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Swarm-Intelligence-Centric Routing Algorithm for Wireless Sensor Networks

机译:无线传感器网络的群体智能路由算法

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摘要

The swarm intelligence (SI)-based bio-inspired algorithm demonstrates features of heterogeneous individual agents, such as stability, scalability, and adaptability, in distributed and autonomous environments. The said algorithm will be applied to the communication network environment to overcome the limitations of wireless sensor networks (WSNs). Herein, the swarm-intelligence-centric routing algorithm (SICROA) is presented for use in WSNs that aim to leverage the advantages of the ant colony optimization (ACO) algorithm. The proposed routing protocol addresses the problems of the ad hoc on-demand distance vector (AODV) and improves routing performance via collision avoidance, link-quality prediction, and maintenance methods. The proposed method was found to improve network performance by replacing the periodic “Hello” message with an interrupt that facilitates the prediction and detection of link disconnections. Consequently, the overall network performance can be further improved by prescribing appropriate procedures for processing each control message. Therefore, it is inferred that the proposed SI-based approach provides an optimal solution to problems encountered in a complex environment, while operating in a distributed manner and adhering to simple rules of behavior.
机译:基于群体的BIO-Inspired算法,展示了异质个体代理的特征,例如稳定性,可扩展性和适应性,在分布式和自主环境中。所述算法将应用于通信网络环境以克服无线传感器网络(WSN)的局限性。这里,展示了群智能的路由算法(SicroA)以用于WSN,其目的是利用蚁群优化(ACO)算法的优点。所提出的路由协议解决了临时按需距离向量(AODV)的问题,并通过碰撞避免,链路质量预测和维护方法来提高路由性能。发现该方法通过用中断替换周期性的“Hello”消息来提高网络性能,从而促进链接断开的预测和检测。因此,通过规定用于处理每个控制消息的适当程序,可以进一步提高整体网络性能。因此,推断推出的基于SI的方法提供了在复杂环境中遇到的问题的最佳解决方案,同时以分布式方式操作并遵守简单的行为规则。

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