Optimal Sensor Nodes Deployment Method Using Bacteria Foraging Algorithm in Wireless Sensor Networks

Abstract

Abstract. The nodes in wireless sensor networks (WSN) need to be deployed optimally to cover whole geographic area and the communication link between them should be optimal. During deployment in remote locations, simulation of the proposed algorithm can be used for optimally deploying the sensor nodes in the area. Bacteria foraging is the nature inspired algorithm which is used to make clusters among various similar entities. Here the nodes to be deployed can be taken as the bacteria that are in search of the food which is depicted by the best possible communication link. This paper presents a novel algorithm for optimal sensor node deployment leading to optimal clustering of WSN nodes. This paper utilizes the fact that an area can be covered fully using regular hexagon. So using a bacteria foraging algorithm for optimization the locations are such adjusted that all the nodes in the network moves to vertices of regular hexagons connected with each other. This leads to complete coverage of the area and all the nodes are equidistant.

Hybrid ANT Colony Optimization Routing Algorithm using for AODV Protocol Improvement in Flying Adhoc Network

“…In 2013, Pooja et al [15] discussed about the coverage can increase the effective distance of the sensor as a problem, affecting the power required by the system. This is a unique problem and, at maximum coverage, the sensor must be maintained in a situation where the sensitivity of the network is fully utilized to ensure the high quality of the service.…”

Evolutionary Algorithms for Clustering in Wireless Sensor Networks

“…Bacteria Foraging Algorithm (BFA) [29]: is a novel algorithm for optimal sensor node deployment leading to optimal clustering of WSN nodes is presented. Using a bacteria foraging algorithm for optimizing the locations are adjusted such that all the nodes in the network moves to vertices of regular hexagons connected with each other.…”

“…Clustering characteristics [29,21]  Clustering Method: If the algorithm is centralized the control message for cluster formation and CH selection will be received from the BS based on information gathered from all nodes to elect the appropriate number of clusters and the most efficient nodes to act as CHs every iteration but in case distributed algorithm these decisions will be taken by the nodes themselves. Hybrid scheme can be performed by a combination of centralized and distributed.…”