Sizing the streaming media cluster solution for a given workload

Authors:
L. Cherkasova;Wenting Tang
Affiliations:
Hewlett Packard Labs., Palo Alto, CA, USA;Hewlett Packard Labs., Palo Alto, CA, USA
Venue:
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Year:
2004

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Cited 2

R-Capriccio: a capacity planning and anomaly detection tool for enterprise services with live workloads

Proceedings of the ACM/IFIP/USENIX 2007 International Conference on Middleware
R-Capriccio: a capacity planning and anomaly detection tool for enterprise services with live workloads

MIDDLEWARE2007 Proceedings of the 8th ACM/IFIP/USENIX international conference on Middleware

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Abstract

The goal of the proposed benchmarking and capacity planning framework is to evaluate the amount of resources needed for processing a given workload while meeting the specified performance requirements. There are two essential components in our capacity planning framework: (i) the capacity measurements of different hardware and software solutions using a specially designed set of media benchmarks; and (ii) a media service workload profiler, called MediaProf, which extracts a set of quantitative and qualitative parameters characterizing the service demand. The capacity planning tool matches the requirements of the media service workload profile, SLA and configuration constraints to produce the best available cost/performance solution. In case of a multi-node configuration, the capacity planner performs a cluster sizing evaluation by taking into account the choice of load balancing solution.