Please use this identifier to cite or link to this item:
https://idr.l3.nitk.ac.in/jspui/handle/123456789/6943
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shishira, S.R. | |
dc.contributor.author | Kandasamy, A. | |
dc.contributor.author | Chandrasekaran, K. | |
dc.date.accessioned | 2020-03-30T09:46:27Z | - |
dc.date.available | 2020-03-30T09:46:27Z | - |
dc.date.issued | 2017 | |
dc.identifier.citation | ACM International Conference Proceeding Series, 2017, Vol., , pp.151-156 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/6943 | - |
dc.description.abstract | Workload is a set of inputs given to a infrastructure for processing. Performance can be measured based on the efficient processing of the workloads. Different workloads has different set of characteristics. In this paper, we have mainly focused on cloud workloads. Understanding the characteristics of workloads is the key to make an optimal configuration decisions and improve the system performance. This paper describes various computing workloads and relates them to their resource utilization. Specifically, the paper concentrates on cloud workloads characterization. We have classified the workloads based on different aspects from the literature also we have provided the characteristic features of the workload to know the properties and make it more understandable for the researchers. � 2017 Association for Computing Machinery. | en_US |
dc.title | Workload Characterization: Survey of Current Approaches and Research Challenges | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.