Affiliation:
1. Anil Neerukonda Institute of Technology & Sciences, Bheemunipatnam, India
Abstract
In wireless sensor networks (WSNs), consumption of energy is the major challenging issue. If the data is transmitted directly from the node to the base station, it leads to more transmissions and energy consumed also increases if the communication distance is longer. In such cases, to reduce the longer communication distances and to reduce the number of transmissions, a clustering technique is employed. Another way to reduce the energy consumed is to reduce the transmission from node to CH or from CH to BS. Reducing the transmission distance is a NP-Hard problem. So, optimization techniques can be used effectively to solve such problems. In this article, is the implementation of a social group optimization (SGO) to reduce the transmission distance and to allow the nodes to consume less energy. The performance of SGO is compared with GA and PSO and the results show that SGO outperforms in terms of fitness and energy.
Cited by
2 articles.
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1. Enhancing Energy Efficiency in Cluster Based WSN using Grey Wolf Optimization;ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal;2023-11-01
2. GWO-C: Grey wolf optimizer-based clustering scheme for WSNs;International Journal of Communication Systems;2020-02-06