Liu et al., 2016 - Google Patents
Quantitative workload analysis and prediction using Google cluster tracesLiu et al., 2016
- Document ID
- 12971338948730076738
- Author
- Liu B
- Lin Y
- Chen Y
- Publication year
- Publication venue
- 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
External Links
Snippet
Resource allocation efficiency and energy consumption are among the top concerns to today's Cloud data center. Finding the optimal point where users' multiple job requests can be accomplished timely with minimum electricity and hardware cost is one of the key factors …
- 238000004458 analytical method 0 title description 7
Classifications
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- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
- G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
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- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
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