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Load Balancing and Fault Tolerance-Based Routing in Wireless Sensor Networks

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International Conference on Innovative Computing and Communications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1059))

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Abstract

Energy-efficient data collection from the environment is a critical operation in many applications areas of wireless sensor networks (WSNs). Unprecedented techniques which help in ameliorating the energy efficiency are highly required to elongate the lifetime of the network. In WSNs, sensed data needs to be forwarded to the sink node in an energy-efficient manner. Multi-hop communication helps a lot in reducing the energy consumption if the parent node through which data needs to be transmitted is selected in an efficient manner. Some nodes get overloaded while others are having very less load when parent nodes are selected in a random manner. In this paper, we have proposed a linear optimization-based formulation to balance the load of the nodes by selecting the parent node in an efficient manner. Moreover, when after some interval of sensing, some parent nodes start to get dying, the child nodes change their parent node to avoid the packet loss. So, a fault tolerance strategy is also proposed. Simulation results verify that proposed work is outperforming in terms of packet delivery ratio, network lifetime, and count of dead nodes.

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References

  1. Rodríguez-Molina J, Martínez J-F, Castillejo P, López L (2013) Combining wireless sensor networks and semantic middleware for an internet of things-based sportsman/woman monitoring application. Sensors 13(2):1787–1835

    Article  Google Scholar 

  2. Nayyar A, Puri V, Nguyen NG (2019) Biosenhealth 1.0: a novel internet of medical things (IoMT)-based patient health monitoring system. In: International Conference on Innovative Computing and Communications. Springer, Berlin, pp 155–164

    Google Scholar 

  3. Chang J-H, Tassiulas L (2004) Maximum lifetime routing in wireless sensor networks. IEEE/ACM Trans Netw 12(4):609–619

    Article  Google Scholar 

  4. Inoue S, Kakuda Y, Kurokawa K, Dohi T (2010) A method to prolong the lifetime of sensor networks by adding new sensor nodes to energy-consumed areas. In: 2010 2nd international symposium on aware computing (ISAC). IEEE, pp 332–337

    Google Scholar 

  5. Bagci H, Yazici A (2013) An energy aware fuzzy approach to unequal clustering in wireless sensor networks. Appl Soft Comput 13(4):1741–1749

    Article  Google Scholar 

  6. Al-Kiyumi RM, Foh CH, Vural S, Chatzimisios P, Tafazolli R (2018) Fuzzy logic-based routing algorithm for lifetime enhancement in heterogeneous wireless sensor networks. IEEE Trans Green Commun Netw 2(2):517–532

    Article  Google Scholar 

  7. Ishmanov F, Malik AS, Kim SW (2011) Energy consumption balancing (ECB) issues and mechanisms in wireless sensor networks (WSNS): a comprehensive overview. Eur Trans Telecommun 22(4):151–167

    Article  Google Scholar 

  8. Guleria K, Verma AK (2018) Comprehensive review for energy efficient hierarchical routing protocols on wireless sensor networks. Wirel Netw 1–25

    Google Scholar 

  9. Dhivya Devi C, Vidya K (2019) A survey on cross-layer design approach for secure wireless sensor networks. In: International conference on innovative computing and communications. Springer, pp 43–59

    Google Scholar 

  10. Kacimi R, Dhaou R, Beylot A-L (2013) Load balancing techniques for lifetime maximizing in wireless sensor networks. Ad hoc Netw 11(8):2172–2186

    Article  Google Scholar 

  11. Mhatre V, Rosenberg C (2004) Homogeneous vs heterogeneous clustered sensor networks: a comparative study. In: ICC, pp 3646–3651

    Google Scholar 

  12. Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd annual Hawaii international conference on System sciences, 2000. IEEE, p 10

    Google Scholar 

  13. Asorey-Cacheda R, Garcia-Sanchez A-J, García-Sánchez F, García-Haro J (2017) A survey on non-linear optimization problems in wireless sensor networks. J Netw Comput Appl 82:1–20

    Article  Google Scholar 

  14. Abu-Baker A, Huang H, Johnson E, Misra S, Asorey-Cacheda R, Balakrishnan M (2010) Maximizing \(\alpha \)-lifetime of wireless sensor networks with solar energy sources. In: Military communications conference, 2010-MILCOM 2010. IEEE, pp 125–129

    Google Scholar 

  15. Kulkarni RV, Venayagamoorthy GK (2011) Particle swarm optimization in wireless-sensor networks: a brief survey. IEEE Trans Syst Man Cybern Part C (Appl Rev) 41(2):262–267

    Article  Google Scholar 

  16. Younis M, Akkaya K (2008) Strategies and techniques for node placement in wireless sensor networks: a survey. Ad Hoc Netw 6(4):621–655

    Article  Google Scholar 

  17. Rodoplu V, Meng TH (1998) Minimum energy mobile wireless networks. In: 1998 IEEE International Conference on Communications, 1998. ICC 98. Conference Record, vol 3. IEEE, pp 1633–1639

    Google Scholar 

  18. Singh S, Woo M, Raghavendra CS (1998) Power-aware routing in mobile ad hoc networks. In: Proceedings of the 4th annual ACM/IEEE international conference on mobile computing and networking. ACM, pp 181–190

    Google Scholar 

  19. Kim D, Garcia-Luna-Aceves JJ, Obraczka K, Cano J-C, Manzoni P (2003) Routing mechanisms for mobile ad hoc networks based on the energy drain rate. IEEE Trans Mob Comput 2(2):161–173

    Article  Google Scholar 

  20. Yen H-H (2009) Optimization-based channel constrained data aggregation routing algorithms in multi-radio wireless sensor networks. Sensors 9(6):4766–4788

    Article  Google Scholar 

  21. Ok C-S, Lee S, Mitra P, Kumara S (2009) Distributed energy balanced routing for wireless sensor networks. Comput Ind Eng 57(1):125–135

    Article  Google Scholar 

  22. Liu A, Ren J, Li X, Chen Z, Shen XS (2012) Design principles and improvement of cost function based energy aware routing algorithms for wireless sensor networks. Comput Netw 56(7):1951–1967

    Article  Google Scholar 

  23. Habibi J, Aghdam AG, Ghrayeb A (2015) A framework for evaluating the best achievable performance by distributed lifetime-efficient routing schemes in wireless sensor networks. IEEE Trans Wirel Commun 14(6):3231–3246

    Article  Google Scholar 

  24. Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 1(4):660–670

    Article  Google Scholar 

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Acknowledgements

Priti Maratha acknowledges the support from the University Grant Commission, New Delhi, under the National Eligibility Test-Junior Research Fellowship scheme with Reference ID-3361/ (NET-JUNE 2015).

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Correspondence to Priti Maratha .

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Maratha, P., Kapil (2020). Load Balancing and Fault Tolerance-Based Routing in Wireless Sensor Networks. In: Khanna, A., Gupta, D., Bhattacharyya, S., Snasel, V., Platos, J., Hassanien, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1059. Springer, Singapore. https://doi.org/10.1007/978-981-15-0324-5_24

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