Region-Based Clustering Approach for Energy Efficient Wireless Sensor Networks

TLDR: The proposed clustering technique can be used in military applications to detect and gain information about enemy movements and reduces energy consumption, prolongs network lifetime, and achieves scalability.

Abstract: Nowadays there is a huge increase in the use of sensors in various applications such as remote monitoring of environment, automobiles, disaster prone zones, home control, and military applications. The capabilities of Wireless Sensor Network (WSN) can be extended using self-organization to change their behavior dynamically and achieve network wide characteristics. Clustering techniques show the self-organized behavior of WSNs. Sensor nodes are grouped into disjoint, nonoverlapping subsets called clusters. Cluster Heads (CHs) collect data from the sensor nodes present in the cluster and forward it to the neighboring nodes using shortest path distance calculation and finally to the Base Station (BS). In the proposed clustering technique, network area is divided into regions. Cluster Head (CH) is elected by using the highest residual energy and the node degree. Cluster communication is at the most two-hop which results in less number of messages from member nodes to BS. Within a cluster, data is sent to CH by member nodes. After some time CH’s energy level goes below threshold value, then new CH is elected and clusters are reformed within each region. Our proposed clustering technique can be used in military applications to detect and gain information about enemy movements. Results are obtained by varying the number of nodes at different transmission ranges. The simulation results show that the proposed clustering algorithm reduces energy consumption, prolongs network lifetime, and achieves scalability.