Abstract
Optimization is one of the best alternative solutions for addressing majority of the computational challenges associated with the wireless sensor network (WSN). At present, the successful implications of bio-inspired approaches are significantly proven to solve diversified complex problems in wireless network. However, after reviewing the existing literatures, it was found that yet there is bigger scope to enhance the capability of bio-inspired approach in the area of WSN. Therefore, this paper introduces a novel bio-inspired algorithm called as killer whale hunting (KWH) targeted for optimizing the data aggregation process with highly improved network sustenance capability. The formulation of the algorithm is designed on the basis of social and cognitive behaviour of killer whale which has a distinct style of hunting its prey. Using analytical modelling, the proposed approach was found to offer better energy efficiency and sufficient data forwarding capability in contrast to existing energy-efficient bio-inspired techniques.
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Parvathi, C., Talanki, S. (2020). Bio-Inspired Scheme of Killer Whale Hunting-Based Behaviour for Enhancing Performance of Wireless Sensor Network. In: Raju, K.S., Senkerik, R., Lanka, S.P., Rajagopal, V. (eds) Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 1079. Springer, Singapore. https://doi.org/10.1007/978-981-15-1097-7_29
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