FTTCNF- Novel Approach for Fault Tolerant Topology Control in Manet

Abstract

In wireless networks it is observed that as nodes move unpredictably sudden link disconnections occur during transmission. This leads to frequent path changes and multiple path discoveries which subsequently increase transmission of control packets in network. The nodes in the network simply rebroadcast the received route request (RREQ) packet if they do not have the route to the required destination. In addition to this, frequent hello messages for neighbour set construction and maintenance also increase control message count in the network causing a flooding issue. In order to mitigate these problems, the proposed Fault Tolerant Topology Control Neuro Fuzzy method (FTTCNF), incorporates measures to improve the network stability and to reduce the control packets in the network. These measure 1.reduce control message transmissions among neighbours by finding a stable path 2. neighbour node distance is computed based on the reception of a signal strength Indication (RSSI), 3. path stability is decided by the link expiry time (LET) which can be used to predict the neighbour mobility deviations. These factors, ( above mentioned distance, path stability factor PSF, and LET) are subjected to the fuzzification process to identify the fuzzy rule values and are given as input to the neuron formation stage. Final neuron value is computed for all available paths and the maximum value path is chosen for data transmission. Energy level monitoring is also applied at each node to check the node’s current energy and should it go below the energy threshold level the node by itself, joining the routing process is avoided. Simulation results have proved that the proposed method significantly reduces the routing overhead and improves the stability of path during data transmission.