A novel routing recovery strategy based on particle swarm algorithm for wireless sensor networks with multiple mobile sinks

Hu, Yi; Wu, Xiaodan; Wang, Fu Qiang; Liu, Xiangzhi; Han, Hua

doi:10.1109/icarcv.2014.7064386

Cited by 1 publication

(1 citation statement)

References 11 publications

(13 reference statements)

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“…Recently, centralized nature-inspired algorithms have been studied to design routing protocol for MWSNs and have been proven to be good a solutions [ 10 , 11 , 12 , 13 ]. PSO is now prevailing due to its simple concept, easy implementation and effectiveness [ 14 ]; therefore, in this study, we employ PSO to build the optimal routing tree.…”

Section: Introductionmentioning

confidence: 99%

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

Jian-hui

Liu

Cao

et al. 2016

Sensors

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Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

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