Design and Implementation of Energy Efficient Reliable Sectoring Scheme for Reliability Prediction in Wireless Sensor Network
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Abstract
The Wireless Sensor Network (WSN) works efficiently once sensing the physical phenomenon, aggregation of data, and transmitting it to the end-user performs well. It directly reflects on the performance of the network along-with the quality of service
newline(QoS) values. A perilous limitation of WSN is that the sensor nodes work with batteries. Its main operational feasibility concerns that energy resource constraints. To maintain a better lifespan of the sensor network, the energy level of a sensor node needs to be use properly. One of the solutions is to group sensor nodes by considering the distance for communication as less as possible. The key focus of the research is to perform partitioning of sensor networks into sectors to use the energy of the node efficiently. Firstly, the innovative Energy-Efficient Reliable Sectoring Scheme (EERSS) is proposed to a performed grouping of sensor nodes into various sectors. According to the literature survey, the existing clustering schemes face the limitations of an unbalanced distribution of node density into a cluster, the distance between cluster head (CH) to sink node while the election of CH, redundant data transmission in each iteration, and high transmission delay. To overcome these issues an EERSS is proposed. The election of SH is performed by considering the threshold-based energy level of the node, Receiving Signal Strength Identification (RSSI) value of each node, a hop away distance between the SH and SN, node coverage by SH, and broadcast initiated with path discovery(PD)and path selection (PS) in the routing table. The performance of the proposed EERSS is implemented and compared with Low-Energy Adaptive Clustering Hierarchy protocol (LEACH), Power-Efficient Gathering in Sensor Information System (PEGASIS), Concentric Clustering Scheme (CCS), and Track Sector Clustering (TSC), with implementations in NS-2. Simulation results are weightiness of the EERSS algorithm provides