Abstract
Wireless Sensor Networks (WSNs) ordinarily be composed of a large number of low-power sensor nodes which having several functions, that are a battery powered, and thus have very limited energy capacity. To lengthen the operational lifetime of a sensor network, energy efficiency should be considered in every aspect of sensor network design. In this paper, Enhanced Hierarchical Routing Technique (EHRT) is proposed to overcome the constraint of limited energy capacity of sensor nodes which enhancing the network lifetime and the energy efficiency. The suggested technique is a cluster-based routing which optimizes the low-energy adaptive clustering hierarchy routing technique (LEACH) by using a modified artificial fish swarm algorithm (AFSA). This modified AFSA selects the optimum clusters’ head (CHs) locations by applying a number of behaviors following, preying and swarming on each cluster separately and using a modified fitness function to compare these behaviors’ outputs to select the best CHs locations for each cluster separately. A framework for evaluating the performance is constructed and applied to verify the efficiency of the suggested technique comparing to other energy efficient routing techniques; optimized hierarchical routing technique (OHRT), low-energy adaptive clustering hierarchy (LEACH), and particle swarm optimized (PSO) routing techniques. The proposed technique yields best results than other techniques OHRT, LEACH, and PSO in terms of energy consumption and network lifetime. It reduces the energy dissipation by factor 0.7 compared with OHRT.
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Hamza, N.M., El-said, S.A., Attia, E.R.M., Abdalla, M.I. (2018). Energy Aware Optimized Hierarchical Routing Technique for Wireless Sensor Networks. In: Hassanien, A., Tolba, M., Elhoseny, M., Mostafa, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-74690-6_60
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DOI: https://doi.org/10.1007/978-3-319-74690-6_60
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