A Task Scheduling Algorithm Based on Classification Mining in Fog Computing Environment

作者：Lindong Liu, Deyu Qi, Naqin Zhou, Yilin Wu · 发表于：Wireless Communications and Mobile Computing · 年份：2018 · DOI：10.1155/2018/2102348 · 被引用次数：101 · 研究领域：Distributed and Parallel Computing Systems、Cloud Computing and Resource Management、IoT and Edge/Fog Computing

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.