A routing algorithm for wireless sensor networks based on clustering and an fpt-approximation algorithm

•An FPT-approximation algorithm to solve the load-balanced clustering problem.•The proposed FPT-approximation algorithm has an approximation factor of 1.2.•The algorithm is practical for WSNs with up to 800 sensors and 40 cluster heads.•A new energy-efficient and energy-balanced routing algorithm in...

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Vydané v:The Journal of systems and software Ročník 155; s. 145 - 161
Hlavní autori: Yarinezhad, Ramin, Hashemi, Seyed Naser
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Inc 01.09.2019
Predmet:
Energy-aware
Load balancing
Multi-hop routing
Wireless sensor network
Wireless sensor network
Multi-hop routing
Energy-aware
Load balancing
ISSN:0164-1212, 1873-1228
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Shrnutí:•An FPT-approximation algorithm to solve the load-balanced clustering problem.•The proposed FPT-approximation algorithm has an approximation factor of 1.2.•The algorithm is practical for WSNs with up to 800 sensors and 40 cluster heads.•A new energy-efficient and energy-balanced routing algorithm in WSNs. Clustering sensor nodes is an effective method for routing in Wireless Sensor Networks (WSNs), which maximizes the network lifetime and reduces the energy consumption. However, in a clustered-WSN, the Cluster Heads (CHs) bear a higher load compared to the other nodes, which leads to their earlier death. Therefore, minimizing the maximum load of the CHs is an important problem, which is called the Load-Balanced Clustering Problem (LBCP). LBCP is an NP-hard problem and the best-known approximation factor for this problem is 1.5. Moreover, it has been shown that there is no polynomial-time approximation algorithm that solves this problem with a better approximation factor. In this paper, we propose a Fixed Parameter Tractable (FPT) approximation algorithm with an approximation factor of 1.2 for LBCP. We also propose an energy-efficient and energy-balanced routing algorithm for routing between the CHs and the sink. The simulation results show that the proposed algorithm is practical for large-scale WSNs and performs better than the other similar algorithms.
ISSN:0164-1212
1873-1228
DOI:10.1016/j.jss.2019.05.032