Performance Evaluation of Fuzzy Logic Based RPL Objective Functions
Keywords:
RPL, fuzzy logic, End-to-end delay, Power consumptionAbstract
Introduction: This paper is based on the evaluation of different fuzzy logic based approaches, implemented by Routing Protocol for Low-power Lossy networks (RPL), carried out using different topologies.
Importance: This study is carried out to find out the strengths and weaknesses of fuzzy logic based approaches in RPL for different topologies. Fuzzy logic based RPL uses multi-metric approach, i.e., a technique which uses more than one metrics for route optimization.
Methodology: Two fuzzy logic based approaches implemented by RPL are selected, and compared with the single metric techniques, for two different topologies. This comparison is carried out in a network simulator called Cooja. Four performance evaluation metrics, i.e., end to end delay, packet delivery ratio (PDR), power consumption and number of parent switches, are used for comparison.
Novelty statement: As per author’s knowledge, Evaluation of the fuzzy logic based RPL techniques for different topologies and impact of node’s relative location on its results is not carried out.
Results and Discussions: It has been shown that using fuzzy logic in RPL, increases the packet delivery ratio and decreases end-to-end delay and power consumption in some cases. However, at the same time, it increases the number of parents switched. Results also reflected that, in case, if there are small number of nodes i.e., no congestion and node is closer to the root, instead of using a complicated and time consuming fuzzy logic based approach, the originally proposed less-complex methods should be preferred, as they consume less power and also add less processing delay. Fuzzy logic shows better results when the nodes are far away from root and there is congestion; in this case, a single metric cannot decide the best route for forwarding data.
Concluding Remarks: In future work, while using fuzzy logic in RPL, a dynamic approach may improve the results by selecting an objective function according to the traffic load, number of nodes and node’s location with respect to the root.
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