CloudAlloc: a monitoring and reservation system for compute clusters

Authors:
Enrico Iori;Alkis Simitsis;Themis Palpanas;Kevin Wilkinson;Stavros Harizopoulos
Affiliations:
University of Trento, Trento, Italy;HP Labs, Palo Alto, CA, USA;University of Trento, Trento, Italy;HP Labs, Palo Alto, CA, USA;Nou Data, Palo Alto, CA, USA
Venue:
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Year:
2012

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Abstract

Cloud computing has emerged as a promising environment capable of providing flexibility, scalability, elasticity, fail-over mechanisms, high availability, and other important features to applications. Compute clusters are relatively easy to create and use, but tools to effectively share cluster resources are lacking. CloudAlloc addresses this problem and schedules workloads to cluster resources using allocation algorithms that can be easily changed according to the objectives of the enterprise. It also monitors resource utilization and thus, provides accountability for actual usage. CloudAlloc is a lightweight, flexible, easy-to-use tool for cluster resource allocation that has also proved useful as a research platform. We demonstrate its features and also discuss its allocation algorithms that minimize power usage. CloudAlloc was implemented and is in use at HP Labs.