Resource Prediction using Wavelet Neural Network in Mobile Ad-hoc Networks

Many multimedia applications over Mobile Ad hoc NETworks (MANETs) require Quality of Service (QoS) to meet real-time services. Resource prediction, resource allocation and quality prediction are important component for QoS provisioning which is affected by many factors such as latency, bandwidth, reliability, packet-loss, memory size, buffer cache, available capacity, and CPU speed. Media Access Control (MAC) protocol is responsible for efficient usage of resources in MANET to provide QoS. In this paper, we propose a novel prediction mechanism in MANET to predict traffic, buffer-space, energy and bandwidth that is necessary for efficient resource allocation to support real-time and multimedia communication. Resource prediction mechanism is being designed with wavelet neural networks. Simulation result shows that the predicted resource closely match with the actual values.