This paper proposes a Random early detection algorithm based on fuzzy logic Principles. The main target of using the fuzzy logic is to reduce the number of lost packets which are sent by a sender using RED algorithm in queue-buffer router of the network topology. The function of fuzzy logic is to dynamically tune the maximum drop probability (max p ) parameter of the RED algorithm. To realize this target, a twoinput-single-output fuzzy logic is implemented. The inputs of the fuzzy logic are average queue size, the difference in average queue size. To estimate the performance of the FLRED: simple network topology with FTP is suggested. In this research, the opnet modeler 14.5 has been used. The simulation results show that the FLRED algorithm is better than traditional RED algorithm as far as the number of lost packets is concerned. KeywordsActive queue management (AQM), Congestion Control , Fuzzy logic Random early detection (FLRED) , Random early detection algorithm (RED).

ZigBee is widely used wireless network in Internet of Things (IoT) applications to remotely sensor and automation due to its unique characteristics compared to other wireless networks. According to ZigBee classification of IEEE 802.15.4 standard, the network consists of four layers. The ZigBee topology is represented in second layer, which is the network and security layer. Furthermore, the ZigBee topology consists of three topologies, star, tree and mesh. Also there are many transmission bands allowed in physical layer, such as 2.4 GHz, 915 MHz, 868 MHz, … etc. The study use Riverbed Modeler to evaluates the effect of ZigBee different topologies on different transmission bands regarding the performance of throughput and end to end delay. The results of the study show which topology should be used at each transmission band to obtain maximum throughput or provides lowest end to end delay, which is case sensitive in some IoT applications that required for example minimum delay.