Routing in MANET (Mobile Ad hoc Network) is a challenging task because of the mobile nature of the nodes in a network and topology changes very often and developing effective routing protocols for MANET is also a highly challenging task. To fulfil the multiple routing requirements as low control overhead, low packet delay, high packet delivery rate and adapting effectively to network topology changes and so on, are the issues which are emerging. Amidst lots of problems which are found to be NP-hard in routing, new ways to find approximate solutions have to be investigated. A lot of attention was attracted by Swarm intelligence inspired algorithms which are based on the Ant Colony Optimization meta heuristic technique because they can offer optimized solutions ensuring low control overhead, robustness etc. and presents framework for approximating solutions to NP-hard problems. This paper includes 1) Introducing the ACO technique and its principles 2) Various ACO based routing protocols 3) summary and conclusion.

MANET is a self organizing and self configurable infrastructure less network of mobile nodes connected by wireless where the nodes move arbitrarily. Routing is a critical issue in Mobile Ad Hoc Networks. One of wellknown protocol for Ad hoc networks is Zone Routing Protocol. However, many useless control packets are used resulting in the increase of network load and decrease of network performance. This paper studies various enhancements that have been made on ZRP to improve its performance.

In Vehicular Ad hoc Networks (VANET), topology varies very frequently because vehicles move in high speed. VANET is deployed on road. In GPSR Protocol, as the data packets are forwarded depending upon on the beacon information sent by neighboring nodes, which contain the location of neighbors. Hence nodes move in mobile nature as they change their positions. Mobile pattern of node is reflected by Mobility Models, as they characterize the movement of users who are mobile on the road, with respect to their direction, velocity and location over a period of time. Mobility models are practiced in implementation of protocols and the pattern by which the mobility models reflect real world practices of vehicles on the roads. Using simple pattern randomly, graph constrained mobility models are common practices while doing research. These models donot describe mobility of vehicles in realistic manner. For instance while accelerating and decelerating in the presence of nearby vehicles, these situations greatly affect the Network performance. Selecting the mobility model which is realistic one is the main focus of this paper. To address the challenges such as high mobility of vehicle nodes on the road and random topology, VANET needs a suitable mobility model to obtain improved Packet Delivery Ratio, Throughput, End to End Delay etc. This paper first implements the GPSR Protocol and then GPSR is analyzed by applying different mobility models such as Random Way Point, Gauss Markov, Manhattan Grid, Reference Point Group and Random direction. Results are analyzed by taking the following parameters: Routing overhead, Throughput, PDR and End to End Delivery. The implementation is carried out using NS—2.35 and Bonmotion is used to create mobility models.

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