As an emerging computing paradigm, fog computing provides more available computing resources for Internet of Things (IoT) users in an efficient and timely manner. However, the energy consumption generated by fog computing is also further increased, which makes electricity costs and carbon emissions continue to rise. At the same time, the mobile characteristics of computing nodes in fog computing will reduce the system’s reliability. In this paper, a low-delay scheduling algorithm is proposed for fog computing workflows under energy consumption constrained, namely the Minimal Schedule Time with Energy Constraint (MSTEC) algorithm. The algorithm can set energy consumption constrained for the workflow and effectively reduce the completion time of the workflow. In addition, a High Reliability with Energy Constraint (HREC) algorithm for fog computing workflow under energy consumption constrained was proposed to optimize the system reliability of fog computing in mobile scenarios. Our experiments show that the MSTEC algorithm reduces the completion time by about 16.5% on average compared with the baseline algorithm, and the HREC algorithm improves the system reliability by 22% compared with the MSTEC algorithm, which demonstrates that our proposed algorithms can achieve better performance for energy consumption constrained workflows in fog computing environments.

中文翻译：

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基于 SLA 的任务卸载，适用于雾计算中能耗受限的工作流程

雾计算作为一种新兴的计算范式，能够高效、及时地为物联网用户提供更多可用的计算资源。然而，雾计算产生的能源消耗也进一步增加，这使得电力成本和碳排放不断上升。同时，雾计算中计算节点的移动特性会降低系统的可靠性。本文针对能耗约束下的雾计算工作流提出了一种低延迟调度算法，即能量约束下的最小调度时间（MSTEC）算法。该算法可以为工作流设置能耗约束，有效减少工作流的完成时间。此外，提出了一种能耗约束下的雾计算工作流高可靠性（HREC）算法，以优化移动场景下雾计算的系统可靠性。我们的实验表明，与基线算法相比，MSTEC算法平均减少了约16.5%的完成时间，而HREC算法与MSTEC算法相比，系统可靠性提高了22%，这表明我们提出的算法可以取得更好的性能适用于雾计算环境中能耗受限的工作流程。