Patience-aware Scheduling for Cloud Services: Freeing Users from the Chains of Boredom

TL;DR

This paper proposes patience-aware scheduling strategies for cloud services that prioritize requests based on user patience levels, improving user experience during peak loads compared to traditional FIFO methods.

Contribution

It introduces novel scheduling algorithms that account for user patience, demonstrating improved performance under peak load conditions through analytical and computational evaluation.

Findings

Patience-aware scheduling enhances user experience during peak loads.

The new algorithms outperform FIFO in response time management.

User patience significantly influences scheduling effectiveness.

Abstract

Scheduling of service requests in Cloud computing has traditionally focused on the reduction of pre-service wait, generally termed as waiting time. Under certain conditions such as peak load, however, it is not always possible to give reasonable response times to all users. This work explores the fact that different users may have their own levels of tolerance or patience with response delays. We introduce scheduling strategies that produce better assignment plans by prioritising requests from users who expect to receive the results earlier and by postponing servicing jobs from those who are more tolerant to response delays. Our analytical results show that the behaviour of users' patience plays a key role in the evaluation of scheduling techniques, and our computational evaluation demonstrates that, under peak load, the new algorithms typically provide better user experience than the traditional FIFO strategy.