Cloud-based computing systems can get oversubscribed due to the budget constraints of their users or limitations in certain resource types. The oversubscription can, in turn, degrade the users perceived Quality of Service (QoS). The approach we investigate to mitigate both the oversubscription and the incurred cost is based on smart reusing of the computation needed to process the service requests (i.e., tasks). We propose a reusing paradigm for the tasks that are waiting for execution. This paradigm can be particularly impactful in serverless platforms where multiple users can request similar services simultaneously. Our motivation is a multimedia streaming engine that processes the media segments in an on-demand manner. We propose a mechanism to identify various types of “mergeable” tasks and aggregate them to improve the QoS and mitigate the incurred cost. We develop novel approaches to determine when and how to perform task aggregation such that the QoS of other tasks is not affected. Evaluation results show that the proposed mechanism can improve the QoS by significantly reducing the percentage of tasks missing their deadlines and reduce the overall time (and subsequently the incurred cost) of utilizing cloud services by more than 9 percent.

中文翻译：

---

利用多媒体云系统中功能重用的潜力


由于用户的预算限制或某些资源类型的限制，基于云的计算系统可能会被超额订阅。超额订阅反过来又会降低用户感知的服务质量 (QoS)。我们研究的减轻超额订阅和产生的成本的方法是基于智能重用处理服务请求（即任务）所需的计算。我们为等待执行的任务提出了一种重用范例。这种范例在无服务器平台中特别有影响力，因为多个用户可以同时请求类似的服务。我们的动机是多媒体流引擎，以按需方式处理媒体片段。我们提出了一种机制来识别各种类型的“可合并”任务并将其聚合以提高服务质量并降低所产生的成本。我们开发了新颖的方法来确定何时以及如何执行任务聚合，以便其他任务的 QoS 不受影响。评估结果表明，所提出的机制可以通过显着降低任务错过期限的百分比来提高服务质量，并将使用云服务的总体时间（以及随后产生的成本）减少9%以上。