Towards the Tradeoff Between Service Performance and Information Freshness
Towards the Tradeoff Between Service Performance and Information Freshness
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DOI：
10.1109/icc.2019.8761529
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发表时间：
2019-01
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影响因子：
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通讯作者：
Zhongdong Liu;Bo Ji
中科院分区：
文献类型：
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作者：
Zhongdong Liu;Bo Ji
过去十年见证了对数据驱动的实时服务需求的空前增长。这些服务受到新兴应用的推动，这些应用需要快速注入数据流并实时（或近实时）计算更新的分析结果。在许多此类应用中，计算资源通常被共享用于处理来自信息源的更新和来自终端用户的查询。这就需要对更新和查询进行联合调度，因为服务提供商在收到用户查询时需要做出一个关键决策：要么立即用当前可用但可能过时的信息做出响应，要么首先处理新的更新，然后用更新的信息做出响应。因此，在这种情况下，服务性能（例如响应时间）和信息新鲜度之间的权衡自然就出现了。为此，我们提出了一个简单的单服务器双队列模型，该模型捕捉了更新和查询的耦合调度，并旨在设计能够妥善处理性能和新鲜度之间重要权衡的调度策略。具体而言，我们将响应时间作为性能指标，将信息年龄（AoI）作为新鲜度指标。在展示了最简单的先来先服务（FCFS）策略的局限性之后，我们提出了两种基于阈值的策略：优先处理查询的Query - k策略和优先处理更新的Update - k策略。然后，我们严格分析了基于阈值的策略的响应时间和峰值信息年龄（PAoI）。此外，我们提出了Joint - (M, N)策略，该策略通过选择两个阈值M和N的不同值，可以灵活地对更新或查询进行优先级排序。最后，我们进行模拟以评估所提出策略的响应时间和PAoI。结果表明，我们提出的基于阈值的策略能够有效地控制性能和新鲜度之间的平衡。
The last decade has witnessed an unprecedented growth in the demand for data-driven real-time services. These services are fueled by emerging applications that require rapidly injecting data streams and computing updated analytics results in real-time (or near-real-time). In many of such applications, the computing resources are often shared for processing both updates from information sources and queries from end users. This requires joint scheduling of updates and queries because the service provider needs to make a critical decision upon receiving a user query: either it responds immediately with currently available but possibly stale information, or it first processes new updates and then responds with fresher information. Hence, the tradeoff between service performance (e.g., response time) and information freshness naturally arises in this context. To that end, we propose a simple single-server two-queue model that captures the coupled scheduling of updates and queries and aim to design scheduling policies that can properly address the important tradeoff between performance and freshness. Specifically, we consider the response time as a performance metric and the Age of Information (AoI) as a freshness metric. After demonstrating the limitations of the simplest First-Come-First-Served (FCFS) policy, we propose two threshold-based policies: the Query-k policy that prioritizes queries and the Update-k policy that prioritizes updates. Then, we rigorously analyze both the response time and the Peak AoI (PAoI) of the threshold-based policies. Further, we propose the Joint-(M, N) policy, which allows flexibly prioritizing updates or queries through choosing different values of two thresholds M and N. Finally, we conduct simulations to evaluate the response time and the PAoI of the proposed policies. The results show that our proposed threshold-based policies can effectively control the balance between performance and freshness.