Rearrangement of mobile wireless sensor nodes for coverage maximization based on immune node deployment algorithm

Abo‐Zahhad, Mohammed; Ahmed, Sabah M.; Sabor, Nabil; Sasaki, Shigenobu

doi:10.1016/j.compeleceng.2015.04.003

Cited by 29 publications

(15 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The traditional random node deployment will form coverage holes in the perceptual area. In response to this, Mohammed Abo-Zahhad et al 2005 [7] proposed a WSNs deployment approach based on a multiobjective immune algorithm. This method redefines sensor nodes to reduce coverage holes and improve network coverage, saves energy consumption, and guarantees connectivity while limiting sensor mobile costs.…”

Section: Deployment Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of node deployment in wireless sensor networks in warehouse environment monitoring systems

Mao

Jiang

Zhang

2019

J Wireless Com Network

View full text Add to dashboard Cite

This paper mainly studies the deployment of wireless sensor network nodes in the warehouse environment monitoring system, discusses the deployment algorithm of wireless sensor network nodes in the warehouse environment, and finds out the node deployment scheme with better network performance through comparison. Wireless sensor network node deployment is the basis of wireless sensor network application in storage environment monitoring system. It affects the performance of the whole network and is the primary problem to be solved in network application. This paper discusses the advantages of wireless sensor network in the monitoring of storage environment, especially the deployment and simulation analysis of sensor nodes in the warehouse environment. Aiming at the influence of sensor perception model on the effectiveness of the node deployment plan, this paper proposes a node deployment collaborative perception model based on 0-1 perception model and exponential model. The sensor node deployment problem is transformed into a three-dimensional node deployment problem. Finally, the algorithm is applied to tobacco storage environment. In order to verify the effectiveness of the proposed algorithm, the scheme obtained by the proposed algorithm is compared with that obtained by the corresponding deployment algorithm in this paper. The comparison results show that the overall performance of the algorithm is better than that of the usual scheme.

show abstract

Section: Deployment Methodsmentioning

confidence: 99%

“…By superposing the coordinates of the class B node obtained by offset γ and step (3), the coordinates of the class B node are obtained (7). Determine whether L 00 A exceeds the limit range.…”

mentioning

confidence: 99%

Analysis of node deployment in wireless sensor networks in warehouse environment monitoring systems

Mao

Jiang

Zhang

2019

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…They define an optimization problem solved with a linear programming model and the energy management aspect is not considered. Abo Zahhad et al [22] use a Multi-objective algorithm to solve the coverage problem. Their algorithm aims to cover the whole area by finding the minimum movement to assign at each sensor; but, though, the energy aspect is not considered.…”

Section: Related Problemsmentioning

confidence: 99%

DACYCLEM: A decentralized algorithm for maximizing coverage and lifetime in a mobile wireless sensor network

et al. 2019

View full text Add to dashboard Cite

“…In the past, UWSN redeployment algorithms were mainly based on graph theory, cube lattice category, virtual force and swarm intelligence optimization, and other related ways [10,11,12,13,14,15]. The first three types of redeployment algorithms are relatively complex and unsuitable for large-scale underwater environmental problems.…”

Section: Introductionmentioning

confidence: 99%

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

Jiang

Yang

2016

Sensors

View full text Add to dashboard Cite

This study addresses the optimization of node redeployment coverage in underwater wireless sensor networks. Given that nodes could easily become invalid under a poor environment and the large scale of underwater wireless sensor networks, an underwater sensor network redeployment algorithm was developed based on wolf search. This study is to apply the wolf search algorithm combined with crowded degree control in the deployment of underwater wireless sensor networks. The proposed algorithm uses nodes to ensure coverage of the events, and it avoids the prematurity of the nodes. The algorithm has good coverage effects. In addition, considering that obstacles exist in the underwater environment, nodes are prevented from being invalid by imitating the mechanism of avoiding predators. Thus, the energy consumption of the network is reduced. Comparative analysis shows that the algorithm is simple and effective in wireless sensor network deployment. Compared with the optimized artificial fish swarm algorithm, the proposed algorithm exhibits advantages in network coverage, energy conservation, and obstacle avoidance.

show abstract

Rearrangement of mobile wireless sensor nodes for coverage maximization based on immune node deployment algorithm

Cited by 29 publications

References 12 publications

Analysis of node deployment in wireless sensor networks in warehouse environment monitoring systems

Analysis of node deployment in wireless sensor networks in warehouse environment monitoring systems

DACYCLEM: A decentralized algorithm for maximizing coverage and lifetime in a mobile wireless sensor network

Underwater Sensor Network Redeployment Algorithm Based on Wolf Search

Contact Info

Product

Resources

About