Abstract
Communication between mobile nodes is the key purpose of Mobile Ad Hoc Networks (MANETs). However, increase in the traffic leads to multiple challenging issues like congestion among nodes, consumption of more bandwidth, high energy requirement and low efficiency output. A powerful solution to these issues of the MANET is to use intelligent routing protocols. The Adaptive Neural Fuzzy Inference System (ANFIS) is one of those advanced technique which adjust itself according to the change in system. Therefore, the use of ANFIS in routing protocol results in efficient guiding of packet from source to destination. In this paper, the route selection mechanism of traditional Ad Hoc on Demand Distance Vector (AODV) routing protocol is improved with the use of ANFIS having input attributes hop count, energy consumption and delay. Simulation of the proposed ANFIS Aided AODV (AAODV) shows the clear improvement in quantitative parameters like Throughput and Packet Delivery Ratio (PDR).
Highlights
Mobile ad hoc networks have the characteristics of less infrastructure, mobility, dynamic topology and the ability to communicate with each other even though they are not directly in the range
Route a-g-l-m-n-k is recommended by the traditional Ad Hoc on Demand Distance Vector (AODV) routing algorithm because it has the least hop count but the system decides to take route a-b-h-i-j-n-k due to minimum total cost
The results have demonstrated some important characteristic of Adaptive Neural Fuzzy Inference System (ANFIS) based AODV routing protocol
Summary
Mobile ad hoc networks have the characteristics of less infrastructure, mobility, dynamic topology and the ability to communicate with each other even though they are not directly in the range. Due to these characteristics, MANETs have gained tremendous attention of researchers from the last decade. With the increase in mobile users, the demand of wireless applications has significantly increased. To meet these requirements, canon of routing protocols have been already developed (Murthy and Manoj, 2004; Sharma and Alam, 2012). The hybrid protocols are the combination of on demand as well as table driven protocols
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