A clustering routing algorithm based on wolf pack algorithm for heterogeneous wireless sensor networks
In order to maximize the network performance of heterogeneous sensor networks and effectively control the network cost, a clustering routing algorithm based on wolf pack algorithm (CLWPA) for heterogeneous wireless sensor networks is proposed. Firstly, the optimal deployment of heterogeneous nodes i...
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| Published in: | Computer networks (Amsterdam, Netherlands : 1999) Vol. 167; p. 106994 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Amsterdam
Elsevier B.V
11.02.2020
Elsevier Sequoia S.A |
| Subjects: | |
| ISSN: | 1389-1286, 1872-7069 |
| Online Access: | Get full text |
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| Summary: | In order to maximize the network performance of heterogeneous sensor networks and effectively control the network cost, a clustering routing algorithm based on wolf pack algorithm (CLWPA) for heterogeneous wireless sensor networks is proposed. Firstly, the optimal deployment of heterogeneous nodes is transformed into a mixed integer programming problem. The approximate optimal solution of the problem is obtained by through the wolf pack algorithm (WPA) which improved by logistic function and levy flight, then a heterogeneous network routing algorithm based on the improved wolf pack algorithm (LWPA) is proposed. Secondly, in order to solve the problem of fixed path in LWPA routing algorithm, the concept of edge degree is introduced to improve DEEC algorithm. The improved DEEC algorithm (IDEEC) is used to dynamically cluster common nodes in heterogeneous networks, and the data transmission mode is carried out after the clustering mode set. Finally, through simulation analysis, compared with other three heterogeneous network routing algorithms, CLWPA algorithm effectively prolongs the network's stable period and lifetime, and the energy consumption is more balanced. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1389-1286 1872-7069 |
| DOI: | 10.1016/j.comnet.2019.106994 |