AoI-aware task scheduling in edge-assisted real-time applications

被引：0
|
作者：
Wang H. [1 ]
Sun Q. [1 ]
Ma X. [1 ]
Zhou A. [1 ]
Wang S. [1 ]
机构：
[1] State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing
来源：
Tongxin Xuebao/Journal on Communications | 2024年 / 45卷 / 06期
基金：
中国国家自然科学基金;
关键词：
age of information; deadline; edge computing; Lyapunov optimization; task scheduling;
D O I：
10.11959/j.issn.1000-436x.2024109
中图分类号：
TP33 [电子数字计算机（不连续作用电子计算机）];
学科分类号：
081201 ;
摘要：
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. © 2024 Editorial Board of Journal on Communications. All rights reserved.
引用
收藏
页码：144 / 159
页数：15
相关论文
共 29 条
  • [1] ANDREWS J G, BUZZI S, CHOI W, Et al., What will 5G be?, IEEE Journal on Selected Areas in Communications, 32, 6, pp. 1065-1082, (2014)
  • [2] KAUL S, GRUTESER M, RAI V, Et al., Minimizing age of information in vehicular networks, Proceedings of the 2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 350-358, (2011)
  • [3] YATES R D, SUN Y, BROWN D R, Et al., Age of information: an introduction and survey, IEEE Journal on Selected Areas in Communications, 39, 5, pp. 1183-1210, (2021)
  • [4] KOSTA A, PAPPAS N, ANGELAKIS V., Age of information: a new concept, metric, and tool, Foundations and Trends® in Networking, 12, 3, pp. 162-259, (2017)
  • [5] YATES R D, KAUL S K., The age of information: real-time status updating by multiple sources, IEEE Transactions on Information Theory, 65, 3, pp. 1807-1827, (2019)
  • [6] WANG H Y, SUN Q B, WANG S G., A survey on the optimisation of age of information in wireless networks, International Journal of Web and Grid Services, 19, 1, pp. 1-33, (2023)
  • [7] CHEN X R, GATSIS K, HASSANI H, Et al., Age of information in random access channels, IEEE Transactions on Information Theory, 68, 10, pp. 6548-6568, (2022)
  • [8] DAS A K, ROY S, BANDARA E, Et al., Securing age-of-information (AoI) -enabled 5G smart warehouse using access control scheme, IEEE Internet of Things Journal, 10, 2, pp. 1358-1375, (2023)
  • [9] WANG S H, CHEN M Z, YANG Z H, Et al., Distributed reinforcement learning for age of information minimization in real-time IoT systems, IEEE Journal of Selected Topics in Signal Processing, 16, 3, pp. 501-515, (2022)
  • [10] LI J, WANG J P, CHEN Q, Et al., Digital twin-enabled service satisfaction enhancement in edge computing, Proceedings of the IEEE Conference on Computer Communications, pp. 1-10, (2023)
123