An improved DV-Hop algorithm based on PSO and Modified DE algorithm
Wireless sensor networks (WSN) have been used in many fields, and the localization technology is one of the core technologies of WSN. Distance Vector-Hop (DV-Hop) algorithm is one of the localization algorithms for WSN, which is widely used because of its simple principle and low cost. The tradition...
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| Published in | Telecommunication systems Vol. 82; no. 3; pp. 403 - 418 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.03.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1018-4864 1572-9451 |
| DOI | 10.1007/s11235-023-00991-w |
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| Abstract | Wireless sensor networks (WSN) have been used in many fields, and the localization technology is one of the core technologies of WSN. Distance Vector-Hop (DV-Hop) algorithm is one of the localization algorithms for WSN, which is widely used because of its simple principle and low cost. The traditional DV-Hop algorithm has high localization error, so the PMDDV-Hop algorithm is proposed in this paper. First, the average hop-size of anchor nodes is optimized by the Particle Swarm Optimization (PSO) algorithm to reduce the accumulation of errors. Then the coordinates of the unknown nodes are optimized using the Differential Evolutionary (DE) algorithm. To reduce the probability of falling into local optimum during evolution, the levy flight strategy is introduced into the DE algorithm to increase the diversity of the population. To further improve the performance of the PMDDV-Hop algorithm, the mutation factor and crossover factor in the DE algorithm are dynamically changed to make them adaptive to the degree of population evolution. Finally, extensive experimental simulations are conducted to evaluate the effectiveness of the PMDDV-Hop algorithm. Experimental results show that the PMDDV-Hop algorithm can effectively reduce the localization error. |
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| AbstractList | Wireless sensor networks (WSN) have been used in many fields, and the localization technology is one of the core technologies of WSN. Distance Vector-Hop (DV-Hop) algorithm is one of the localization algorithms for WSN, which is widely used because of its simple principle and low cost. The traditional DV-Hop algorithm has high localization error, so the PMDDV-Hop algorithm is proposed in this paper. First, the average hop-size of anchor nodes is optimized by the Particle Swarm Optimization (PSO) algorithm to reduce the accumulation of errors. Then the coordinates of the unknown nodes are optimized using the Differential Evolutionary (DE) algorithm. To reduce the probability of falling into local optimum during evolution, the levy flight strategy is introduced into the DE algorithm to increase the diversity of the population. To further improve the performance of the PMDDV-Hop algorithm, the mutation factor and crossover factor in the DE algorithm are dynamically changed to make them adaptive to the degree of population evolution. Finally, extensive experimental simulations are conducted to evaluate the effectiveness of the PMDDV-Hop algorithm. Experimental results show that the PMDDV-Hop algorithm can effectively reduce the localization error. |
| Author | Sun, Haibin Li, Hongxing Wang, Dong Meng, Ziran |
| Author_xml | – sequence: 1 givenname: Haibin surname: Sun fullname: Sun, Haibin organization: Computer Science and Engineering, Shandong University of Science and Technology – sequence: 2 givenname: Dong orcidid: 0000-0003-1341-0271 surname: Wang fullname: Wang, Dong email: wangdongcwc@163.com organization: Computer Science and Engineering, Shandong University of Science and Technology – sequence: 3 givenname: Hongxing surname: Li fullname: Li, Hongxing organization: Computer Science and Engineering, Shandong University of Science and Technology – sequence: 4 givenname: Ziran surname: Meng fullname: Meng, Ziran organization: Computer Science and Engineering, Shandong University of Science and Technology |
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| CitedBy_id | crossref_primary_10_1007_s11277_024_11571_9 crossref_primary_10_1016_j_procs_2024_10_124 crossref_primary_10_1007_s11227_024_06641_5 crossref_primary_10_3390_electronics12153220 crossref_primary_10_1109_ACCESS_2024_3384370 |
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| Keywords | Differential evolution Wireless sensor networks Levy flight Localization DV-Hop Optimization |
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| SubjectTerms | Algorithms Artificial Intelligence Business and Management Computer Communication Networks Evolutionary algorithms IT in Business Localization Mutation Nodes Particle swarm optimization Probability Theory and Stochastic Processes Telecommunications systems Wireless sensor networks |
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| Title | An improved DV-Hop algorithm based on PSO and Modified DE algorithm |
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