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首页> 外文期刊>International journal of business data communications and networking >Adaptive-Sunflower-Based Grey Wolf Algorithm for Multipath Routing in IoT Networks
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Adaptive-Sunflower-Based Grey Wolf Algorithm for Multipath Routing in IoT Networks

机译:基于向日葵的物联网多径路由灰狼算法

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This paper devises a routing method for providing multipath routing inan IoT network. Here the Fractional Artificial Bee colony(FABC)algorithm is devised for initiating clustering process. Moreover the multipath routing is performed by the newly devised optimization technique, namely Adaptive-Sunflower based grey wolf(Adaptive-SFG)optimization technique which is designed by incorporating adaptive idea in Sunflower based grey wolf technique. In addition the fitness function is newly devised by considering certain factors that involves Context awareness, link lifetime Energy, Trust, and Delay.For the computation of the trust, additional trust factors like direct trust indirect trust recent trust and forwarding rate factor is considered. Thus, the proposed Adaptive SFG algorithm selects the multipath for routing based on the fitness function.Finally, route maintenance is performed to ensure routing without link breakage.The proposed Adaptive-SFG outperformed other methods with high energy of0.185Jminimal delay of 0.765sec maximum throughput of47.690and maximum network lifetime of98.7.
机译:该文设计了一种在物联网网络中提供多路径路由的路由方法。这里设计了分数人工蜂群(FABC)算法来启动聚类过程。此外,通过新设计的优化技术,即基于自适应的灰狼(Adaptive-SFG)优化技术,将自适应思想融入到基于向日葵的灰狼技术中,实现了多径路由。此外,适应度函数是新设计的,考虑了某些涉及上下文感知、链接生命周期能量、信任和延迟的因素,在计算信任时,考虑了其他信任因素,如直接信任、间接信任、近期信任和转发率因素。因此,所提出的自适应SFG算法基于适应度函数选择多径进行路由。最后,进行路由维护,确保路由无链路断裂。所提出的Adaptive-SFG具有0.185J的高能量,0.765秒的最小延迟,47.690%的最大吞吐量和98.7%的最大网络寿命。

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