Mobility management and adaptive dynamic clustering for mobile wireless sensor networks

Abstract

Mobile node Tracking and data gathering in wireless sensor networks (WSNs) is one of the challenging tasks. In this paper, we have shown the performance evaluation and testing results of our efficient routing algorithms in the context of MWSN for data gathering under various scenarios. In this progression, Distributed Cluster-based Algorithm for Target Tracking method is used to define the next position of the Node. Then, Prediction-Based Clustering Algorithm for Movement Detection method is used to catch the optimal data communication path. If the mobile nodes move within the range of the communicative region, it collects the data from neighbour Cluster Member (CM) and if Mobile Data Collector (MDC) moved out, it receives the routing information from neighbour cluster head (CH) and exchange that information with another MDCs. Our proposed algorithm minimizes the cluster overhead and improves the three tier routing problem using Adaptive Dynamic Clustering (ADC). Here the MDCs are performs like vehicle and gathering the information from neighbour CHs and CMs. The Performance evaluation results show that the proposed system efficiently supports for node mobility management with low control overhead and delay applications as compared to other cluster-based algorithms and also upturns the lifetime of the CH and packet delivery ratio when the number of sources Increases.