Collaborative Load-Balancing in Storage Networks Using Agent Negotiation
CIA '08 Proceedings of the 12th international workshop on Cooperative Information Agents XII
Evolution of storage management: transforming raw data into information
IBM Journal of Research and Development
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FAST'11 Proceedings of the 9th USENIX conference on File and stroage technologies
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The designers of clustered file systems, storage resource management software and storage virtualization devices are trying to provide the necessary planning functionality in their products to facilitate the invocation of the appropriate corrective actions in order to satisfy user specified service level objectives (SLOs). However, most existing approaches only perform planning for a single type of action such as workload throttling, or data migration, or addition of new resources. As will be shown in this paper, single action based plans are not always cost effective. In this paper we present a framework SMART that considers multiple types of corrective actions in an integrated manner and generates a combined corrective action schedule. Furthermore, often times, the best cost-effective schedule for a one-week lookahead could be different from the best cost-effective schedule for a one-year lookahead. An advantage of the SMART framework is that it considers this lookahead time window in coming up with its corrective action schedules. Finally, another key advantage of this framework is that it has a built-in mechanism to handle unexpected surges in workloads. We have implemented our framework and algorithm as part of a clustered file system and performed various experiments to show the benefits of our approach.