Solving the load balanced clustering and routing problems in WSNs with an fpt-approximation algorithm and a grid structure
Clustering is an efficient technique in designing routing algorithms for Wireless Sensor Networks (WSNs), which prolongs the network lifetime and leads to scalability. However, in clustered WSNs, the cluster heads consume more energy than the other nodes and thus die sooner. Therefore, the load of s...
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| Veröffentlicht in: | Pervasive and mobile computing Jg. 58; S. 101033 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier B.V
01.08.2019
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| Schlagworte: | |
| ISSN: | 1574-1192, 1873-1589 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Clustering is an efficient technique in designing routing algorithms for Wireless Sensor Networks (WSNs), which prolongs the network lifetime and leads to scalability. However, in clustered WSNs, the cluster heads consume more energy than the other nodes and thus die sooner. Therefore, the load of sensor nodes must be balanced among the cluster heads in order to prolong the network lifetime. This problem is called load-balanced clustering problem, which is an NP-hard problem. In this paper, we propose an approximation algorithm to solve this problem with an approximation ratio of 1.1. This algorithm runs in fixed-parameter tractable time. We use a virtual grid infrastructure in the network, which makes the algorithm practical for large-scale WSNs. We also propose a routing algorithm based on this structure. The routing algorithm reduces and balances the energy consumption in the network by finding proper paths between each cluster head and the sink. The simulation results show that the proposed algorithm is practical for large-scale WSNs in addition to having a better performance compared with other similar algorithms. |
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| ISSN: | 1574-1192 1873-1589 |
| DOI: | 10.1016/j.pmcj.2019.101033 |