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 of47.690%and maximum network lifetime of98.7%.
A performance of network is evaluated by considering different parameters. The network lifetime depends on many factors Residual energy, Link lifetime and Delay. The Major Challenge in IoT is to the increased lifetime of low power and lossy network (RPL).The process considering input and output to evaluate Network performance by considering the above factors. The proposed system makes use of FIS (Fuzzy Inference System) for selecting the best path to maximize network lifetime. The outcome obtained by using MATLAB and Network performance is increased. The excellent route is selected if Residual Energy is 194, Link quality is 51.2 and Delay is 1.05 then excellent route quality is 73.4%.
Multipath routing in Internet of things network using fuzzy logic approach to minimize energy consumption, End-to-End delay and ETX (Expected transmission count).Consider the three parameter as input to improve Quality of service for low power and lossy network. We propose a fuzzy Multi-Criteria decision making to select best next hop to reach destination node from multipath routing and also apply fuzzy inference system to display the outcome by applying membership function. We also give priority to the route which will help to select best path from multiple path. The high performance routing protocol is required to IoT sensor nodes that work on limited battery power which will eliminate the problem of energy constrained. This will improve network performance to increase network lifetime. The implementations in Fuzzy logic to design RPL objective function and obtained result in MATLAB tool to choose best solution
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