The issue of task scheduling for a multi-core processor in Fog networks, with a focus on security and energy efficiency is of great importance in real-time systems. Currently, scheduling algorithms designed for cluster computing environments utilize dynamic voltage scaling (DVS) to decrease CPU power consumption, albeit at the expense of performance. This problem becomes more pronounced when a real-time task requires robust security, resulting in heavily overloaded nodes (CPUs or computing systems) in a cluster computing environment. To address such challenges, a solution called “Energy efficient Security Driven Scheduling of Real-Time Tasks using DVS-enabled Fog Networks (ESDS)” has been proposed. The primary goal of ESDS is to dynamically adjust CPU voltages or frequencies based on the workload conditions of nodes in Fog networks, thereby achieving optimal trade-offs between security, scheduling, and energy consumption for real-time tasks. By dynamically reducing voltage or frequency levels, ESDS conserves energy while still meeting deadlines for both running and new tasks, especially during periods of high system workload. Comprehensive experiments have been carried out to compare the ESDS algorithm with established baseline algorithms, including MEG, MELV, MEHV, and AEES. These experiments affirm the originality and effectiveness of the ESDS algorithm.

中文翻译：

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通过支持 DVS 的雾网络实现节能安全驱动的实时任务调度

雾网络中多核处理器的任务调度问题在实时系统中非常重要，重点关注安全性和能源效率。目前，为集群计算环境设计的调度算法利用动态电压调整（DVS）来降低CPU功耗，尽管是以牺牲性能为代价的。当实时任务需要强大的安全性时，这个问题变得更加明显，导致集群计算环境中的节点（CPU或计算系统）严重过载。为了应对这些挑战，人们提出了一种名为“使用支持 DVS 的雾网络 (ESDS) 的实时任务节能安全驱动调度”的解决方案。 ESDS的主要目标是根据雾网络中节点的工作负载情况动态调整CPU电压或频率，从而实现实时任务的安全性、调度和能耗之间的最佳权衡。通过动态降低电压或频率水平，ESDS 可以节省能源，同时仍能满足运行任务和新任务的最后期限，特别是在系统工作负载较高的时期。我们进行了全面的实验，将 ESDS 算法与已建立的基线算法（包括 MEG、MELV、MEHV 和 AEES）进行比较。这些实验肯定了ESDS算法的独创性和有效性。