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北京邮电大学网络与交换技术国家重点实验室,北京 100876
[ "王红艳(1987- ),女,内蒙古呼和浩特人,北京邮电大学博士生,主要研究方向为边缘计算、信息年龄。" ]
[ "孙其博(1975- ),男,河南郑州人,博士,北京邮电大学研究员,主要研究方向为网络服务与智能、物联网应用技术。" ]
[ "马骁(1990- ),女,山东德州人,博士,北京邮电大学讲师,主要研究方向为移动云计算、移动边缘计算。" ]
[ "周傲(1987- ),女,湖南衡阳人,博士,北京邮电大学副教授,主要研究方向为边缘计算、云计算。" ]
[ "王尚广(1982- ),男,河南周口人,博士,北京邮电大学教授,主要研究方向为服务计算、移动边缘计算与智能、5G/6G核心网等。" ]
收稿日期:2023-12-29,
修回日期:2024-05-21,
纸质出版日期:2024-06-25
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王红艳,孙其博,马骁等.边缘辅助实时应用中信息年龄感知的任务调度[J].通信学报,2024,45(06):144-159.
WANG Hongyan,SUN Qibo,MA Xiao,et al.AoI-aware task scheduling in edge-assisted real-time applications[J].Journal on Communications,2024,45(06):144-159.
王红艳,孙其博,马骁等.边缘辅助实时应用中信息年龄感知的任务调度[J].通信学报,2024,45(06):144-159. DOI: 10.11959/j.issn.1000-436x.2024109.
WANG Hongyan,SUN Qibo,MA Xiao,et al.AoI-aware task scheduling in edge-assisted real-time applications[J].Journal on Communications,2024,45(06):144-159. DOI: 10.11959/j.issn.1000-436x.2024109.
针对无线设备资源受限导致状态提取滞后难以满足实时应用对信息新鲜度需求的问题,考虑到边缘节点处理容量的有限性,提出了一种联合考虑信息新鲜度与调度实时性的调度方法。该方法首先利用队列的系统时间和信息年龄分别刻画任务在计算之前的时延和计算之后的信息新鲜度,同时给每个卸载任务合理的截止期限,来保证任务进入计算过程之前的有效性。然后,采用最小处理速率约束方法对任务调度过程中的处理速率进行约束,保证任务调度的实时性。最后,基于Lyapunov优化技术实现优化长期任务调度决策的目的。仿真结果表明,所提方法在调度实时性和系统信息新鲜度方面均具有较好的性能。
To address the issue where the resource limitations of wireless devices caused state extraction delays that cannot meet the freshness requirements of real-time applications
considering the limited processing capacity of edge nodes
a scheduling method that jointly considered information freshness and real-time performance was proposed. This method initially characterized the task delay before computation and the information freshness after computation by utilizing the system time of the queue and the age of information
respectively. Simultaneously
reasonable deadlines were assigned to each offloaded task to ensure their validity before entering the computation process. Then
the minimum processing rate constraint method was employed to restrict the processing rate during task scheduling
thereby ensuring the real-time nature of task scheduling. Finally
the objective of optimizing long-term task scheduling decisions was achieved based on Lyapunov optimization techniques. Simulation results demonstrate the good performance of the proposed method in both scheduling timeliness and system information freshness.
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