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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Goudarzi, H. Ghasemazar, M. Pedram, M. |
| Copyright Year | 2012 |
| Abstract | Cloud computing systems (or hosting datacenters) have attracted a lot of attention in recent years. Utility computing, reliable data storage, and infrastructure-independent computing are example applications of such systems. Electrical energy cost of a cloud computing system is a strong function of the consolidation and migration techniques used to assign incoming clients to existing servers. Moreover, each client typically has a service level agreement (SLA), which specifies constraints on performance and/or quality of service that it receives from the system. These constraints result in a basic trade-off between the total energy cost and client satisfaction in the system. In this paper, a resource allocation problem is considered that aims to minimize the total energy cost of cloud computing system while meeting the specified client-level SLAs in a probabilistic sense. The cloud computing system pays penalty for the percentage of a client's requests that do not meet a specified upper bound on their service time. An efficient heuristic algorithm based on convex optimization and dynamic programming is presented to solve the aforesaid resource allocation problem. Simulation results demonstrate the effectiveness of the proposed algorithm compared to previous work. |
| Starting Page | 172 |
| Ending Page | 179 |
| File Size | 359472 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467313957 |
| DOI | 10.1109/CCGrid.2012.112 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-05-13 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Servers Cloud computing Time factors Optimization Resource management Memory management Contracts Server Consolidation Cloud Computing Virtual Machine Placement Service Level Agreement Energy Efficiency Data center |
| Content Type | Text |
| Resource Type | Article |
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