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Proceedings of the 12th IFIP/IEEE International Symposium on Integrated Network Management, IM 2011, Dublin, Ireland, 23-27 May 2011; 01/2011
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Xiaoyun Zhu,
Donald Young,
Brian J. Watson,
Zhikui Wang,
Jerry Rolia,
Sharad Singhal,
Bret McKee,
Chris Hyser, Daniel Gmach,
Robert Gardner,
Tom Christian,
Ludmila Cherkasova
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ABSTRACT: Recent advances in hardware and software virtualization offer unprecedented management capabilities for the mapping of virtual
resources to physical resources. It is highly desirable to further create a “service hosting abstraction” that allows application
owners to focus on service level objectives (SLOs) for their applications. This calls for a resource management solution that
achieves the SLOs for many applications in response to changing data center conditions and hides the complexity from both
application owners and data center operators. In this paper, we describe an automated capacity and workload management system
that integrates multiple resource controllers at three different scopes and time scales. Simulation and experimental results
confirm that such an integrated solution ensures efficient and effective use of data center resources while reducing service
level violations for high priority applications.
Cluster Computing 02/2009; 12(1):45-57. · 0.52 Impact Factor
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Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2009, San Francisco, California, USA, September 14-18, 2009; 01/2009
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Computer Networks. 01/2009; 53:2905-2922.
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ABSTRACT: The consolidation of multiple servers and their workloads aims to minimize the number of servers needed thereby enabling the efficient use of server and power resources. At the same time, applications participating in consolidation scenarios often have specific quality of service requirements that need to be supported. To evaluate which workloads can be consolidated to which servers we employ a trace-based approach that determines a near optimal workload placement that provides specific qualities of service. However, the chosen workload placement is based on past demands that may not perfectly predict future demands. To further improve efficiency and application quality of service we apply the trace-based technique repeatedly, as a workload placement controller. We integrate the workload placement controller with a reactive controller that observes current behavior to i) migrate workloads off of overloaded servers and ii) free and shut down lightly-loaded servers. To evaluate the effectiveness of the approach, we developed a new host load emulation environment that simulates different management policies in a time effective manner. A case study involving three months of data for 138 SAP applications compares our integrated controller approach 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. We consider two typical enterprise environments: blade and server based resource pool infrastructures. The results show that the integrated controller approach outperforms the use of either controller separately for the enterprise application workloads in our study. We show the influence of the blade and server pool infrastructures on the effectiveness of the management policies.
Dependable Systems and Networks With FTCS and DCC, 2008. DSN 2008. IEEE International Conference on; 07/2008
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TWEB. 01/2008; 2.
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2007 IEEE International Conference on Web Services (ICWS 2007), July 9-13, 2007, Salt Lake City, Utah, USA; 01/2007
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Service-Oriented Computing - ICSOC 2006, 4th International Conference, Chicago, IL, USA, December 4-7, 2006, Proceedings; 01/2006
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Proceedings of the 22nd International Conference on Data Engineering, ICDE 2006, 3-8 April 2006, Atlanta, GA, USA; 01/2006
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Datenbanksysteme in Business, Technologie und Web, 11. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), Karlsruhe, 2.-4. März 2005; 01/2005
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Advanced Information Systems Engineering, 17th International Conference, CAiSE 2005, Porto, Portugal, June 13-17, 2005, Proceedings of the CAiSE'05 Workshops, Vol. 2; 01/2005
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ABSTRACT: 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.
Computer Networks.
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Xiaoyun Zhu,
Don Young,
Brian J. Watson,
Zhikui Wang,
Jerry Rolia,
Sharad Singhal,
Bret McKee,
Chris Hyser, Daniel Gmach,
Rob Gardner,
Tom Christian,
Lucy Cherkasova
[show abstract]
[hide abstract]
ABSTRACT: Recent advances in hardware and software virtualization offer unprecedented management capabilities for the mapping of virtual resources to physical resources. It is highly desirable to further create a "service hosting abstraction" that allows application owners to focus on service level objectives (SLOs) for their applications. This calls for a resource management solution that achieves the SLOs for many applications in response to changing data center conditions and hides the complexity from both application owners and data center operators. In this paper, we describe an automated capacity and workload management system that integrates multiple resource controllers at three different scopes and time scales. Simulation and experimental results confirm that such an integrated solution ensures efficient and effective use of data center resources while reducing service level violations for high priority applications.
Autonomic Computing, International Conference on.
