A heuristic node placement strategy for extending network lifetime and ensuring target coverage in mobile wireless sensor networks

Binh, Huynh Thi Thanh; Hanh, Nguyen Thi; Tan, Nguyen Phuc; Quan, La Van; Ngoc, Dang The; Minh, Nguyen Huu Nhat; Phap, Huynh Cong

doi:10.1007/s12065-024-00916-9

Evol. Intel.

2024

DOI: 10.1007/s12065-024-00916-9

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A heuristic node placement strategy for extending network lifetime and ensuring target coverage in mobile wireless sensor networks

Huynh Thi Thanh Binh,

Nguyen Thi Hanh,

Nguyen Phuc Tan

et al.

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Cited by 2 publications

References 29 publications

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UrMapSens: Joint Mapping-Sensing Design of Wireless Sensor Networks for Urban Environmental Monitoring

Boubrima,

Bechkit,

Rivano

et al. 2024

IEEE Sensors J.

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UrMapSens: Joint Mapping-Sensing Design of Wireless Sensor Networks for Urban Environmental Monitoring

Boubrima,

Bechkit,

Rivano

et al. 2024

IEEE Sensors J.

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An Enhanced Particle Swarm Optimization-Based Node Deployment and Coverage in Sensor Networks

Bhargavi,

Varma,

Hemalatha

et al. 2024

Sensors

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Positioning, coverage, and connectivity play important roles in next-generation wireless network applications. The coverage in a wireless sensor network (WSN) is a measure of how effectively a region of interest (ROI) is monitored and targets are detected by the sensor nodes. The random deployment of sensor nodes results in poor coverage in WSNs. Additionally, battery depletion at the sensor nodes creates coverage holes in the ROI and affects network coverage. To enhance the coverage, determining the optimal position of the sensor nodes in the ROI is essential. The objective of this study is to define the optimal locations of sensor nodes prior to their deployment in the given network terrain and to increase the coverage area using the proposed version of an enhanced particle swarm optimization (EPSO) algorithm for different frequency bands. The EPSO algorithm avoids the deployment of sensor nodes in close proximity to each other and ensures that every target is covered by at least one sensor node. It applies a probabilistic coverage model based on the Euclidean distances to detect the coverage holes in the initial deployment of sensor nodes and guarantees a higher coverage probability. Delaunay triangulation (DT) helps to enhance the coverage of a given network terrain in the presence of targets. The combination of EPSO and DT is applied to cover the holes and optimize the position of the remaining sensor nodes in the WSN. The fitness function of the EPSO algorithm yielded converged results with the average number of iterations of 78, 82, and 80 at 3.6 GHz, 26 GHz, and 38 GHz frequency bands, respectively. The results of the sensor deployment and coverage showed that the required coverage conditions were met with a communication radius of 4 m compared with 6–120 m with the existing works.

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A heuristic node placement strategy for extending network lifetime and ensuring target coverage in mobile wireless sensor networks

Cited by 2 publications

References 29 publications

UrMapSens: Joint Mapping-Sensing Design of Wireless Sensor Networks for Urban Environmental Monitoring

UrMapSens: Joint Mapping-Sensing Design of Wireless Sensor Networks for Urban Environmental Monitoring

An Enhanced Particle Swarm Optimization-Based Node Deployment and Coverage in Sensor Networks

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