Abstract
Wireless Sensor Network (WSN) plays a vital role in industrial application (IA) and is developing as a dynamic research area over previous years. The sensor nodes of WSN are energy constrained and hence the strategy of energy-efficient routing protocol remains as a significant concern to be tackled. The main issues addressed in WSNs are the network lifetime constraints and the time delay occurring in the transmission of data. Data routing remains to be a critical task in numerous decisive applications like military, ecosystem, survey disaster controlling etc. The shortest path is practiced by the Routing methods with minimal energy depletion pattern. The lifetime of WSNs can be enhanced through some of the Energy efficient clustering and routing algorithms. In this article, a new swarm intelligence optimization method named dragonfly algorithm (DA) is presented for cluster head selection in an energy efficient way. For efficient routing, the Glow-worm Swarm Optimization (GSO) algorithm is used. This method prolongs the lifetime of the network, alive nodes, throughput, total packet sent and similarly reduces the dead nodes, and the energy consumption of the network.
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Vinodhini, R., Gomathy, C. (2020). A Hybrid Approach for Energy Efficient Routing in WSN: Using DA and GSO Algorithms. In: Smys, S., Bestak, R., Rocha, Á. (eds) Inventive Computation Technologies. ICICIT 2019. Lecture Notes in Networks and Systems, vol 98. Springer, Cham. https://doi.org/10.1007/978-3-030-33846-6_55
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