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Sensors 2016, 16(7), 1081; doi:10.3390/s16071081

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

1
School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China
2
School of Medical Information and Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, China
3
Data Analytics Department, Institute for Infocomm Research, 1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632, Singapore
*
Author to whom correspondence should be addressed.
Academic Editors: Mianxiong Dong, Zhi Liu, Anfeng Liu and Didier El Baz
Received: 4 June 2016 / Revised: 6 July 2016 / Accepted: 8 July 2016 / Published: 14 July 2016
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
View Full-Text   |   Download PDF [4636 KB, uploaded 14 July 2016]   |  

Abstract

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. View Full-Text
Keywords: discrete particle swarm optimization; wireless sensor network with mobile sinks; routing; energy efficiency discrete particle swarm optimization; wireless sensor network with mobile sinks; routing; energy efficiency
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Yang, J.; Liu, F.; Cao, J.; Wang, L. Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks. Sensors 2016, 16, 1081.

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