Ant Colony based Routing for Mobile Ad-Hoc Networks towards Improved Quality of Services
Mobile Ad Hoc Network (MANET) is a dynamic multihop wireless network which is established by a set of mobile nodes on a
shared wireless channel. One of the major issues in MANET is routing due to the mobility of the nodes. Routing means the act
of moving information across an internet work from a source to a destination. When it comes to MANET, the complexity
increases due to various characteristics like dynamic topology, time varying QoS requirements, limited resources and energy
etc. QoS routing plays an important role for providing QoS in wireless ad hoc networks. The biggest challenge in this kind of
networks is to find a path between the communication end points satisfying user’s QoS requirement. Nature-inspired
algorithms (swarm intelligence) such as ant colony optimization (ACO) algorithms have shown to be a good technique for
developing routing algorithms for MANETs. In this paper, a new QoS algorithm for mobile ad hoc network has been proposed.
The proposed algorithm combines the idea of Ant Colony Optimization (ACO) with Optimized Link State Routing (OLSR)
protocol to identify multiple stable paths between source and destination nodes.
A mobile ad hoc network (MANET) is a decentralized group of mobile nodes which exchange information temporarily by means of wireless transmission . Since the nodes are mobile, the network topology may change rapidly and unpredictably over time. The network topology is unstructured and nodes may enter or leave at their will. A node can communicate to other nodes which are within its transmission range. This kind of network promises many advantages in terms of cost and flexibility compared to network with infrastructures.
MANETs are very suitable for a great variety of applications such as data collection, seismic activities, and medical applications. Unfortunately nodes in MANETs are limited in energy, bandwidth. These resources constraints pose a set of non trivial problems; in particular, routing and flow control. Routing in communication networks is necessary because, generally, nodes are not directly connected. The main problem solved by any routing protocol is to direct traffic from sources to destinations, but nowadays, because of increasing complexity in modern networks, routing algorithms face important challenges .
The routing function is particularly challenging in these networks because the network structure is constantly changing and the network resources are limited. This is particularly true in wireless ad hoc networks where node mobility and link failures produce constant changes in the network topology. Routing algorithms lack of adaptability to frequent topological changes, limited resources, energy availability reduces network performance. The demand for real time and quality of services (QoS) in the network has been increased as the internet expands.
The role of a QoS routing strategy is to compute paths that are suitable for different type of traffic generated by various applications while maximizing the utilizations of network resources. But the problem of finding multiconstrained paths has high computational complexity, and thus there is a need to use algorithms that address this difficulty. The major objectives of QoS routing are i) to find a path from source to destination satisfying user’s requirements ii) To optimize network resource usage and iii) To degrade the network performance when unwanted things like congestion, path breaks appear in the network .
In recent years, a large number of MANET routing algorithms have been proposed. These algorithms all deal with dynamic aspects of MANETs in their own way, using reactive or proactive behavior or a combination of both. The proposed algorithm in this paper is hybrid one. The hybrid algorithm is suitable for MANETs because it has flexibility to change according to change in the topology of the network. This is not possible with only proactive or only reactive type of routing algorithms i.e. reactive algorithms are suitable for mobile while proactive are suitable for stable network environment.