Mobile Ad-Hoc Networks (MANETs for short) are gaining the importance in the field of wireless communication. The promising feature of MANET is that it can be deployed immediately in demanding situations as they do not require the infrastructure or any centralized structures as compared to traditional wired and wireless networks.An intelligent system has been designed to select an optimum route for various contexts.An efficient protocol is designed to overcome the limits of route finding and link formation in MANET’s. This can be done by making use of the application of soft-computing techniques such as artificial neural networks, fuzzy logic and genetic algorithms. Traditional techniques are based on statistical techniques such as regression models and probabilistic methods.It can be seen from the simulation outcomes that the route finding time using the HYPER-NF-NET simulator which use soft computingtechniques is 20% to the routing finding time using NS-2 simulator. It is also seen from the simulation results that the HYPER-NF-NET protocol performance is better compared to AODV, DSR and OLSR routing protocols for different node population and various degree of congestion. The simulation results showcase a superiority of HYPER-NF-NET simulator over NS-2 and associated HFNET protocol over other existing protocols.

The decentralized and infrastructure less feature of Mobile Ad-hoc network (MANET) has made it a potential networking solution to be used in major applications ranging natural disaster management, vehicular communication, industrial communication etc. Though, being a dominating mobile communication system, exceedingly high network topology and mobility pattern in MANETs make it trivial to achieve Quality of Service (QoS) delivery, particularly for event-driven (mission-critical) communication. With this motivation, in this research paper a robust QoS Oriented Cross-Synch Routing Protocol for Event Driven, Mission-Critical Communication named Q-CSRPM has been developed for MANET. The proposed Q-CSRPM routing protocol exploits cross-layer routing architecture by applying network layer, MAC layer and physical layer information of IEEE 802.11 standard to perform optimal best forwarding node selection and reliable path formation. Q-CSRPM protocol performed proactive node management, service differentiation based data prioritization and resource scheduling, and dynamic buffer assessment based congestion detection at the network layer, dynamic link quality estimation and packet velocity estimation at the MAC layer, and PHY switching control at the physical layer of the protocol stack. Q-CSRPM applies dynamic link quality, congestion probability and packet velocity of a node for best forwarding node selection to form forwarding path. The node information sharing across the layers of protocol stack enables optimal BFN selection and routing control. It strengthened Q-CSRPM to exhibit 98.2% and 93% of packet delivery ratio for real time data and non-real time data respectively. A minimum of 2% deadline miss ratio was observed.