Utilisation of multi‐objective immune deployment algorithm for coverage area maximisation with limit mobility in wireless sensors networks

Abstract

Coverage is one of the most important performance metrics for wireless sensor network (WSN) since it reflects how well a sensor field is monitored. The coverage issue in WSNs depends on many factors, such as the network topology, sensor sensing model and the most important one is the deployment strategy. Random deployment of the sensor nodes can cause coverage holes formulation. This problem is non-deterministic polynomial-time hard problem. So in this study, a new centralised deployment algorithm based on the immune optimisation algorithm is proposed to relocate the mobile nodes after the initial configuration to maximise the coverage area. Moreover, the proposed algorithm limits the moving distance of the mobile nodes to reduce the dissipation energy in mobility and to ensure the connectivity among the sensor nodes. The performance of the proposed algorithm is compared with the previous algorithms using Matlab simulation. Simulation results clear that the proposed algorithm based on binary and probabilistic sensing models improves the network coverage and the redundant covered area with minimum moving consumption energy. Furthermore, the simulation results show that the proposed algorithm also works when obstacles appear in the sensing field.

Minimizing sensor movement in target coverage problem: A hybrid approach using Voronoi partition and swarm intelligence

“…In 2015, Zahhad et al [10] noted the coverage problem that is mentioned in Hui et al [11] work on hybrid sensor deployment strategy. For relocating the mobile nodes after the initial configuration to maximise the coverage area, they proposed a new centralised deployment algorithm based on the immune optimisation algorithm.…”

“…Based on immune algorithm, a new centralized algorithm is used to maximize the coverage area with less energy utilization. So, the centralized algorithm has an advantage over the very low processing power of the sensor nodes [10].…”

“…Based on immune algorithm, a new centralized algorithm is used to maximize the coverage area with less energy utilization. So, the centralized algorithm has an advantage over the very low processing power of the sensor nodes [10].Sensor deployment is the basic problem in WSNs. It is divided into two kinds of methods: based on continued points and based on grid [11].…”

Resource Optimization in Wireless Sensor Networks for an Improved Field Coverage and Cooperative Target Tracking

“…Coverage optimization problems for WSNs has been tackled many times in the literature. For limited mobility nodes, an artificial immune system (AIS) algorithm was investigated to maximize the coverage area [2], where the traveled distance was utilized as a measure for mobility cost. Yoon and Kim introduced a novel normalization method to the genetic algorithm (GA), which reduced the redundancy in the solution space resulting in a better performance [3].…”

“…The objective of this relocation is to maximize the coverage rate. For this we follow a probabilistic sensing model, where each sensor has a circular sensing/detection area with a radius of R s [2],…”