Fuzzy neural network for dynamic load balancing of nodes for ad hoc network using

Abstract EN

In ad hoc network, many traffic types reach continually with different rates and with different times.

There are three cases of rates (low, medium and high) which depending on the capacity of links.

The performance of ad hoc network is reducing when an imbalance load of traffic occurs among the links or nodes.

There is a necessary thing to use a technique to provide load balancing between the nodes (or links) of network that leading to destination node for the arrival traffic rates, so as to avoid exceeding the traffic rates on the viability of nodes (or links).

In this paper, a system based on fuzzy neural networks (FNNs) is proposed for solving the load balancing problem in the Ad hoc networks to achieve dynamic load balancing is facing continuous changes in the network.

The proposed fuzzy neural system (FNS) is located at each point in the network to make load balancing for nodes using two fuzzy neural networks, firstly,FNN1 based on two measurements which are queue length, which permitqueue size to classify queue state ( Under–full …….

Over– full).

Secondly, FNN2 used queue state that represented output of the FNN1, while the other is throughput for node and the output is load for this node.

The Gaussian member ship function is used with back propagation algorithm for training the NN.