Age-optimal Sampling and Transmission Scheduling in Multi-Source Systems
Age-optimal Sampling and Transmission Scheduling in Multi-Source Systems
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DOI：
10.1145/3323679.3326510
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发表时间：
2018-12
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影响因子：
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通讯作者：
A. Bedewy;Yin Sun;S. Kompella;N. Shroff
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文献类型：
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作者：
A. Bedewy;Yin Sun;S. Kompella;N. Shroff
在本文中，我们考虑了多源系统中最小化信息年龄的问题，其中样本从多个源获取并通过具有随机延迟的信道发送到目的地。由于干扰，一次只能调度一个源。我们考虑的问题，找到一个决策政策，确定采样时间和传输顺序的来源，以最小化总平均峰值年龄（TaPA）和总平均年龄（TaA）的来源。我们的调查这个问题的结果在一个重要的分离原则：最优调度策略和最优采样策略是相互独立的。特别是，我们证明，对于任何给定的采样策略，最大年龄优先（MAF）调度策略提供了最好的年龄性能之间的所有调度策略。这将我们的整体优化问题转化为最优采样问题，给定的决策策略遵循MAF调度策略。虽然零等待采样策略（其中一旦信道空闲就生成样本）被证明是最佳的，可以最大限度地减少TaPA，但它并不总是最小化TaA。我们使用动态规划（DP）研究最佳抽样问题，以最小化的TaA。最后，我们提供了一个近似分析的Bellman方程近似的TA-最优采样策略的注水解决方案，这是非常接近最优的，通过数值计算。
In this paper, we consider the problem of minimizing the age of information in a multi-source system, where samples are taken from multiple sources and sent to a destination via a channel with random delay. Due to interference, only one source can be scheduled at a time. We consider the problem of finding a decision policy that determines the sampling times and transmission order of the sources for minimizing the total average peak age (TaPA) and the total average age (TaA) of the sources. Our investigation of this problem results in an important separation principle: The optimal scheduling strategy and the optimal sampling strategy are independent of each other. In particular, we prove that, for any given sampling strategy, the Maximum Age First (MAF) scheduling strategy provides the best age performance among all scheduling strategies. This transforms our overall optimization problem into an optimal sampling problem, given that the decision policy follows the MAF scheduling strategy. While the zero-wait sampling strategy (in which a sample is generated once the channel becomes idle) is shown to be optimal for minimizing the TaPA, it does not always minimize the TaA. We use Dynamic Programming (DP) to investigate the optimal sampling problem for minimizing the TaA. Finally, we provide an approximate analysis of Bellman's equation to approximate the TaA-optimal sampling strategy by a water-filling solution which is shown to be very close to optimal through numerical evaluations.