算力网络中面向计算重用的任务调度优化

doi:10.11959/j.issn.1000-436x.2023206

通信学报 ›› 2023, Vol. 44 ›› Issue (11): 129-142.doi: 10.11959/j.issn.1000-436x.2023206

• 学术论文 • 上一篇

算力网络中面向计算重用的任务调度优化

马云霄¹, 吴忠辉¹, 徐祖云¹, 衷璐洁², 许长桥¹

¹ 北京邮电大学网络与交换技术国家重点实验室，北京 100876
² 首都师范大学信息工程学院，北京 100048

修回日期:2023-09-19 出版日期:2023-11-01 发布日期:2023-11-01
作者简介:马云霄（1997− ），女，山东泰安人，北京邮电大学博士生，主要研究方向为多媒体传输、边缘计算等
吴忠辉（1997− ），男，安徽宣城人，北京邮电大学博士生，主要研究方向为区块链、人工智能和边缘计算等
徐祖云（1999− ），男，安徽六安人，北京邮电大学硕士生，主要研究方向为移动互联网、多媒体通信等
衷璐洁（1979− ），女，江西南昌人，博士，首都师范大学副教授，主要研究方向为通信网络、计算机系统结构、移动网络等
许长桥（1977− ），男，江西吉安人，博士，北京邮电大学教授，主要研究方向为移动网络、多媒体通信、网络安全等
基金资助:
国家自然科学基金资助项目(62225105);北京邮电大学博士生创新基金资助项目(CX2021108)

Optimization of task scheduling for computing reuse in computing power network

Yunxiao MA¹, Zhonghui WU¹, Zuyun XU¹, Lujie ZHONG², Changqiao XU¹

¹ State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
² Information Engineering College, Capital Normal University, Beijing 100048, China

Revised:2023-09-19 Online:2023-11-01 Published:2023-11-01
Supported by:
The National Natural Science Foundation of China(62225105);The BUPT Excellent Ph.D. Students Foundation(CX2021108)

摘要/Abstract

摘要：

为应对未来算力需求爆炸性增长所带来的挑战，将计算重用技术引入算力网络中，通过重用计算任务结果，来缩短服务时延并减少计算资源消耗。在此基础上，提出基于服务联盟的上下文感知在线学习算法。首先，设计重用指数来减少额外查找时延；然后，基于服务联盟机制进行在线学习，根据上下文信息及历史经验做出计算任务调度决策。仿真实验结果表明，所提算法在服务时延、计算资源消耗等方面均优于基准算法。

关键词: 算力网络, 计算重用, 任务调度, 在线学习

Abstract:

To cope with the challenges posed by the future explosive growth in computing power demand, computing reuse technology was introduced into the computing power network to reduce service latency and computational resource consumption by reusing the results of computational tasks.Based on this, a service federation-based context-aware online learning algorithm was proposed.First, the reuse index was designed to reduce the extra lookup latency.Then, online learning was performed based on the service federation mechanism to make computational task scheduling decisions according to contextual information and historical experience.The experimental results show that the proposed algorithm outperforms the baseline algorithms in terms of service latency and computational resource consumption.

Key words: computing power network, computing reuse, task scheduling, online learning

中图分类号:

TP393

马云霄, 吴忠辉, 徐祖云, 衷璐洁, 许长桥. 算力网络中面向计算重用的任务调度优化[J]. 通信学报, 2023, 44(11): 129-142.

Yunxiao MA, Zhonghui WU, Zuyun XU, Lujie ZHONG, Changqiao XU. Optimization of task scheduling for computing reuse in computing power network[J]. Journal on Communications, 2023, 44(11): 129-142.

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参数	值
算力节点传输功率/mW	100
噪声功率/dBm	-100
算力节点带宽资源/MHz	[10,20]
子任务的数据量/MB	[0.3,0.5]
子任务的计算需求/GHz	[0.5,0.6]
算力节点计算资源/GHz	[1,10]
查找时延/s	0.05

算力网络中面向计算重用的任务调度优化

Optimization of task scheduling for computing reuse in computing power network

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