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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaofeng Gao Wen Xu Fan Wu Guihai Chen |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Comput. Sci. & Eng., Shanghai Jiatong Univ., Shanghai, China (Xiaofeng Gao; Wen Xu; Fan Wu; Guihai Chen) |
| Abstract | As the base infrastructure to support various cloud services, data center draws more and more attractions from both academia and industry. A stable, effective, and robust data center network (DCN) management system is urgently required from institutions and corporations. However, existing management schemes have several problems, including the difficulty to manage the entire network with heterogeneous network components by a centralized controller, and the short-sighted mechanism to deal with resource allocation, congestion control, and VM migration. In this paper, we design Sheriff: a distributed pre-alert and management scheme for DCN management. Sheriff is a regional self-automatic control scheme at end host side to balance network traffic and workload. It includes two phases: prediction and management. Each end-host predicts possible overload and congestion by prediction strategy based on ARIMA and Neural Network methodology, and perform an Alert message. Delegated local controllers then monitor their dominating region and activate localized protocols VmMigration to manage the network. We illustrate the predication accuracy by network traces from a local data center service provider, examine the management efficiency by simulations on both Fat-Tree topology and Bcube topology, and prove that VmMigration is an approximation with ratio 3+2/p where p is a constant predefined in local search algorithm. Both numerical simulations and theoretical analysis validate the efficiency of our design. In all, Sheriff is a fast and effective scheme to better improve the performance of DCN. |
| Starting Page | 669 |
| Ending Page | 678 |
| File Size | 6752572 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781467375870 |
| ISSN | 01903918 |
| DOI | 10.1109/ICPP.2015.76 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-09-01 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Conferences Parallel processing |
| Content Type | Text |
| Resource Type | Article |
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