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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhen Huang Changjian Wang Lixia Liu Yuxing Peng |
| Copyright Year | 2012 |
| Description | Author affiliation: National Laboratory of Parallel and Distributed Processing, National University of Defense and Technology, Changsha, Hunan, China (Zhen Huang; Changjian Wang; Lixia Liu; Yuxing Peng) |
| Abstract | MapReduce emerges as a popular programming model for data-intensive scalable computing. As one of core components, task schedule comes to be a very hot topic in recent studies. However, the computing on fault-tolerant applications has not been covered yet. In the paper, we at first point out the importance of fault-tolerant computing and propose a novel model to find out an optimal task allocation scheme, which allows us to obtain the optimal job availability. To analyze the properties of task allocation, we proof several theorems and evaluate them with analysis and experiments. Our experiments show that the reduction of job unavailability by our method is about one order of magnitude as compared to the systematical allocation. |
| Starting Page | 249 |
| Ending Page | 254 |
| File Size | 154136 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467302418 |
| e-ISBN | 9781467302425 |
| DOI | 10.1109/ICCSE.2012.6295068 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-07-14 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Availability Fault tolerance Upper bound Computational modeling Generating function Fault tolerant systems Multi-task allocation Polynomials Resource management Fault-tolerant computing MapReduce |
| Content Type | Text |
| Resource Type | Article |
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