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Traffic Modeling and Performance Analysis for Remote Sensing Satellite Networks

机译:遥感卫星网络的流量建模和性能分析

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Remote sensing satellite (RSS) plays an increasingly important role in satellite networks. Current studies have paid wide attention to system modeling and performance analysis of RSS traffic acquisition, storing and transmission processes. However, in traffic acquisition process, the transitions between the "on" state and the "off" state of the on-board sensor generally exhibit a Markovian feature. Besides, the continuous stream traffic arrives in the "on" states and no traffic arrives in the "off" states. These features have not been sufficiently investigated. Meanwhile, the idiomatic Poisson traffic models are no more accurate, which inevitably brings great challenges to precise performance analysis. Aiming at above features, we present a Markov Modulated Deterministic Process (MMDP) model to simulate the traffic acquisition process. Afterwards, according to the global coverage of relay satellites, we describe the integrated traffic acquisition, storing and transmission processes as an MMDP/D/1/K queueing model. Further, we derive the closed-form expressions of some important quality of service indices (i.e., the loss probability, the average queue length and the average delay). Finally, we conduct numerous simulations to verify the effectiveness of theoretical results.
机译:遥感卫星(RSS)在卫星网络中扮演着越来越重要的角色。当前的研究已广泛关注RSS流量获取,存储和传输过程的系统建模和性能分析。但是,在交通量获取过程中,车载传感器的“开启”状态和“关闭”状态之间的过渡通常表现出马尔可夫特征。此外,连续流流量到达“开”状态,没有流量到达“关”状态。这些特征尚未得到充分研究。同时,惯用的Poisson交通模型不再准确,这不可避免地给精确的性能分析带来了巨大的挑战。针对以上特征,我们提出了一种马尔可夫调制确定过程(MMDP)模型来模拟交通量获取过程。然后,根据中继卫星的全球覆盖范围,我们将集成的流量获取,存储和传输过程描述为MMDP / D / 1 / K排队模型。此外,我们导出了一些重要的服务质量指标(即丢失概率,平均队列长度和平均延迟)的闭式表达式。最后,我们进行了大量模拟以验证理论结果的有效性。

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