This paper describes various computer system workloads and relates them to their underlying resource utilization. Specifically, the paper concentrates on Cloud workload characterization based upon issues,-capabilities, and technologies surrounding the categories from the multiple points of view of the various players involved in Cloud Computing. The relationship is established between the categories and key limiting underlying technologies, and the dynamic and measurable low-level metrics and measurements that are used to detect and reduce resource contention, and identify category changes during run-time. Research questions are posed on dynamic low-level measurements and a usage case example with high performance computing (HPC) clusters. The Cloud workload categories can provide a basis for common communication for various viewpoints from players, including facility managers, Cloud IT or service providers, Cloud users, consumers, IT managers, and hardware vendors. This common communication tool will facilitate better service-level agreements (SLAs), capital purchase decisions, and future computer architecture design-decisions.
|Original language||English (US)|
|Number of pages||16|
|Journal||IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India)|
|State||Published - Sep 1 2013|
- Data center
ASJC Scopus subject areas
- Electrical and Electronic Engineering