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Sensors 2010, 10(5), 4521-4540; doi:10.3390/s100504521

Article

A Multipath Routing Protocol Based on Clustering and Ant Colony Optimization for Wireless Sensor Networks

Jing Yang ^1,2,* , Mai Xu ^3,4, Wei Zhao ⁴ and Baoguo Xu ¹

¹ School of Communication and Control Engineering, Jinangnan University, Wuxi, 214122, China ² College of Electrical Engineering, Guizhou University, Guiyang, 550003, China ³ Department of Electrical and Electronic Engineering, Imperial College London, London, UK ⁴ Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China

* Author to whom correspondence should be addressed.

Received: 4 March 2010; in revised form: 14 April 2010 / Accepted: 16 April 2010 / Published: 4 May 2010

(This article belongs to the Special Issue Wireless Sensor Network and Its Application in Advanced Computer Science)

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Abstract: For monitoring burst events in a kind of reactive wireless sensor networks (WSNs), a multipath routing protocol (MRP) based on dynamic clustering and ant colony optimization (ACO) is proposed.. Such an approach can maximize the network lifetime and reduce the energy consumption. An important attribute of WSNs is their limited power supply, and therefore some metrics (such as energy consumption of communication among nodes, residual energy, path length) were considered as very important criteria while designing routing in the MRP. Firstly, a cluster head (CH) is selected among nodes located in the event area according to some parameters, such as residual energy. Secondly, an improved ACO algorithm is applied in the search for multiple paths between the CH and sink node. Finally, the CH dynamically chooses a route to transmit data with a probability that depends on many path metrics, such as energy consumption. The simulation results show that MRP can prolong the network lifetime, as well as balance of energy consumption among nodes and reduce the average energy consumption effectively.

Keywords: wireless sensor networks (WSNs); clustering; multipath; ant colony optimization (ACO)

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