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Mobile Adhoc Network(MANET) Routing Protocols
The specific challenges and possible applications of MANETs have made this a very popular research area, and a lot of routing algorithms have been proposed. People traditionally classify these algorithms as either proactive or reactive. In purely proactive protocols (e.g., DSDV ) nodes try to maintain at all times routes to all other nodes. This means that they need to keep track of all topology changes, which can become difficult if there are a lot of nodes or if they are very mobile. Therefore, reactive protocols (e.g., AODV or DSR ) are in general more scalable . In these protocols, nodes only gather routing information on demand: only when they have data for a certain destination they construct a path, and only when the path becomes infeasible they search a new path. In this way they greatly reduce the routing overhead, but they can suffer from oscillations in performance since they are never prepared for disruptive events. Hybrid algorithms like ZRP have both a proactive and a reactive component, in order to try to combine the best of both worlds. Most of the algorithms are single path: at any time, they use only one path between source and destination. Multipath routing offers an interesting alternative in terms of link failure robustness and load balancing. Some algorithms create multiple paths at path setup time, and use the best of these until it fails, after which they switch to the second best and so on (e.g., AODV-BR ). A problem with this way of working is that alternative paths are often infeasible by the time they need to be used. Moreover, when only the best path is used, one looses the opportunity to spread data packets over the different paths, a practice which can improve the network throughput.
The first ant-based routing algorithms were ABC and AntNet . Both algorithms follow a similar general strategy. Nodes send ant agents out at regular intervals to randomly chosen destinations. The main aim of the ants is to sample the paths, assign a quality to them, and use this information to update the routing tables in the nodes they pass. These routing tables contain an entry for each destination and each neighbor, indicating the goodness of going over this neighbor on the way to the destination. This goodness value is called pheromone. This pheromone information is used for the routing of both ants and data packets: all packets are routed stochastically, choosing with a higher probability those links with higher pheromone values. If enough ants are sent to the different destinations, nodes keep up-to-date information about the best paths, and automatically adapt their data load spreading to this. Ant-based routing algorithms have a number of properties which are desirable in MANETs: they are highly adaptive to network changes, use active path sampling, are robust to agent failures, provide multipath routing, and take care of data load spreading. However, the fact that they crucially rely on repeated path sampling can cause significant overhead if not dealt with carefully.There have been a number of attempts to design ant-based routing algorithms for MANETs. Examples are ARA and PERA . However, these algorithms loose much of the proactive sampling and exploratory behavior of the original ant-based algorithms in their attempt to limit the overhead caused by the ants.
There are four multi-hop wireless ad hoc network routing protocols that cover a range of design choices : Destination-Sequenced Distance-Vector (DSDV),Dynamic Source Routing (DSR),Ad Hoc On-Demand Distance Vector Routing (AODV).While DSDV is a table-driven routing protocol, DSR, AODV, fall under the On-demand routing protocols category.Our New Approach is a hybrid multipath algorithm, designed along the principles of ACO routing . It consists of both reactive and proactive components. It gains the advantages of both proactive and reactive routing algorithms.i)Route Discovery– Reactive Low routing overheads,ii) Route Maintenance -- Proactive Dynamic path maintenance,iii) Ant Colony Optimization- Small Ant , converge to best path quickly.iv) Multi Path Routing--Congestion control and load balancing.It does not maintain paths to all destinations at all times (like the ACO algorithms for wired networks), but sets up paths when they are needed at the start of a session. This is done in a reactive path setup phase, where Ant agents called reactive forward Ants are launched by the source in order to find multiple paths to the destination, and backward Ants return to set up the paths. The paths are represented in pheromone tables indicating their respective quality. After path setup, data packets are routed stochastically as datagram’s over the different paths using these pheromone tables. While a data session is going on, the paths are probed, maintained and improved proactively using different agents, called proactive forward Ants. The algorithm reacts to link failures with either local path repair or by warning preceding nodes on the paths.
