期刊
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
卷 -, 期 -, 页码 -出版社
WILEY-HINDAWI
DOI: 10.1155/2018/2102348
关键词
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资金
- National Natural Science Foundation of China [61772205]
- Guangdong Province Natural Science Foundation Team Project [10351806001000000]
- Guangdong Provincial Scientific and Technological Projects [2016A010101018, 2016A010119171, 2016A010106007, 2016B090927010]
- Guangdong Province Advanced and Key Technology Creative Research Project [2014B010110004]
- Nansha Science and Technology Projects [2017GJ001]
- Industry-University-Academy Collaborative Innovation Key Project of Guangzhou [201604016074]
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.
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