DocumentCode
61512
Title
NFRA: Generalized Network Flow-Based Resource Allocation for Hosting Centers
Author
Patel, K. ; Annavaram, Murali ; Pedram, Massoud
Author_Institution
Nvidia Inc., Santa Clara, CA, USA
Volume
62
Issue
9
fYear
2013
fDate
Sept. 2013
Firstpage
1772
Lastpage
1785
Abstract
Due to prohibitive cost of data center setup and maintenance, many small-scale businesses rely on hosting centers to provide the cloud infrastructure to run their workloads. Hosting centers host services of the clients on their behalf and guarantee quality of service as defined by service level agreements (SLAs.) To reduce energy consumption and to maximize profit it is critical to optimally allocate resources to meet client SLAs. Optimal allocation is a nontrivial task due to 1) resource heterogeneity where energy consumption of a client task varies depending on the allocated resources 2) lack of energy proportionality where energy cost for a task varies based on server utilization. In this paper, we introduce a generalized Network Flow-based Resource Allocation framework, called NFRA, for energy minimization and profit maximization. NFRA provides a unified framework to model profit maximization under a wide range of SLAs. We will demonstrate the simplicity of this unified framework by deriving optimal resource allocations for three different SLAs. We derive workload demands and server energy consumption data from SPECWeb2009 benchmark results to demonstrate the efficiency of NFRA framework.
Keywords
cloud computing; computer centres; contracts; energy consumption; quality of service; resource allocation; NFRA framework; SLA; SPECWeb2009 benchmark; cloud infrastructure; data center maintenance; data center setup; energy consumption reduction; energy cost; energy minimization; energy proportionality lackness; generalized network flow-based resource allocation framework; hosting centers; profit maximization; quality of service; resource allocation; resource heterogeneity; server energy consumption data; server utilization; service level agreements; small-scale business; workload demands; Energy consumption; Minimization; Resource management; Servers; Throughput; Time factors; Resource allocation; clouds; data center; energy proportionality; hosting center; network flow;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/TC.2012.253
Filename
6338922
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