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IEEE Transactions on Software Engineering
The limited performance benefits of migrating active processes for load sharing
SIGMETRICS '88 Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Adaptation in natural and artificial systems
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SustainIT'10 Proceedings of the First USENIX conference on Sustainable information technology
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Efficient resource management for virtual desktop cloud computing
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Transforming reactive auto-scaling into proactive auto-scaling
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Automatic virtual machine clustering based on bhattacharyya distance for multi-cloud systems
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IBM Journal of Research and Development
Resource virtualization methodology for on-demand allocation in cloud computing systems
Service Oriented Computing and Applications
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The consolidation of multiple workloads and servers enables the efficient use of server and power resources in shared resource pools. We employ a trace-based workload placement controller that uses historical information to periodically and proactively reassign workloads to servers subject to their quality of service objectives. A reactive migration controller is introduced that detects server overload and underload conditions. It initiates the migration of workloads when the demand for resources exceeds supply. Furthermore, it dynamically adds and removes servers to maintain a balance of supply and demand for capacity while minimizing power usage. A host load simulation environment is used to evaluate several different management policies for the controllers in a time effective manner. A case study involving three months of data for 138 SAP applications compares three integrated controller approaches with the use of each controller separately. The study considers trade-offs between: (i) required capacity and power usage, (ii) resource access quality of service for CPU and memory resources, and (iii) the number of migrations. Our study sheds light on the question of whether a reactive controller or proactive workload placement controller alone is adequate for resource pool management. The results show that the most tightly integrated controller approach offers the best results in terms of capacity and quality but requires more migrations per hour than the other strategies.