Design Technique for Head Selection in WSNs to Enhance the Network Performance Based on Nodes Residual Status: an Extension to EBRS Method
Abstract
Power efficiency plays a very important role in the sensor networks spatially in wireless networks like WSNs. These wireless networks are composed of geographically scattered independent nodes in attachment with the wireless sensors to sense and retain various physical and environmental states from the atmosphere. The batteries, attached to these sensors, are outfitted with limited power and limited storage space capabilities. Hence, it is very essential to make energy stability in the wireless network for making efficient data transmission for performance enhancement in the system. Thus, to enhance network performance, energy-balancing techniques are required to provide a link with efficiently routing the data in the network with minimum power expenditure. Hence, the clustering is one of the best ways to balance the overall energy. Furthermore, the cluster head can further improve the network performance by the properly maintained status of the energy and buffer. The existing algorithm selects the head node of the cluster based on remaining power status only. Conversely, they root the cluster-head to become a bottleneck node and make to drop the packets due to insufficient buffer. Therefore, it is very essential to maintain these parameters to improve network performance. Hence, we propose a new efficient metric for choosing the head node known as “Cluster Head Selection Based on Energy and Buffer Residual Status” to increase the network performance. This work provides the residual status of the head node based on the available power as well as the buffer status. The calculations are done by the well-known algorithm (Knapsack). The performance is examined by the network simulator with the NS2.34/2.35 version. The outcome shows that the proposed work performs well in contrast with the existing works in WSNs.
Keywords: Energy-Efficiency, Network Performance, Wireless Sensor Network, Routing, Residual Status, Cluster-Head, Buffer.