A Task Scheduling Algorithm Based on Classification Mining in Fog Computing Environment
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| Publicat a: | Wireless Communications & Mobile Computing (Online) vol. 2018 (2018) |
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| Autor principal: | |
| Altres autors: | , , |
| Publicat: |
John Wiley & Sons, Inc.
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| Accés en línia: | Citation/Abstract Full Text Full Text - PDF |
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|---|---|---|---|
| 001 | 2407628105 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1530-8677 | ||
| 022 | |a 1530-8669 | ||
| 024 | 7 | |a 10.1155/2018/2102348 |2 doi | |
| 035 | |a 2407628105 | ||
| 045 | 2 | |b d20180101 |b d20181231 | |
| 084 | |a 239331 |2 nlm | ||
| 100 | 1 | |a Liu, Lindong |u Research Institute of Computer Systems, South China University of Technology, Guangzhou, China; Department of Computer Science, Guangdong University of Education, Guangzhou, China | |
| 245 | 1 | |a A Task Scheduling Algorithm Based on Classification Mining in Fog Computing Environment | |
| 260 | |b John Wiley & Sons, Inc. |c 2018 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Fog computing (FC) is an emerging paradigm that extends computation, communication, and storage facilities towards the edge of a network. In this heterogeneous and distributed environment, resource allocation is very important. Hence, scheduling will be a challenge to increase productivity and allocate resources appropriately to the tasks. We schedule tasks in fog computing devices based on classification data mining technique. A key contribution is that a novel classification mining algorithm I-Apriori is proposed based on the Apriori algorithm. Another contribution is that we propose a novel task scheduling model and a TSFC (Task Scheduling in Fog Computing) algorithm based on the I-Apriori algorithm. Association rules generated by the I-Apriori algorithm are combined with the minimum completion time of every task in the task set. Furthermore, the task with the minimum completion time is selected to be executed at the fog node with the minimum completion time. We finally evaluate the performance of I-Apriori and TSFC algorithm through experimental simulations. The experimental results show that TSFC algorithm has better performance on reducing the total execution time of tasks and average waiting time. | |
| 653 | |a Research | ||
| 653 | |a Standard deviation | ||
| 653 | |a Text categorization | ||
| 653 | |a Task scheduling | ||
| 653 | |a Datasets | ||
| 653 | |a Performance evaluation | ||
| 653 | |a Classification | ||
| 653 | |a Electronic devices | ||
| 653 | |a Resource allocation | ||
| 653 | |a Internet of Things | ||
| 653 | |a Researchers | ||
| 653 | |a Traffic congestion | ||
| 653 | |a Computer simulation | ||
| 653 | |a Distributed processing | ||
| 653 | |a Scheduling | ||
| 653 | |a Big Data | ||
| 653 | |a Data mining | ||
| 653 | |a Cloud computing | ||
| 653 | |a Algorithms | ||
| 653 | |a Storage facilities | ||
| 653 | |a Completion time | ||
| 653 | |a Schedules | ||
| 700 | 1 | |a Qi, Deyu |u Research Institute of Computer Systems, South China University of Technology, Guangzhou, China | |
| 700 | 1 | |a Zhou, Naqin |u Cyberspace Institute of Advanced technology, Guangzhou University, Guangzhou, China | |
| 700 | 1 | |a Wu, Yilin |u Department of Computer Science, Guangdong University of Education, Guangzhou, China | |
| 773 | 0 | |t Wireless Communications & Mobile Computing (Online) |g vol. 2018 (2018) | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2407628105/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2407628105/fulltext/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2407628105/fulltextPDF/embedded/ZKJTFFSVAI7CB62C?source=fedsrch |