A NEURO-FUZZY MODEL FOR INTELLIGENT LAST MILE ROUTING

In recent times, routing packets from source to destination has become crucial and more traffic control mechanisms are used to determine the best effort services on the network. These strategies when employed help to ensure a reduction in link latency and packet loss rate as well as optimal route selection for packet transmission. In this project, a novel algorithm based on neuro-fuzzy logic is proposed to handle routing intelligently. The proposed algorithm selects the optimal route for the transmission of packets by taking into consideration quality of service (QoS), and quality of experience (QoE), and the rate of packet transfer. From the results obtained, the neuro-fuzzy algorithm had an average end-to-end delay time of 0.545s