Mobile Ad hoc Network (MANET) is a developing area in the existing mobile environment. Its standards are defined by IETF. MANETs consists of several characteristics like dynamic topology, easy deployment and robustness which make them as a striking topic for the research community. Routing, enhancing the QoS is a challenging issue in MANETs. In this paper, one of the best proactive routing protocols ie Source Tree Adaptive Routing (STAR) protocol has been chosen. The selection of the stable configurable values in protocol will affect QoS performance. In MANETs, Time to Live (TTL) is a constant value and it has to be configured with network size accordingly. The impact of TTL value on the performance of STAR routing protocol has been analyzed. Simulation results suggest that the impact of TTL shows significant change on the performance of STAR at all network sizes with lower mobility. This paper shows that static values like TTL are not suitable for dynamic environment in protocol configuration and suggests that the TTL value should be a varied with the networksize and mobility speed accordingly to achieve better performance.

In Mobile Ad hoc Networks, routing is a challenging issue. Basically, the working routing protocols for these networks are classified in to three categories like the reactive protocols, proactive protocols and the hybrid t protocols which were the combination of above two types of protocols. Among them proactive routing protocols category is selected for the present study. In proactive routing protocols, STAR with LORA approach is chosen because it has less control overhead when compared to ORA approach and other proactive routing protocols. It works on few defacto parameter values in a dynamic MANET environment. These static values for parameters are not suitable in a dynamic environment. With reference to the IETF draft, it is a time series problem. In this paper, an effort has been made to incorporate the soft computing technique, fuzzy logic based STAR to enhance the performance of a MANET to support real time communication. The proposed Fuzzy logic approach based STAR performance is evaluated using simulation through QualNet simulator. From the results, it is observed that the Fuzzy logic based STAR provides superior performance than the defactoSTAR protocol. The comparative performance was measured using the performance metrics End-to-end delay, Jitter and throughput. A number of simulation scenarios were executed for small, medium and large size networks. From the simulation results, we conclude that Fuzzy Logic based STAR outperforms for small, medium size networks.

Ad hoc networks are the infrastructure-less networks that are easily deployable and self-configuring, with each constituent node performing like a transceiver. The nodes are free to move subjectively in Mobile ad-hoc networks (MANET). Thus, the network's wireless topology may be haphazard and may alter rapidly. The main important aspect to be handled is choosing a proper path for transmitting data in case of Link Failure (LF). The main concern of the research work is maintaining the path stability in the occurrence of LF in the network. Ant Colony Optimization (ACO) is used for optimizing the Routing Protocols (RP) such as Ad-hoc on demand Distance Vector (AODV). The Prediction of LF (PLF) mechanism is used for choosing the stable/proper path in the occurrence of node LF in the maintenance phase of distance vector RP based on Neighbour Node (NN). Hence, AODV-ACO-PLF is used for efficient transmission of data packets in the ad-hoc networks by maintaining stable path in-case of LF. The path stability is also maintained in presence of LF in the networks by choosing a different path using PLF Prediction Mechanism. The "AODV-ACO-PLF" methodology is used for finding the ideal way to communicate with the source and destination by giving better results in End-to end delay (6%), drop (5%), packet delivery ratio (7%), and energy consumption (7.5%) than existing methodology such as Path Selection Algorithm based on Hamming Distance and delay parameters (PSA-HD) and Predict Failure in AODV (PF-AODV) methodology in MANET.