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 fourth category of work relies on as a measure of improving routing in terms of mobility sensitivity. @cite_9 have proposed whose basic idea is to detect link changes in a quicker way, by increasing the HELLO sending rate. Albeit interesting, such rate only assists in understanding that some nodes may be on the move, but not exactly which.
@cite_9
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This paper describes two techniques that improve throughput in an ad hoc network in the presence of nodes that agree to forward packets but fail to do so. To mitigate this problem, we propose categorizing nodes based upon their dynamically measured behavior. We use a watchdog that identifies misbehaving nodes and a pathrater that helps routing protocols avoid these nodes. Through simulation we evaluate watchdog and pathrater using packet throughput, percentage of overhead (routing) transmissions, and the accuracy of misbehaving node detection. When used together in a network with moderate mobility, the two techniques increase throughput by 17 in the presence of 40 misbehaving nodes, while increasing the percentage of overhead transmissions from the standard routing protocol's 9 to 17 . During extreme mobility, watchdog and pathrater can increase network throughput by 27 , while increasing the overhead transmissions from the standard routing protocol's 12 to 24 . A key ingredient of many current models proposed to capture the topological evolution of complex networks is the hypothesis that highly connected nodes increase their connectivity faster than their less connected peers, a phenomenon called preferential attachment. Measurements on four networks, namely the science citation network, Internet, actor collaboration and science coauthorship network indicate that the rate at which nodes acquire links depends on the node's degree, offering direct quantitative support for the presence of preferential attachment. We find that for the first two systems the attachment rate depends linearly on the node degree, while for the last two the dependence follows a sublinear power law. Lightweight link quality estimation is crucial in wireless sensor networks. Indeed, devices with limited capabilities shall trade off between consuming their resources to maintain a precise view of the neighbours' link quality and to build routes almost blindly. For instance, the Routing Protocol for Low-Power and Lossy Networks (RPL), which has been recently standardised by the IETF to enable IPv6-based sensor networks, only estimates the quality of the links used to deliver data packets. However, this solution has been demonstrated to cause periods of routing instability and reduced packet delivery rates since it estimates only the quality of utilised links. To address this issue in this work we propose a lightweight link estimation procedure that exploits Trickle-based topology maintenance techniques to simultaneously estimate link qualities and propagate routing information. Our proposed scheme has been integrated in the Contiki's RPL prototype implementation. Simulation results demonstrate that our proposal is capable of measuring the quality of the links to neighbours with small overhead, which results into better routing decisions and improved packet delivery rates. Mobile ad-hoc networks rely on the cooperation of nodes for routing and forwarding. For individual nodes there are however several advantages resulting from noncooperation, the most obvious being power saving. Nodes that act selfishly or even maliciously pose a threat to availability in mobile adhoc networks. Several approaches have been proposed to detect noncooperative nodes. In this paper, we investigate the effect of using rumors with respect to the detection time of misbehaved nodes as well as the robustness of the reputation system against wrong accusations. We propose a Bayesian approach for reputation representation, updates, and view integration. We also present a mechanism to detect and exclude potential lies. The simulation results indicate that by using this Bayesian approach, the reputation system is robust against slander while still benefitting from the speed-up in detection time provided by the use of rumors.