Enacting SLAs in clouds using rules
Euro-Par'11 Proceedings of the 17th international conference on Parallel processing - Volume Part I
Auto-scaling to minimize cost and meet application deadlines in cloud workflows
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Energy-efficient and SLA-aware management of IaaS clouds
Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet
Cooperative dynamic scheduling of virtual machines in distributed systems
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing - Volume 2
Self-managing SLA compliance in cloud architectures: a market-based approach
Proceedings of the 3rd international ACM SIGSOFT symposium on Architecting Critical Systems
Optimal resource provisioning for cloud computing environment
The Journal of Supercomputing
Adaptive resource configuration for Cloud infrastructure management
Future Generation Computer Systems
Towards an agent-based symbiotic architecture for autonomic management of virtualized data centers
Proceedings of the Winter Simulation Conference
Tight bounds for online vector bin packing
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
Dynamic resource allocation with management objectives: implementation for an OpenStack cloud
Proceedings of the 8th International Conference on Network and Service Management
The Journal of Supercomputing
Scheduling highly available applications on cloud environments
Future Generation Computer Systems
Multi-Layer Resource Management in Cloud Computing
Journal of Network and Systems Management
The analysis of service provider-user coordination for resource allocation in cloud computing
Information-Knowledge-Systems Management
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In computing clouds, it is desirable to avoid wasting resources as a result of under-utilization and to avoid lengthy response times as a result of over-utilization. In this paper, we propose a new approach for dynamic autonomous resource management in computing clouds. The main contribution of this work is two-fold. First, we adopt a distributed architecture where resource management is decomposed into independent tasks, each of which is performed by Autonomous Node Agents that are tightly coupled with the physical machines in a data center. Second, the Autonomous Node Agents carry out configurations in parallel through Multiple Criteria Decision Analysis using the PROMETHEE method. Simulation results show that the proposed approach is promising in terms of scalability, feasibility and flexibility.