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Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems
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AI
DOI：10.1016/j.jpdc.2012.02.014.png)
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Abstract
En 中文
Resource management remains one of the main issues of cloud computing providers because system resources have to be continuously allocated to handle workload fluctuations while guaranteeing Service Level Agreements (SLA) to the end users. In this paper, we propose novel capacity allocation algorithms able to coordinate multiple distributed resource controllers operating in geographically distributed cloud sites. Capacity allocation solutions are integrated with a load redirection mechanism which, when necessary, distributes incoming requests among different sites. The overall goal is to minimize the costs of allocated resources in terms of virtual machines, while guaranteeing SLA constraints expressed as a threshold on the average response time. We propose a distributed solution which integrates workload prediction and distributed non-linear optimization techniques. Experiments show how the proposed solutions improve other heuristics proposed in literature without penalizing SLAs, and our results are close to the global optimum which can be obtained by an oracle with a perfect knowledge about the future offered load. (C) 2012 Elsevier Inc. All rights reserved.
Keywords:
Cloud systems
Performance modeling
Resource management
Capacity allocation
Load balancing
SLA
Journal
IF:
4
Papers:
3.8K
Citations:
4.8K