Resource-level QoS metric for CPU-based guarantees in cloud providers
GECON'10 Proceedings of the 7th international conference on Economics of grids, clouds, systems, and services
Adaptive Scheduling on Power-Aware Managed Data-Centers Using Machine Learning
GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing
Energy-efficient and multifaceted resource management for profit-driven virtualized data centers
Future Generation Computer Systems
Supporting CPU-based guarantees in cloud SLAs via resource-level QoS metrics
Future Generation Computer Systems
Feedback-based optimization of a private cloud
Future Generation Computer Systems
Client Classification Policies for SLA Enforcement in Shared Cloud Datacenters
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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Resource management is a key challenge that service providers must adequately face in order to ensure their profitability. This paper describes a proof-of-concept framework for facilitating resource management in service providers, which allows reducing costs and at the same time fulfilling the quality of service agreed with the customers. This is accomplished by means of virtualization. Our approach provides application-specific virtual environments and consolidates them in order to achieve a better utilization of the providers resources. In addition, it implements self-adaptive capabilities for dynamically distributing the providers resources among these virtual environments based on Service Level Agreements. The proposed solution has been implemented as a part of the Semantically-Enhanced Resource Allocator prototype developed within the BREIN European project. The evaluation shows that our prototype is able to react in very short time under changing conditions and avoid SLA violations by rescheduling efficiently the resources.