Throughput and End-to-End Delay Comparison in Wireless Sensor Network using BPR

Any network should have the ability to operate in harsh environments despite of the constraints taken in WSN. One of the basic features of any sensor network is to monitor and sense the surrounding for communication between them but because of their limited capabilities, sensor nodes are susceptible to various sources of failures such as presence of anomalies, malware attacks, hardware failures and software corruption which can reduce nodes functionality and badly affect most WSN operations. The existing system methods like (BOUND HOLE and GAR)can be used to diminish these issues but their performance is bounded by some restriction, the solution is to BY-PASS the infected node dynamically using twin rolling balls technique. The identification of the infected node is done by the adopting the fuzzy data clustering approach which classify the node based on the anomaly detection with the help of threshold values. The BPR algorithm bypasses the infected node to reach the destination, increasing the performance of the network. The twin rolling ball concept is used to get the idea of stuck packets in the network. Thus, BPR provides better performance in terms of QoS parameters that is throughput, end-to-end delay and energy consumption as compared to existing system.