Fuzzy Based Particle Swarm Optimization Routing Technique for Load Balancing in Wireless Sensor Networks
Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to reduce the energy consumption using particle swarm optimization algorithm, the cluster head sends its information along data packets to the heads with link. The simulation results show that the presented routing protocol can perform load balancing effectively and reduce the energy consumption of cluster heads.
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 Blaho, M., Urban, M., Fodrek, P., &Foltin, M. (2012). Wireless network effect on PI and type-2 fuzzy logic controller. International Journal of Communications, 6(1), 18–25.
 Harold Robinson, Y., &Rajaram, M. (2015). “Trustworthy link failure recovery algorithm for highly dynamic mobile adhoc networks”, World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, vol.9, no.2, 233–236.
 Li, C., Ye, M., Chen, G., & Wu, J. (2005). An energy-efficient unequal clustering mechanism for wireless sensor networks. In IEEE international conference on mobile adhoc and sensor systems conference (MAHSS) (pp. 597–604).
 Bagci, H., &Yazici, A. (2010). An energy aware fuzzy unequal clustering algorithm for wireless sensor networks. In Proceeding of IEEE international conference on fuzzy systems (FUZZ) (pp. 1–8).
 Lindsey, S., & Raghavendra, C.S. (2002). PEGASIS: Power-efficient gathering using in sensor information systems. In Proceeding of IEEE aerospace conference (pp. 1125–1130). Big Sky: Montana.
 Handy, M., Haase, M., & Timmermann, D. (2002). Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In The 4th international workshop on mobile and wireless communications network (pp. 368–372).
 Wang, L. X. (1996). A course in fuzzy systems and control. Englewood Cliffs: Prentice-Hall Inc.
 Harold Robinson, Y., &Rajaram, M. (2016), “A memory aided broadcast mechanism with fuzzy classification on a device-to-device mobile Ad Hoc network”, Wireless Personal Communications, 1–23, doi:10.1007/s11277-016-3213-0.
 Colorni, A., Dorigo, M. & Maniezzo, V. (1991). Distributed optimization by ant colonies. In Proceedings of ECAL91-European conference on artificial life (pp. 134–142). Paris, France: Elsevier.
 Zhang, F., Zhang, Q. Y., & Sun, Z. M. (2013). ICT2TSK: An improved clustering algorithm for WSN using a type-2 Takagi–Sugeno–Kang fuzzy logic system. In 2013 IEEE symposium on wireless technology and applications (ISWTA), September 22–25 (pp. 153–158). Malaysia: Kuching.
 Harold Robinson, Y., &Rajaram, M. (2015), “Energy-aware multipath routing scheme based on particle swarm optimization in mobile ad hoc networks”, The Scientific World Journal, 1–9. doi:10.1155/2015/284276.
 Harold Robinson, Y., &Rajaram, M. (2015), “Establishing pairwise keys using key Predistribution schemes for sensor networks”, World Academy of Science, Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering, 9(2), 608–612.
 Ayyasamy, A., and K. Venkatachalapathy. "Context aware adaptive fuzzy based QoS routing scheme for streaming services over MANETs." Wireless Networks 21.2 (2015): 421-430.
 Ayyasamy, A., and K. Venkatachalapathy. "Increased Throughput for Load based Channel Aware Routing in MANETs with Reusable Paths." International Journal of Computer Applications 40.2 (2012): 20-23.
 Balaji, S., Harold Robinson, Y. and Rajaram, M. (2016) SCSBE: Secured Cluster and Sleep Based Energy-Efficient Sensory Data Collection with Mobile Sinks. Circuits and Systems, 7, 1992-2001. http://dx.doi.org/10.4236/cs.2016.78173
 Estrin, D., Govindan, R., Heidemann, J. and Kumar, S. (1999) Next Century Challenges: Scalable Coordination in Sensor Networks. Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, 263-270.
