Optimized Energy Utilization in Cognitive Radio Networks with Congestion Control - Mettu.Jhansi Lakshmi (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Various real-time applications can be handled through wireless sensor networks, which consist of a wide range of sensor nodes. A novel congestion control mechanism is proposed on optimized rates for energy-efficient transmissions. To reduce energy consumption across the network, a rate-based congestion control algorithm based on cluster routing is presented. By reducing the end-to-end delay, rate control improves the network life time over a large simulation period. Clustering is initially performed using novel routing algorithms. After that, rate control is implemented using an energy optimization strategy suitable for high packet delivery ratios. Finally, packets are sent with maximum throughput using region Optimization-driven routing. The simulation is performed on the NS2 simulation platform. Finally, performances are evaluated with respect to average delay in end to end nodes, delivery ratio of packets, throughput, energy efficiency, energy consumption and reliability. Novel routing with an energy optimal algorithm (NREOA) reduces energy consumption as the network progresses and a variation of 20% compared with existing protocols.