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Particle Swarm Optimization with Taguchi for Cluster Heads Election in Wireless Sensor Networks |
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PP: 2015-2022 |
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Author(s) |
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Young-Long Chen,
Wan-Ren Chen,
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Abstract |
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The main features of wireless sensors are energy limited, hence, the algorithm design with the enhancement of energy
efficiency becomes an important topic. Divide cluster in a wireless sensor network (WSN) is a very important technology which can
blend the data into the cluster to expand the lifetime of the entire network. In this paper, we are going to propose a new algorithm to
be associated with a particle swarm optimization (PSO) algorithm and Taguchi algorithm to select the optimal cluster heads from a
wireless cluster sensor network. In a WSN, PSO algorithm is used to select cluster head and to reach the energy dissipation balance
among all nodes, which can in turn reduce the probability of the early death of the nodes. Meanwhile, the equation of optimal number
of clusters is used to decide the field number of clusters of low-energy adaptive clustering hierarchy (LEACH). In PSO algorithm, the
selection of parameter is very important, hence, in order to achieve optimal parameter value, too much number of experiments is usually
spent, therefore, in this paper, Taguchi algorithm was adopted to reduce the number of experiments and the energy dissipation of the
node. Consequently, we can get the optimal parameter value of PSO algorithm, and the energy dissipation of each node can then be
balanced. From the simulation result, it can be seen that our proposed PSO-LEACH architecture with Taguchi algorithm has reduced
energy dissipation as compared to LEACH architecture and PSO-LEACH architecture, meanwhile, the energy balance of each node
can be reached, and the lifetime of the entire wireless sensor network can then be extended. |
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