Design and Development of an Ant-based Load Balancing Algorithm in structured P2P clustered Network
Due to the advancement of technology Wireless Sensor Networks have gained great importance in the recent times. Sensor nodes are capable of carrying out certain processing, collecting needed data and interaction with other network nodes. Sensor nodes are of restricted energy which is a barrier during peak times in a network. Ant colony optimization is one of the methods used for optimizing the conservation of energy. A cluster in a network comprises of cluster members and cluster heads which are at one hop away from cluster head. The cluster head occupies the resources to its members of the cluster. Clustering is used to decrease the overhead of communication and thereby enhance the performance of the network. A cluster head is liable for not only passing data to the base station but also support the usual nodes to pass sensed data to target nodes. The cluster head energy consumption is larger than the general nodes. The selection of the cluster head will influence the lifetime of the wireless sensor network. In this study ant-based load balancing algorithm in a structured P2P clustered network is proposed for efficient selection of cluster head by removing the limitations of ant colony optimization in a mutual way. The ant colony optimization algorithm uses an artificial ants colony to predict the shortest path between the destination node and source node by predicting the cluster heads in the network. The ant colony optimization algorithm considers different parameters like the range of transmission, number of nodes, etc. The experimental results show that the proposed algorithm is an efficient methodology for predicting the minimum cluster head numbers.