Optimum deployment of sensor nodes in wireless sensor network using hybrid fruit fly optimization algorithm and bat optimization algorithm for 3D Environment

Satinder Singh Mohar

doi:10.1007/s12083-022-01364-x

Optimum deployment of sensor nodes in wireless sensor network using hybrid fruit fly optimization algorithm and bat optimization algorithm for 3D Environment

2022-08-11

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AI

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Satinder Singh Mohar *

DOI：10.1007/s12083-022-01364-x

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Deployment of sensor nodes in three dimensional areas with sufficient coverage of sensor nodes is one of the major challenges in wireless sensor network. Coverage is main concern in node deployment because it influences the performance of wireless sensor network. For better performance of wireless sensor network it is essential to increase the coverage of nodes by locating the nodes at optimum positions with help of efficient optimization algorithm. In this paper the sensor nodes are located by using Hybrid fruit fly optimization algorithm and bat optimization algorithm in three dimensional environment. The exploration feature of fruit fly optimization algorithm is combined with exploitation characteristics of bat optimization algorithm in proposed algorithm. The grid points covered once by sensor node are removed from entire grid points for remaining nodes. With removal of grid points the overload on sensor nodes is reduced in proposed algorithm. The simulation results of Hybrid fruit fly optimization algorithm and bat optimization algorithm are compared in terms of variance, standard deviation, coverage rate and coefficient of dispersion with fruit fly optimization algorithm and bat optimization algorithm. Moreover, to verify the efficiency of proposed algorithm the results are also compared with other optimization algorithms such as artificial bee colony algorithm with dynamic search strategy, grey wolf optimization algorithm, enhanced grey wolf optimization algorithm, whale optimization algorithm, hybrid shuffled frog leaping algorithm and whale optimization algorithm, differential evolution algorithm, shuffled frog leaping algorithm, hybrid shuffled frog leaping algorithm and whale optimization algorithm based on differential evolution respectively. The simulation result signifies that proposed Hybrid fruit fly optimization algorithm and bat optimization algorithm is efficient than above stated existing optimization algorithm in terms of average coverage rate. The simulation results also demonstrate that proposed algorithm has attained maximum coverage about 99.25% which is higher as compared to existing algorithms. The standard deviation of proposed algorithm is least i.e. 0.0012 which means proposed algorithm is more reliable as compared to existing algorithms for deploying sensor nodes in three dimensional wireless sensor network.

Keyword:

Sensor nodes

Bat optimization algorithm

Wireless sensor network

Node deployment

Fruit fly optimization algorithm

Optimum deployment of sensor nodes in wireless sensor network using hybrid fruit fly optimization algorithm and bat optimization algorithm for 3D Environment

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