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Mobility-aware routing in delay tolerant networks

机译:延迟容忍网络中的移动感知路由

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Delay tolerant networks (DTNs) make use of opportunistic encounters of nodes for communication. The characteristics of high mobility of nodes, frequent link variation and long communication delays in DTNs result in an absence of an instantaneous end-to-end path from any source to a destination, making routing a challenge in DTNs. To deal with this issue, a lot of routing schemes have been proposed, in which future contacts of nodes are predicted based on node mobility traces and contact information. However, the previous works did not consider the spatial information of nodes, such as dwelling time at a location, and the transitivity of contacts in the prediction process of future encounter opportunities of nodes. In this paper, a novel mobility prediction-based routing (MPR) scheme is proposed for DTNs, in which the spatial information of nodes and contact transitivity are both taken into account. Specifically, a time-homogeneous semi-Markov process model is proposed to describe node mobility. By employing the semi-Markov model, we formulate the probability of a node destined to an area subject to the remaining time period constraint. The simulation results show that the proposed MPR scheme substantially improves delivery ratio and reduces delivery latency compared with traditional DTN routing schemes.
机译:时延容忍网络(DTN)利用节点的机会相遇进行通信。节点的高移动性,频繁的链路变化以及DTN中较长的通信延迟的特性导致从任何源到目的地都没有即时的端到端路径,这使得路由成为DTN中的挑战。为了解决这个问题,已经提出了许多路由方案,其中基于节点移动性轨迹和联系信息来预测节点的未来联系。但是,先前的工作没有考虑节点的空间信息,例如某个位置的停留时间,以及在节点未来的预测过程中接触的传递性。本文提出了一种新的基于DTN的基于移动性预测的路由(MPR)方案,该方案同时考虑了节点的空间信息和联系传递性。具体来说,提出了一种时间均匀的半马尔可夫过程模型来描述节点的移动性。通过使用半马尔可夫模型,我们制定了以剩余时间段约束为目标的目标区域的概率。仿真结果表明,与传统的DTN路由方案相比,所提出的MPR方案显着提高了传递比率,并减少了传递延迟。

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