Minimum distance clustering algorithm based on an improved differential evolution
by Xiangyuan Yin; Zhihao Ling; Liping Guan; Feng Liang
International Journal of Sensor Networks (IJSNET), Vol. 15, No. 1, 2014

Abstract: The goals of wireless sensor networks (WSNs) are to sense and collect data and to transmit the information to a sink. Because the sensor nodes are typically battery powered, the main challenges in WSNs are to optimise the energy consumption and to prolong the network lifetime. This paper proposes a centralised clustering algorithm termed the minimum distance clustering algorithm that is based on an improved differential evolution (MD-IDE). The new algorithm combines the advantages of simulated annealing and differential evolution to determine the cluster heads (CHs) for minimising the communication distance of the WSN. Many simulation results demonstrate that the performance of MD-IDE outperforms other well-known protocols, including the low-energy adaptive clustering hierarchy (LEACH) and LEACH-C algorithms, in the aspects of reducing the communication distance of the WSN for reducing energy consumption.

Online publication date: Sun, 12-Oct-2014

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