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 %. In addition, it can and reduce the overall time (and subsequently the incurred cost) of utilizing cloud services by more than 9%.
翻译: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由于用户的预算限制或某些资源类型的限制而过多地订阅。 过度订阅反过来又会降低用户对服务质量的认识。 我们调查的减轻超额订阅和产生成本的方法是基于明智地重新使用处理服务请求所需的计算方法(即任务)。 我们建议对等待执行的任务重新使用一种模式。这种模式在服务器上的无服务器平台中特别具有影响,因为多用户可以同时请求类似的服务。 我们的动机是多媒体流动引擎,按需处理媒体部分。我们建议一种机制,确定各种“可合并”的任务,并汇总这些任务,以改进QOS,并降低产生的成本。我们制定了新的方法,以确定何时和如何执行任务组合,使其他任务的QOS不受影响。评价结果表明,拟议的机制可以大大降低任务缺失的百分比,从而改进QOS。此外,它还可以减少使用云服务的总体时间(以及随后产生的成本),而不是9。