Mobility and Heterogeneity Aware Cluster-Based Data Aggregation for Wireless Sensor Network

Internet of things (IoT) is the modern era, which offers a variety of novel applications for mobile targets and opens the new domains for the distributed data aggregations using Wireless Sensor Networks (WSNs). However, low cost tiny sensors used for network formation generate the large amount of redundant sensing data and hence, results in energy and bandwidth constraints. In this context, the paper proposes the sink mobility and nodes heterogeneity aware cluster-based data aggregation algorithm (MHCDA) for efficient bandwidth utilization and an increase in network lifetime. The proposed algorithm uses a predefined region for the aggregation of packets at the cluster head for minimizing computation and communication cost. MHCDA exploits correlation of data packets generated by nodes with a variable packet generation rate to reduce energy consumption by 8.66%. Also, it prolongs the network life by 23.53 % as compared to with and without mobility of the sink and state of the-art solutions.