Abstract: Wireless Sensor Network(WSN) are very popular as they are low cost solutions to many real-world challenges with limited computational power, battery life and memory resources. Past few years have witnessed increased in the potential use of wireless sensor network (WSN) such as military surveillance, tracking and monitoring, disaster management and combat field reconnaissance. Sensor nodes involved in these applications are remotely deployed in large numbers. These autonomous nodes are used to monitor an environment. Many issues in WSN are formulated as multidimensional optimization problem and solved through bio-inspired techniques. The main problem in WSN is the lifetime of network. To support scalability, nodes are often grouped in clusters having a leader, often referred as cluster head (CH). A CH is responsible for not only sending data to base station but also assist the general nodes to send sensed data to target nodes. The energy consumption of CH is greater than general nodes. Therefore CH selection will affect the lifetime of WSN. In this paper, an approach is introduced for the selection of cluster head by using swarm intelligence. This proposed approach is based on energy distributed clustering (EDC) algorithm. Honey bee optimization with some parameters are employed over EDC algorithm for effective cluster head selection. This approach helps in reducing the energy consumption. This proposed technique works in three stages: Cluster nodes sends data to CH, CH sends data directly to Leader and leader sends data to BS. Simulations results demonstrate that EDC-HBO algorithm improves the life time of network
Keywords: Wireless Sensor Network, Cluster Head, HBO, Energy Distributed Clustering, Fitness Value.