Harnessing the Potential of Function-Reuse in Multimedia Cloud Systems

TL;DR

This paper introduces a task reusing paradigm for multimedia cloud systems that enhances QoS and reduces costs by intelligently aggregating similar waiting tasks, especially in serverless environments.

Contribution

It proposes a novel mechanism for identifying and merging similar tasks to improve performance and cost-efficiency in multimedia cloud processing.

Findings

QoS improved by significantly reducing missed deadlines

Overall cloud service utilization time reduced by over 9%

Effective task aggregation mechanism demonstrated

Abstract

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%.