Node density based clustering to maximize the network lifetime of WSN using multiple mobile elements

Abstract

Collecting data from a large wireless sensor network (WSN) is a challenging issue and there are mainly two approaches to increase the efficiency: by hierarchical routing based on node clustering and by mobile elements (MEs). Since either method has pros and cons, this paper presents a hybrid approach, called Node Density based Clustering and Multiple Mobile Collection (NDCMMC), to combine the hierarchical routing and ME data collection in WSN. A Number of cluster heads (CHs) are selected and they collect data from normal nodes then MEs collect data from the cluster heads. For a randomly deployed WSN, a new CH selection scheme is based on the node density is proposed. The nodes which are surrounded by more deployed nodes are more likely to be CHs. In this paper, we have implemented multiple Mobile Elements to reduce delay in data gathering and to the increase the network lifetime. The advantage is that, the efficiency of both intra-cluster routing and ME data collection is improved. Low-complexity traveling track planning algorithm is designed for multiple MEs to pass by all CHs. The analytical model of NDCMMC is also developed and the expectation of the sensor power consumption and network lifetime are derived. The proposed work will add benefits to the existing work by improving two main advantages: reducing delay in data gathering and maximize the network lifetime.