Efficient management of idleness in storage systems

Abstract

Various activities that intend to enhance performance, reliability, and availability of storage systems are scheduled with low priority and served during idle times. Under such conditions, idleness becomes a valuable “resource” that needs to be efficiently managed. A common approach in system design is to be nonwork conserving by “idle waiting”, that is, delay the scheduling of background jobs to avoid slowing down upcoming foreground tasks. In this article, we complement “idle waiting” with the “estimation” of background work to be served in every idle interval to effectively manage the trade-off between the performance of foreground and background tasks. As a result, the storage system is better utilized without compromising foreground performance. Our analysis shows that if idle times have low variability, then idle waiting is not necessary. Only if idle times are highly variable does idle waiting become necessary to minimize the impact of background activity on foreground performance. We further show that if there is burstiness in idle intervals, then it is possible to predict accurately the length of incoming idle intervals and use this information to serve more background jobs without affecting foreground performance.