TY - GEN
T1 - Towards autonomic workload provisioning for enterprise grids and clouds
AU - Quiroz, Andres
AU - Kim, Hyunjoo
AU - Parashar, Manish
AU - Gnanasambandam, Nathan
AU - Sharma, Naveen
PY - 2009
Y1 - 2009
N2 - This paper explores autonomic approaches for optimizing provisioning for heterogeneous workloads on enterprise Grids and clouds. Specifically, this paper presents a decentralized, robust online clustering approach that addresses the distributed nature of these environments, and can be used to detect patterns and trends, and use this information to optimize provisioning of virtual (VM) resources. It then presents a model-based approach for estimating application service time using long-term application performance monitoring, to provide feedback about the appropriateness of requested resources as well as the system's ability to meet QoS constraints and SLAs. Specifically for high-performance computing workloads, the use of a quadratic response surface model (QRSM) is justified with respect to traditional models, demonstrating the need for application-specific modeling. The proposed approaches are evaluated using a real computing center workload trace and the results demonstrate both their effectiveness and cost-efficiency.
AB - This paper explores autonomic approaches for optimizing provisioning for heterogeneous workloads on enterprise Grids and clouds. Specifically, this paper presents a decentralized, robust online clustering approach that addresses the distributed nature of these environments, and can be used to detect patterns and trends, and use this information to optimize provisioning of virtual (VM) resources. It then presents a model-based approach for estimating application service time using long-term application performance monitoring, to provide feedback about the appropriateness of requested resources as well as the system's ability to meet QoS constraints and SLAs. Specifically for high-performance computing workloads, the use of a quadratic response surface model (QRSM) is justified with respect to traditional models, demonstrating the need for application-specific modeling. The proposed approaches are evaluated using a real computing center workload trace and the results demonstrate both their effectiveness and cost-efficiency.
UR - http://www.scopus.com/inward/record.url?scp=77749320088&partnerID=8YFLogxK
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U2 - https://doi.org/10.1109/GRID.2009.5353066
DO - https://doi.org/10.1109/GRID.2009.5353066
M3 - Conference contribution
SN - 9781424451494
T3 - Proceedings - IEEE/ACM International Workshop on Grid Computing
SP - 50
EP - 57
BT - Grid 2009 - Proceedings of the 2009 10th IEEE/ACM International Conference on Grid Computing
T2 - 2009 10th IEEE/ACM International Conference on Grid Computing, Grid 2009
Y2 - 13 October 2009 through 15 October 2009
ER -