 Kang, S.H. and Nguyen, T. (2012) Distance Based Thresholds for Cluster Head Selection in Wireless Sensor Networks. IEEE Communications Letters, 16, 1396-1399.
 Robinson, Y.H., Balaji, S. and Rajaram, M. (2016) ECBK: Enhanced Cluster Based Key Management Scheme for Achieving Quality of Service. Circuits and Systems, 7, 2014-2024. http://dx.doi.org/10.4236/cs.2016.78175.
 Rijin, I.K., Sakthivel, N.K. and Subasree, S. (2013) Development of an Enhanced Efficient Secured Multi-Hop Routing Technique for Wireless Sensor Networks. International Journal of Innovative Research in Computer and Communication Engineering, 1, 506-512.
 Neto, A. (2013) A Cluster-Based Approach to Provide Energy-Efficient in WSN. International Journal of Computer Science and Network Security, 13, 55-62.
 Harold Robinson, Y., Rajaram, M., Golden Julie, E. and Balaji, S. (2016) Dominating Set Algorithm and Trust Evaluation Scheme for Secured Cluster Formation and Data Transferring. World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, Vol. 10, No. 2, pp. 388-393.
 Hwang, D., & Kim, D. (2008). DFR: Directional flooding-based routing protocol for underwater sensor networks. In OCEANS 2008. IEEE
 Yan, H., Shi, Z. J., & Cui, J. H. (2008). DBR: depth-based routing for underwater sensor networks. In International conference on research in networking (pp. 72–86). Springer Berlin Heidelberg.
 Harold Robinson, Y., Rajaram, M., Golden Julie, E. and Balaji, S. (2016), “Tree Based Data Fusion Clustering Routing Algorithm for Illimitable Network Administration in Wireless Sensor Network”, World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:10, No:6, pp. 1123 – 1130.
 Yang, X.-S., & He, X. (2013). Bat algorithm: Literature review and applications. International Journal of Bio-Inspired Computation, 5(3), 141–149.
 Lee, U., et al. (2010). Pressure Routing for underwater sensor networks. In INFOCOM.
 Harold Robinson, Y., Rajaram, M., Golden Julie, E. and Balaji, S. (2016), “TBOR: Tree Based Opportunistic Routing for Mobile Ad Hoc Networks”, World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:10, No:6, pp. 1115 – 1122.
 Moradpoor, N., Parr, G., McClean, S., Scotney, B., & Owusu, G. (BT Laboratories). Interleaved polling with adaptive cycle time (IPACT) Implementations using OPNET MODELER. India-UK Advanced Technology Centre of excellence in next generation networks, systems and services.
 Singh, S., & Agrawal, S. (2014). VANET routing protocols: Issues and challenges. In 2014 Recent Advances, Engineering and Computational Sciences (RAECS) (pp. 1–5). IEEE
 Ramalakshmi, S., & Robinson, Y. H. (2014). “ATMPH: Attaining optimal throughput capacity of MANET with power control in heterogeneous network”, Programmable Device Circuits and Systems, 6(4), 111–115.
 Rappaport, T. S. (1996). Wireless communications: Principles and practice (Vol. 2). New Jersey: Prentice Hall PTR.
 Yang, L., & Yang, H-C. (2005). Cooperator switch diversity in cooperative networks. In 2005 IEEE Pacific rim conference on communications, computers and signal processing, 2005. PACRIM, pp. 308–311, IEEE.
 Robinson, Y. H., & Rajeswari, S. R. (2011). “Energy-based dynamic encryption for wireless sensor networks. Wireless Communication”, vol.3, no.9, pp. 661–663.
 Mller, A., & Speidel, J. (2010). Switch-and-stay transmit diversity for cooperative decode-and-forward systems. In Wireless communications and networking conference (WCNC), pp. 1–6.
 Selvaraj, M. D., & Mallik, R. K. (2009). Error analysis of the decode and forward protocol with selection combining. IEEE Transactions on Wireless Communications, 8(6), 3086–3094.
