Harnessing PSO and GA for Congestion Control in High-speed Wireless Sensor Networks

Vidhya Rathinasamy, Poonguzhali Krishnan, Geetha Ponnusamy, Murugananth Raj
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Abstract

Sensor and sink nodes create wireless sensor networks. Traffic congestion caused by WSN data transfer causes bigger packet losses, low throughput and excessive energy consumption. This work proposes a hybrid congestion management approach using genetic algorithm and particle swarm optimization. The new approach is simulated and compared to established methods. The suggested system dramatically improved performance metrics. The suggested system of interest increased to 94% detection efficiency, 91% network lifespan, 106 J energy usage, and 22 packet loss rate. The hybrid approach avoided wireless sensor network congestion and managed traffic.
利用 PSO 和 GA 实现高速无线传感器网络的拥塞控制
传感器节点和汇节点创建了无线传感器网络。WSN 数据传输造成的流量拥塞会导致较大的数据包丢失、较低的吞吐量和过多的能量消耗。本研究提出了一种使用遗传算法和粒子群优化的混合拥塞管理方法。对新方法进行了模拟,并与已有方法进行了比较。所建议的系统极大地改善了性能指标。建议的系统检测效率提高到 94%,网络寿命提高到 91%,能源使用量降低到 106 J,数据包丢失率降低到 22%。混合方法避免了无线传感器网络拥塞,并对流量进行了管理。
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