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Preliminary results of an evolutionary approach towards Contact Plan design for satellite DTNs

机译:卫星DTNS接触计划设计的进化方法的初步结果

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Delay and disruption tolerant networks (DTNs) are becoming an appealing solution for extending Internet boundaries so as to embrace disruptive communications. In particular, if node trajectory and orientation can be predicted as in satellite networks, routing schemes can take advantage of the a-priori knowledge of a contact plan comprising the forthcoming communications opportunities. However, the design of such a plan need to consider both available spacecraft resources and the expected traffic which is largely foreseeable in space applications. In this context, the existing Traffic-Aware Contact Plan (TACP) procedure exploits this properties, but the computation complexity of its theoretical formulation results prohibitive for real satellite applications. As a result, we propose CPD-EA: a genetic algorithm to provide sub-optimal yet efficient and implementable contact plans in reasonable time. In particular, we describe the algorithm strategies and evaluate its preliminary performance in a realistic Low Earth Orbit (LEO) scenario demonstrating it usefulness for planning future DTN-based satellite networks.
机译:延迟和中断容忍网络(DTN)正在成为扩展互联网边界的吸引力解决方案,以便接受破坏性通信。特别地,如果可以将节点轨迹和方向预测为卫星网络中的方向,则路由方案可以利用包括即将到来的通信机会的联系计划的a-priori。然而,这种计划的设计需要考虑可用的航天器资源和预期的流量,这在很大程度上可以在太空应用中可预见。在此上下文中,现有的流量感知联系计划(TACP)程序利用此属性,但其理论配方的计算复杂性导致真实卫星应用令人望而却步。因此,我们提出了CPD-EA:遗传算法,以便在合理的时间内提供次优且有效和可实现的联系计划。特别是,我们描述了算法策略,并评估其在现实的低地球轨道(LEO)场景中的初步性能,证明了规划未来DTN的卫星网络的实用性。

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