 Harold Robinson, Y., & Rajaram, M. (2014). “A novel approach to allocate channels dynamically in wireless mesh networks”, World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 8, no.10, pp. 1865–1868.
 Selvaraj, M. D., & Mallik, R. K. (2012). Performance of full CSI selection combining for cooperative diversity systems’. IEEE Transactions on Communications, 60(9), 2482–2488.
 Ko, Y.-C., Alouini, M.-S., & Simon, M. K. (2000). Average SNR of dual selection combining over correlated Nakagami-m fading channels. IEEE Communications Letters, 4(1), 12–14.
 Golden Julie, E., Tamil Selvi, S., & Harold Robinson, Y. (2014). “Opportunistic routing with secure coded wireless multicast using MAS approach”, World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 8, no.7, pp. 1247–1250.
 Li, G., et al. (2012). Performance analysis of incremental relaying for amplify-and-forward cooperative networks in Nakagami-m channels. In 2012 2nd international conference on computer science and network technology (ICCSNT), IEEE, pp. 1681–1685.
 Kim, Y., & Beaulieu, N. (2015). SEP of decode-and-forward cooperative systems with relay selection in Nakagami-m fading channels. IEEE Transactions on Vechicular Technology, 64(5), 1882–1883.
 Golden Julie, E., Tamil Selvi, S., & Harold Robinson, Y. (2016). “Performance Analysis of Energy Efficient Virtual Back Bone Path Based Cluster Routing Protocol for WSN”, Wireless Personal Communications, Springer, 1–19, DOI 10.1007/s11277-016-3520-5.
 Swaminathan, R., Roy, R., & Selvaraj, M. (2015). Performance comparison of selection combining with full CSI and switch-and-examine combining with and without post-selection. IEEE Transactions on Vehicular Technology, 65(5), 3217–3230.
 Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer networks, 52(12), 2292–2330.
 Harold Robinson, Y., Rajaram, M., Golden Julie, E. and Balaji, S. (2016), “Detection of Black Holes in MANET Using Collaborative Watchdog with Fuzzy Logic”, World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:10, No:3, pp. 575 – 581.
 Stankovic, J. A., Wood, A. D., & He, T. (2011). Realistic applications for wireless sensor networks. In S. Nikoletseas & J. D. P. Rolim (Eds.), Theoretical aspects of distributed computing in sensor networks (pp. 835–863). Berlin: Springer.
 Momani, M., & Challa, S. (2010). Survey of trust models in different network domains. arXiv preprint arXiv:1010.0168.
 Golden Julie, E., & Tamil Selvi, S. (2016). Development of energy efficient clustering protocol in wireless sensor network using neuro-fuzzy approach. The Scientific World Journal 2016, Article ID 5063261, 1–8.
 Sakthidevi, I., & Srievidhyajanani, E. (2013). Secured fuzzy based routing framework for dynamic wireless sensor networks. In International conference on circuits, power and computing technologies (ICCPCT) (pp. 1041–1046). IEEE.
 Xia, H., Jia, Z., & Sha, E. H. M. (2014). Research of trust model based on fuzzy theory in mobile ad hoc networks. IET Information Security, 8(2), 88–103.
 E. Golden Julie, E. Sahaya Rose Vigita, S. Tamil Selvi (2014), “Distributed Self-Healing Protocol for Unattended Wireless Sensor Network”, World Academy of Science, Engineering and Technology, International Journal of Computer, Information, Systems and Control Engineering Vol:8 No:10, pp. 1680 – 1683.
 Xia, H., Jia, Z., Ju, L., Li, X., & Zhu, Y. (2011). A subjective trust management model with multiple decision factors for MANET based on AHP and fuzzy logic rules. In 2011 IEEE/ACM international conference on green computing and communications (GreenCom) (pp. 124–130). IEEE.
