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

机译:卫星DTN联络计划设计演进方法的初步结果

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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:容忍延迟和中断的网络(DTN)成为一种吸引人的解决方案,用于扩展Internet边界以包含中断性通信。特别地,如果可以像在卫星网络中那样预测节点的轨迹和方向,则路由选择方案可以利用对包括即将到来的通信机会的联系计划的先验知识。但是,这种计划的设计既要考虑可用的航天器资源,又要同时考虑在空间应用中可预见的预期交通量。在这种情况下,现有的“交通感知联系计划”(TACP)程序利用了此属性,但是其理论公式的计算复杂性使实际卫星应用望而却步。因此,我们提出了CPD-EA:一种遗传算法,可以在合理的时间内提供次优但有效且可实施的联系计划。特别是,我们描述了该算法的策略,并在现实的低地球轨道(LEO)场景中评估了其初步性能,证明了其在规划未来基于DTN的卫星网络方面的有用性。

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