Traffic locality oriented route discovery algorithms for mobile ad hoc networks

There has been a growing interest in Mobile Ad hoc Networks (MANETs) motivated by the advances in wireless technology and the range of potential applications that might be realised with such technology. Due to the lack of an infrastructure and their dynamic nature, MANETs demand a new set of networking protocols to harness the full benefits of these versatile communication systems. Great deals of research activities have been devoted to develop on-demand routing algorithms for MANETs. The route discovery processes used in most on-demand routing algorithms, such as the Dynamic Source Routing (DSR) and Ad hoc On-demand Distance Vector (AODV), rely on simple flooding as a broadcasting technique for route discovery. Although simple flooding is simple to implement, it dominates the routing overhead, leading to the well-known broadcast storm problem that results in packet congestion and excessive collisions. A number of routing techniques have been proposed to alleviate this problem, some of which aim to improve the route discovery process by restricting the broadcast of route request packets to only the essential part of the network. Ideally, a route discovery should stop when a receiving node reports a route to the required destination. However, this cannot be achieved efficiently without the use of external resources; such as GPS location devices. In this thesis, a new locality-oriented route discovery approach is proposed and exploited to develop three new algorithms to improve the route discovery process in on-demand routing protocols. The proposal of our algorithms is motivated by the fact that various patterns of traffic locality occur quite naturally in MANETs since groups of nodes communicate frequently with each other to accomplish common tasks. Some of these algorithms manage to reduce end-to-end delay while incurring lower routing overhead compared to some of the existing algorithms such as simple flooding used in AODV. The three algorithms are based on a revised concept of traffic locality in MANETs which relies on identifying a dynamic zone around a source node where the zone radius depends on the distribution of the nodes with which that the source is “mostly” communicating. The traffic locality concept developed in this research form the basis of our Traffic Locality Route Discovery Approach (TLRDA) that aims to improve the routing discovery process in on-demand routing protocols. A neighbourhood region is generated for each active source node, containing “most” of its destinations, thus the whole network being divided into two non-overlapping regions, neighbourhood and beyond-neighbourhood, centred at the source node from that source node prospective. Route requests are processed normally in the neighbourhood region according to the routing algorithm used. However, outside this region various measures are taken to impede such broadcasts and, ultimately, stop them when they have outlived their usefulness. The approach is adaptive where the boundary of each source node’s neighbourhood is continuously updated to reflect the communication behaviour of the source node. TLRDA is the basis for the new three route discovery algorithms; notably: Traffic Locality Route Discovery Algorithm with Delay (TLRDA D), Traffic Locality Route Discovery Algorithm with Chase (TLRDA-C), and Traffic Locality Expanding Ring Search (TL-ERS). In TLRDA-D, any route request that is currently travelling in its source node’s beyond-neighbourhood region is deliberately delayed to give priority to unfulfilled route requests. In TLRDA-C, this approach is augmented by using chase packets to target the route requests associated with them after the requested route has been discovered. In TL-ERS, the search is conducted by covering three successive rings. The first ring covers the source node neighbourhood region and unsatisfied route requests in this ring trigger the generation of the second ring which is double that of the first. Otherwise, the third ring covers the whole network and the algorithm finally resorts to flooding. Detailed performance evaluations are provided using both mathematical and simulation modelling to investigate the performance behaviour of the TLRDA D, TLRDA-C, and TL-ERS algorithms and demonstrate their relative effectiveness against the existing approaches. Our results reveal that TLRDA D and TLRDA C manage to minimize end-to-end packet delays while TLRDA-C and TL-ERS exhibit low routing overhead. Moreover, the results indicate that equipping AODV with our new route discovery algorithms greatly enhance the performance of AODV in terms of end to end delay, routing overhead, and packet loss.