This paper is focused on a discussion of parameters and heuristics that are expected to assist multihop routing in becoming more sensitive to node mobility. We provide a discussion concerning existing and a few proposed parameters. Moreover, the work also discusses two new heuristics based on the notion of link duration. The heuristics are compared based on a meaningful set of scenarios that attain different mobility aspects.
A second category of work that tries to make routing more sensitive to node mobility relates to throughput variation measurement as a way to determine node mobility. For instance, Suyang and Evans have used the slope of change of throughput in a link vs. the link load to estimate topology changes @cite_0 . Based on history, through throughput monitoring, a decrease, according to Suyang and Evans, means that there is a true change in the physical topology. They have attributed the changes to increase in the node distance and increase in interference. Even with good attributes of avoiding interference and detecting mobility collectively, node mobility individually has attributes that have not been addressed. Nodes may exhibit movement that does not necessarily impact the route stability.
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This paper introduces a novel mobility-aware routing protocol (MARP) for mobile, cognitive ad-hoc networks. Traditional routing protocols trigger the routing updates after the nodes detect the route failure. Even if the link condition is getting worse which means the link is likely to break in the future, the nodes will still transmit the packets along the current path. MARP uses cognitive techniques to predict when the link is likely to break so that it can inform the previous hop to trigger the routing updates before the link breaks. In this way, the nodes are aware of the physical topology changes. Based on simulation results, MARP can increase overall performance of the network significantly. In mobile networks, distance variations caused by node mobility generate fluctuations in the channel gains. Such fluctuations can be treated as another type of fading besides multipath effects. In this paper, the interference statistics in mobile random networks are characterized by incorporating the distance variations of mobile nodes to the channel gain fluctuations. The mean interference is calculated at the origin and at the border of a finite mobile network. The network performance is evaluated in terms of the outage probability. Compared to a static network, the interference in a single snapshot does not change under uniform mobility models. However, random waypoint mobility increases (decreases) the interference at the origin (at the border). Furthermore, due to the correlation of the node locations, the interference and outage are temporally and spatially correlated. We quantify the temporal correlation of the interference and outage in mobile Poisson networks in terms of the correlation coefficient and conditional outage probability, respectively. The results show that it is essential that routing, MAC, and retransmission schemes need to be smart (i.e., correlation-aware) to avoid bursts of transmission failures. The capacity of ad hoc wireless networks is constrained by the mutual interference of concurrent transmissions between nodes. We study a model of an ad hoc network where n nodes communicate in random source-destination pairs. These nodes are assumed to be mobile. We examine the per-session throughput for applications with loose delay constraints, such that the topology changes over the time-scale of packet delivery. Under this assumption, the per-user throughput can increase dramatically when nodes are mobile rather than fixed. This improvement can be achieved by exploiting a form of multiuser diversity via packet relaying. Mobile ad hoc networks (MANETs) are multihop networks that are capable of establishing communication in the absence of any pre-existing infrastructure. Due to frequent node mobility and unreliable wireless links, the network is characterized by unpredictable topological changes. For more robust and reliable communications, it is important that a mobile node anticipates address changes and predicts its future routes in the network. This Chapter describes prediction-based mobility management schemes for mobile ad hoc networks. We propose a Markov model-based mobility management scheme that provides an adaptive location prediction mechanism. We used simulation method to evaluate the prediction accuracy as well as the probability of making the correct predictions. The simulation results indicated that higher order Markov models have slightly greater prediction accuracy than lower order Markov models. However, the prediction accuracy decreases with increase in the probability of random movement both for network sizes and number of hops.