Bio-Inspired Quality of Service Aware Routing in Mobile Ad Hoc Networks

Abstract

In recent years a lot of work has been done in an effort to incorporate Swarm Intelligence (SI) techniques in building an adaptive routing protocols for Mobile Ad Hoc Networks (MANETs). As centralized approach for routing in MANETs lack in scalability and fault-tolerance, SI techniques provide natural solutions through distributed approach to the adaptive routing for MANETs. The mobile nodes found in MANETs are capable of monitoring the network status as well as data processing. Thus the MANETs can be made Context Aware with the help of mobile nodes local monitoring capability. In this thesis work, a novel mobility aware bio inspired routing protocol for MANETs referred to as Mobility Aware Termite (MA-Termite) is proposed by inheriting the hill building nature of social inset Termite MA-Termite will find the reliable path between the source and destination node based on the stable nodes in terms of its mobility with the help of the local monitoring capability of nodes. Further, analytical model is also proposed for studying an asymptotic pheromone behavior of MA-Termite using two different parameters (decay rate and pheromone sensitivity) over both single and double links. The results depict how individual parameters are correlated and how they affect the global performance of MANETs. The best possible parameter values are determined for optimal performance for MA-Termite. Recently, several telecommunication applications of bio-inspired algorithms achieved remarkable success. In SI techniques, the captivating features of insects or mammals are correlated with the real world problems to find solutions. The natural question is whether it is possible to develop a new hybrid algorithm by combining the distinguishing features of these insects or mammals? In this regard, the salient features of mammals such as bats are combined with the proposed MA-Termite algorithm to come up with a new hybrid routing algorithm referred to as Bat-Termite for MANETs. Bat-Termite improved the backup route maintenance and also exhibited superior routing features such as quick route discovery, high robustness with efficient management of multiple routes and rapid route repair. One of the features of both MA-Termite and Bat-Termite algorithms is they always exclusively choose the highest pheromone link thus congests the highest pheromone link over a period of time. This undesirable behavior is referred to as stagnation. Further, MA-Termite lags in load balancing and fails to take the full benefit of multipath environment. One of the methods to avoid the stagnation problem is pheromone heuristic control. Thus, a novel heuristic hybrid Load Balanced Quality of Service (QoS) aware routing protocol referred to as Load BalancedBat-Termite (LB-Bat-Termite) is proposed for MANETs in order to solve the stagnation problem of both MA-Termite and hybrid Bat-Termite algorithms. The LB-Bat-Termite algorithm with its context awareness, QoS awareness and load balancing features exhibited considerable performance gain due to load balancing. LB-Bat-Termite produces additional control packets in order to maintain all possible paths to the destination node and thus mobile nodes spends most of its time in route maintenance than data transfer; hence causes performance degradation under high node density conditions. In prder to improve the scalability and to reduce the control packet overhead, a novel heuristic Load Balanced Termite based QoS aware routing protocol is referred to as Load Balanced-Termite (LB-Termite) is proposed for MANETs. LB-Termite exhibited considerable performance gain under both scalability and mobility factors. The proposed bio-inspired QoS aware routing algorithms in this thesis work could be used for applications such as university or campus settings, data sharing during lecturing or meeting or data sharing during virtual classrooms. The proposed algorithms for MANETs in this thesis namely MA-Termite, Bat-Termite, LB-Bat-Termite and LB-Termite are compared with the state-of-the-art bio-inspired (Simple Ant Routing Algorithm and Termite Algorithm) and non bio- inspired routing algorithms (Ad Hoc On demand Distance Vector Routing algorithm) for its performance evaluation and results are encouraging in terms of QoS parameters (Throughput, Total Packet Drops, End to End Delay and Control Packet Overhead).