 Yu, L., Liu, Z., Gao, Y., & Samba, D. (2012). Trust evaluation model based on behavior space classification for ad hoc networks. Tsinghua Science and Technology, 17(2), 179–185.
 S. Balaji, M. Rajaram (2014), “EUDIS-An Encryption Scheme for User-Data Security in Public Networks”, World Academy of Science, Engineering and Technology, International Journal of Computer, Information, Systems and Control Engineering Vol:8 No:11, pp. 1825 – 1830.
 Luo, J., Liu, X., Zhang, Y., Ye, D., & Xu, Z. (2008). Fuzzy trust recommendation based on collaborative filtering for mobile ad-hoc networks. In 33rd IEEE conference on local computer networks (LCN) (pp. 305–311). Montreal.
 Xia, H., Jia, Z., Ju, L., & Zhu, Y. (2011). Trust management model for mobile ad hoc network based on analytic hierarchy process and fuzzy theory. IET Wireless Sensor Systems, 1(4), 248–266.
 G. Arun SamPaul Thomas, R.Karthik Ganesh, A.Kandasamy, S.Balaji, Y. Harold Robinson, (2011) “An Advanced Controlled-Flooding Routing with Group Organization for Delay Tolerant Networks using A-SMART”, Emerging Trends in Electrical and Computer Technology (ICETECT), 978-1-4244-7926-9/11, IEEE.
 Li, X., Jia, Z., Zhang, P., & Wang, H. (2010). A trust-based multipath routing framework for Mobile Ad hoc NETworks. In 2010 Seventh international conference on fuzzy systems and knowledge discovery (FSKD) (Vol. 2, pp. 773–777). IEEE.
 Liao, X. F. (2011). Research on subject trust evaluation based on fuzzy theory. In Advanced engineering forum (Vol. 1, pp. 52–56). Trans Tech Publications.
 S. Balaji, M. Rajaram (2016), “SIPTAN: Securing Inimitable and Plundering Track for Ad Hoc Network”, Wireless Personal Communications, Springer, 1-21, DOI 10.1007/s11277-016-3187-y.
 Abouelfadl, A. A., El-Bendary, M. A. M., & Shawki, F. (2014). Enhancing transmission over wirelessimage sensor networks based on ZigBee network. Life Science Journal, 11(8), 342–354.
 El-Bendary M. A. M.,, Kasban, H., & El-Tokhy, M. A. R. (2014). Interleaved reed-solomon codes with code rate switching over wireless communications channels. In: International Journal of Information Technology and Computer Science (IJITCS) (http://www.ijitcs.com) on, 16(1).
 Harold Robinson, Y, Golden Julie E, Balaji S, Ayyasamy A, (2016), Energy Aware Clustering Scheme in Wireless Sensor Network Using Neuro-Fuzzy Approach , Wireless Personal Communications, Springer, 1-19, Doi: 10.1007/s11277-016-3793-8
 Y. Xu, A. Saifullah, Y. Chen, C. Lu, S. Bhattacharya, Near optimal multiapplication allocation in shared sensor networks, in: Proceedings of the Eleventh ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc ’10, ACM, New York, NY, USA, 2010, pp. 181–190. doi:10.1145/1860093.1860118. URL http://doi.acm.org/10.1145/ 1860093. 1860118.
 R. Huang, X. Chu, J. Zhang, Y. H. Hu, Energy-efficient monitoring in software defined wireless sensor networks using reinforcement learning: A prototype, International Journal of Distributed Sensor Networks 2015. doi:10.1155/2015/360428.
 S Balaji, M Rajaram, Y Harold Robinson, E Golden Julie (2016), ‘A Hypercube Social Feature Extraction and Multipath Routing in Delay Tolerant Networks’, International Journal of Computer, Electrical, Automation, Control and Information Engineering, World Academy of Science, Engineering and Technology, Vol. 10, No. 6, pp. 1212 – 1221.