Acta Metallurgica Sinica(English letters) ›› 2011, Vol. 18 ›› Issue (6): 89-97.doi: 10.1016/S1005-8885(10)60126-4

• Wireless • Previous Articles     Next Articles

Unequal clustering algorithm for WSN based on fuzzy logic and improved ACO

Song MAO,Zhao Cheng-Lin   

  1. 1. Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China 2. Wireless Network Lab, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2011-04-27 Revised:2011-10-18 Online:2011-12-31 Published:2011-12-30
  • Contact: Song MAO
  • Supported by:

    This work was supported by National Science and Technology Major Project of the Ministry of Science and Technology of China (2009ZX03006-006, 2009ZX03006-009), and the National Natural Science Foundation of China (60902046, 60972079).


This paper proposes a novel energy efficient unequal clustering algorithm for large scale wireless sensor network (WSN) which aims to balance the node power consumption and prolong the network lifetime as long as possible. Our approach focuses on energy efficient unequal clustering scheme and inter-cluster routing protocol. On the one hand, considering each node’s local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine one node’s chance of becoming cluster head and estimate the corresponding competence radius. On the other hand, adaptive max-min ant colony optimization is used to construct energy-aware inter-cluster routing between cluster heads and base station (BS), which balances the energy consumption of cluster heads and alleviates the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The confirmation experiment results have indicated the proposed clustering algorithm has more superior performance than other methods such as low energy adaptive clustering hierarchy (LEACH) and energy efficient unequal clustering (EEUC).

Key words:

WSN, unequal clustering, fuzzy logic, adaptive max-min ant colony optimization (ACO), network lifetime

CLC Number: