Prolong life-span of WSN using clustering method via swarm intelligence and dynamical threshold control scheme

• Kaiyang Bao,
• Xiaoyuan Ma,
• Jianming Wei,

Vol. 10, No. 6, June 29, 2016
10.3837/tiis.2016.06.004, Download Paper (Free):

• Wireless Sensor Network
• Particle Swarm Optimization
• Ant colony optimization
• Dynamical threshold
• Swarm intelligence.

Abstract

Wireless sensors are always deployed in brutal environments, but as we know, the nodes are powered only by non-replaceable batteries with limited energy. Sending, receiving and transporting information require the supply of energy. The essential problem of wireless sensor network (WSN) is to save energy consumption and prolong network lifetime. This paper presents a new communication protocol for WSN called Dynamical Threshold Control Algorithm with three-parameter Particle Swarm Optimization and Ant Colony Optimization based on residual energy (DPA). We first use the state of WSN to partition the region adaptively. Moreover, a three-parameter of particle swarm optimization (PSO) algorithm is proposed and a new fitness function is obtained. The optimal path among the CHs and Base Station (BS) is obtained by the ant colony optimization (ACO) algorithm based on residual energy. Dynamical threshold control algorithm (DTCA) is introduced when we re-select the CHs. Compared to the results obtained by using APSO, ANT and I-LEACH protocols, our DPA protocol tremendously prolongs the lifecycle of network. We observe 48.3%, 43.0%, and 24.9% more percentages of rounds respectively performed by DPA over APSO, ANT and I-LEACH.

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