Congestion Control in 6LoWPAN Networks using Fuzzy Logic (FLCC)

Internet of Things(IoT) has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing ubiquity of radio frequency identification and wireless and mobile sensor networks. IPv6 over low power wireless personal area network (6LoWPAN) is considered as one of the most prominent protocol suite for the IoT. In this network, heavy network traffic causes congestion. This in turn downgrades the network performance. In this paper, a fuzzy logic based approach has been proposed by considering parameters like buffer occupancy, queue length, packet priority, packet size and transmission rate to detect and control congestion in 6LoWPAN networks. The performance of the proposed FLCC technique is evaluated in terms of packet loss rate, node energy consumption, and end-to-end delay. The obtained results are compared with the existing game theoretic framework (GTCCF). The proposed FLCC system outperforms existing GTCCF in terms of packet loss rate, node energy consumption and end-to-end delay.