatronic Systems. Volume: I. United Scholars Publications, pp. 87-108.
[12].Gharajeh, M. S., & Khanmohammadi, S. (2016). DFRTP: Dynamic 3D Fuzzy Routing Based on Traffic Probability in Wireless Sensor Networks. IET Wireless Sensor Systems, 6(6), 211-219.
[13].Gharajeh, M. S., Hassanzadeh, R., (2017). Improving the Fault Tolerance of Wireless Sensor Networks by a Weighted Criteria Matrix. The Mediterranean Journal of Electronics and Communications, Vol. 13, No. 1, pp. 1-6.
[14].Gharajeh, Mohammad Samadi. "Determining the State of the Sensor Nodes Based on Fuzzy Theory in WSNs." International Journal of Computers Communications & Control 9, no. 4 (2014): 419-429.
[15].Guo, D., & Xu, L. (2013). Leach clustering routing protocol for WSN. In Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012 (pp. 153-160). Springer, London.
[16].Guo, S., He, L., Gu, Y., Jiang, B., & He, T. (2014). Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links. IEEE Transactions on Computers, 63(11), 2787-2802.
[17].Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000, January). Energy-efficient communication protocol for wireless microsensor networks. In System sciences, 2000. Proceedings of the 33rd annual Hawaii international conference on (pp. 10-pp). IEEE.
[18].Huang, P., Xiao, L., Soltani, S., Mutka, M. W., & Xi, N. (2013). The evolution of MAC protocols in wireless sensor networks: A survey. IEEE communications surveys & tutorials, 15(1), 101-120.
[19].Kumar, N., & Kaur, J. (2011, September). Improved leach protocol for wireless sensor networks. In Wireless Communications, Networking and Mobile Computing (WiCOM), 2011 7th International Conference on (pp. 1-5). IEEE.
[20].Mahmood, M. A., Seah, W. K., & Welch, I. (2015). Reliability in wireless sensor networks: A survey and challenges ahead. Computer Networks, 79, 166-187.
[21].Munda, G. (2016). Multiple Criteria Decision Analysis and Sustainable Development. In Multiple Criteria Decision Analysis (pp. 1235-1267). Springer New York.
[22].Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: a survey on recent developments and potential synergies. The Journal of supercomputing, 68(1), 1-48.
[23].Samadi Gharajeh, M., & Alizadeh, M. (2016). OPCA: Optimized Prioritized Congestion Avoidance and Control for Wireless Body Sensor Networks. International Journal of Sensors Wireless Communications and Control, 6(2), 118-128.
[24].Samadi Gharajeh, M., & Khanmohammadi, S. (2013). Static three-dimensional fuzzy routing based on the receiving probability in wireless sensor networks. Computers, 2(4), 152-175.
[25].Tyagi, S., & Kumar, N. (2013). A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks. Journal of Network and Computer Applications, 36(2), 623-645.

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