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CGARP: Chaos genetic algorithm-based relay node placement for multifaceted heterogeneous wireless sensor networks: CGARP: Chaos genetic algorithm-based relay node placement for multifaceted heterogeneous
Relay node deployment in wireless sensor network (WSN) is significantly explored in specialized literature. There is a wide spectrum of performance issues like connectivity, coverage, energy efficiency, latency of packet delivery that have been considered as the target criteria to be optimized with...
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Published in: | Innovations in systems and software engineering 2024, Vol.20 (4), p.689-704 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | Relay node deployment in wireless sensor network (WSN) is significantly explored in specialized literature. There is a wide spectrum of performance issues like connectivity, coverage, energy efficiency, latency of packet delivery that have been considered as the target criteria to be optimized with the deployment strategies of relay nodes. The dynamic variation of different attributes of the sensor nodes leverages a heterogeneous topology. None of the literature has considered a heterogeneity-aware relay node placement strategy to pacify the effect of structural diversity on network performance. In this work, we propose chaos genetic algorithm-based relay node placement (CGARP) which takes care of the structural heterogeneity of WSN. CGARP is based on chaos genetic algorithm (CGA), which overcomes the problem of premature convergence of genetic algorithm.
Tent Map
-based generation of the initial population and
Logistic Map
-based chaotic crossover enable CGARP to work well in WSN. The proposed technique has been compared with other relay node placement solutions available in the literature. CGARP achieves 68% improvement in average network lifetime in a 2D grid. It also results in 27% better connectivity and 23% improvement in the usage of relay nodes compared to EERP. The results are obtained through properly designed experiments with simulated realistic environments. These results substantiate the improvements achieved by the proposed approach. |
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ISSN: | 1614-5046 1614-5054 |
DOI: | 10.1007/s11334-022-00439-5 |