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- W4213155832 abstract "This paper devises a routing method for providing multipath routing in an IoT network. Here the fractional artificial bee colony(FABC) algorithm is devised for initiating the 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 involve 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 are 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 of0.185J minimal delay of 0.765 sec maximum throughput of 47.690% and maximum network lifetime of 98.7%." @default.
- W4213155832 created "2022-02-24" @default.
- W4213155832 creator A5001306656 @default.
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- W4213155832 date "2021-12-16" @default.
- W4213155832 modified "2023-09-26" @default.
- W4213155832 title "Adaptive-Sunflower-Based Grey Wolf Algorithm for Multipath Routing in IoT Networks" @default.
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- W4213155832 doi "https://doi.org/10.4018/ijbdcn.286699" @default.
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