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首页> 外文期刊>Communications, IET >Workload scheduling toward worst-case delay and optimal utility for single-hop Fog-IoT architecture
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Workload scheduling toward worst-case delay and optimal utility for single-hop Fog-IoT architecture

机译:针对最坏情况延迟的工作负载调度和单跳Fog-IoT架构的最佳效用

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摘要

Fog computing is a distributed computing model that can utilise the storage, analysis and processing capabilities of fog nodes near edge devices. Although fog computing can support task processing for various Internet of Things (IoT) systems, Fog-IoT architecture faces several new challenges with the rapid development of IoT systems, especially delay-sensitive IoT systems, such as stochastic and dynamic data arrival, optimal utility and deadline of tasks. To address these challenges, workload scheduling toward worst-case delay and optimal utility for single-hop Fog-IoT architecture are studied and the workload dynamic scheduling algorithm (WDSA) is proposed. The proposed WDSA algorithm can maximise the average throughput utility while guarantees the worst-case delay of task processing. In addition, it is online and needs no prior information about future. The algorithm performance is analysed from the perspective of optimality and worst-case delay, demonstrating that the proposed WDSA algorithm can get an approximate optima and worst-case delay guarantees. Finally, simulation results demonstrate that the efficiency and efficacy of this kind of the algorithm can meet the requirement.
机译:雾计算是一种分布式计算模型,可以利用边缘设备附近的雾节点的存储,分析和处理功能。尽管雾计算可以支持各种物联网(IoT)系统的任务处理,但随着IoT系统(尤其是对延迟敏感的IoT系统,例如随机和动态数据到达,最优效用)的快速发展,Fog-IoT体系结构面临着一些新挑战。和任务期限。为了应对这些挑战,研究了针对单跳Fog-IoT体系结构的最坏情况时延和最优效用的工作负载调度,并提出了工作负载动态调度算法(WDSA)。所提出的WDSA算法可以最大程度地提高平均吞吐率,同时保证任务处理的最坏情况下的延迟。此外,它是在线的,不需要任何有关未来的信息。从最优性和最坏情况时延的角度分析了算法的性能,证明了所提出的WDSA算法可以得到近似最优值和最坏情况时延保证。最后,仿真结果表明,该算法的有效性和有效性可以满足要求。

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