Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization
For a hybrid sensor network, the effective coverage rate can be optimized by adjusting the location of the mobile nodes. For many deployments by APF (artificial potential field), due to the common problem of barrier effect, it is difficult for mobile nodes to diffuse by the weaker attraction when th...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-09-01
|
| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/251519 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849764370996789248 |
|---|---|
| author | Ying Zhang Yunlong Qiao Wei Zhao Wei Chen Jinde Cao |
| author_facet | Ying Zhang Yunlong Qiao Wei Zhao Wei Chen Jinde Cao |
| author_sort | Ying Zhang |
| collection | DOAJ |
| description | For a hybrid sensor network, the effective coverage rate can be optimized by adjusting the location of the mobile nodes. For many deployments by APF (artificial potential field), due to the common problem of barrier effect, it is difficult for mobile nodes to diffuse by the weaker attraction when the nodes initially distribute densely in some places. The proposed deployment algorithm PFPSO (Potential Field-Directed Particle Swarm Optimization) can overcome this problem and guide the mobile nodes to the optimal positions. Normally the requirement is different for the effective coverage rate between the hotspot area and the ordinary area. On the basis of PFPSO, NPFPSO (Nonuniform PFPSO) algorithm was also proposed to implement nonuniform coverage according to the importance degree of the monitoring area. Simulation result illustrates that PFPSO algorithm can effectively improve the effective coverage rate of the network, and NPFPSO algorithm can obtain a balanced result of effective coverage rate for both hotspot area and ordinary area. |
| format | Article |
| id | doaj-art-c6e209448cf14e96a2d33f6182f33bc7 |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-c6e209448cf14e96a2d33f6182f33bc72025-08-20T03:05:09ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-09-011110.1155/2015/251519251519Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm OptimizationYing Zhang0Yunlong Qiao1Wei Zhao2Wei Chen3Jinde Cao4 College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China Department of Computer Science, Tennessee State University, Nashville, TN 37209, USA Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi ArabiaFor a hybrid sensor network, the effective coverage rate can be optimized by adjusting the location of the mobile nodes. For many deployments by APF (artificial potential field), due to the common problem of barrier effect, it is difficult for mobile nodes to diffuse by the weaker attraction when the nodes initially distribute densely in some places. The proposed deployment algorithm PFPSO (Potential Field-Directed Particle Swarm Optimization) can overcome this problem and guide the mobile nodes to the optimal positions. Normally the requirement is different for the effective coverage rate between the hotspot area and the ordinary area. On the basis of PFPSO, NPFPSO (Nonuniform PFPSO) algorithm was also proposed to implement nonuniform coverage according to the importance degree of the monitoring area. Simulation result illustrates that PFPSO algorithm can effectively improve the effective coverage rate of the network, and NPFPSO algorithm can obtain a balanced result of effective coverage rate for both hotspot area and ordinary area.https://doi.org/10.1155/2015/251519 |
| spellingShingle | Ying Zhang Yunlong Qiao Wei Zhao Wei Chen Jinde Cao Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization International Journal of Distributed Sensor Networks |
| title | Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization |
| title_full | Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization |
| title_fullStr | Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization |
| title_full_unstemmed | Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization |
| title_short | Dynamic Deployment for Hybrid Sensor Networks Based on Potential Field-Directed Particle Swarm Optimization |
| title_sort | dynamic deployment for hybrid sensor networks based on potential field directed particle swarm optimization |
| url | https://doi.org/10.1155/2015/251519 |
| work_keys_str_mv | AT yingzhang dynamicdeploymentforhybridsensornetworksbasedonpotentialfielddirectedparticleswarmoptimization AT yunlongqiao dynamicdeploymentforhybridsensornetworksbasedonpotentialfielddirectedparticleswarmoptimization AT weizhao dynamicdeploymentforhybridsensornetworksbasedonpotentialfielddirectedparticleswarmoptimization AT weichen dynamicdeploymentforhybridsensornetworksbasedonpotentialfielddirectedparticleswarmoptimization AT jindecao dynamicdeploymentforhybridsensornetworksbasedonpotentialfielddirectedparticleswarmoptimization |