Decision-Making Approaches for Performance QoS in Distributed Storage Systems: A Survey

Abstract

Distributed storage systems designed to offer explicit performance quality-of-service (QoS) guarantees must regulate the allocation and use of resources to achieve a user-specified level of service. QoS-driven systems employ decision-making techniques to decide on appropriate actions to take during initial deployment or under variations in workload and/or system configuration. In this survey we cover both traditional approaches to decision-making for explicit performance QoS (control theory, multi-dimensional constrained optimization, policy-based techniques) as well as more recent approaches based on machine-learning, offering a broad perspective to the state-of-the-art in the field. As performance prediction is a central concept in decision-making, we also summarize research on performance prediction techniques used in this context.