Protruder Optimization-Based Routing Protocol for Energy-Efficient Routing in Wireless Sensor Networks

Prajakta Thakare, V. Ravi Sankar

Source Title: International Journal of Business Data Communications and Networking (IJBDCN)17(2)

ISSN: 1548-0631|EISSN: 1548-064X|EISBN13: 9781799859574|DOI: 10.4018/IJBDCN.286701

MLA

Thakare, Prajakta, and V. Ravi Sankar. "Protruder Optimization-Based Routing Protocol for Energy-Efficient Routing in Wireless Sensor Networks." IJBDCN vol.17, no.2 2021: pp.1-25. http://doi.org/10.4018/IJBDCN.286701

APA

Thakare, P. & Sankar, V. R. (2021). Protruder Optimization-Based Routing Protocol for Energy-Efficient Routing in Wireless Sensor Networks. International Journal of Business Data Communications and Networking (IJBDCN), 17(2), 1-25. http://doi.org/10.4018/IJBDCN.286701

Chicago

Thakare, Prajakta, and V. Ravi Sankar. "Protruder Optimization-Based Routing Protocol for Energy-Efficient Routing in Wireless Sensor Networks," International Journal of Business Data Communications and Networking (IJBDCN) 17, no.2: 1-25. http://doi.org/10.4018/IJBDCN.286701

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Abstract

WSNs find valuable application in monitoring purposes, but they suffer from energy-efficiency issues that affect the network lifetime. The energy-efficiency problem is addressed using the cluster head (CH) formation, data aggregation, and routing techniques. Therefore, an energy-aware routing algorithm named protruder optimization algorithm is proposed, which boosts the network lifetime through finding the optimal routing path. The proposed protruder optimization is developed with the hybridization of the wave propagator characteristics and weed characteristics in such a way that the global optimal convergence is boosted while selecting the optimal routing path. Moreover, the communication in the network through the optimal path is progressed through the optimal CHs selection based on fractional artificial bee colony optimization (FABC), and in turn, the energy minimization problem is aided with data aggregation process using sliding window approach that avoids retransmission of the data. The results of the proposed method are compared with the existing methods on the basis of its performance measures, such as energy, alive nodes, and throughput.