Joint optimization algorithm for 6G network task offloading and fine-grained slice resource scheduling

WANG Ye; WANG Yifei; CHEN Kang; ZHU Xiaorong; TONG En; XU Yufei

doi:10.11959/j.issn.1000-0801.2024144

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Joint optimization algorithm for 6G network task offloading and fine-grained slice resource scheduling

Research and Development | 更新时间：2024-08-05

- Joint optimization algorithm for 6G network task offloading and fine-grained slice resource scheduling
- Telecommunications Science Vol. 40, Issue 5, Pages: 86-99(2024)
- 作者机构：
  
  1.江苏移动信息系统集成有限公司，江苏南京 210013
  2.南京邮电大学通信与信息工程学院，江苏南京 210003
  3.中国移动通信集团江苏有限公司，江苏南京 210013
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61871237;92067101);Program to Cultivate Middle-aged and Young Science Leaders of Universities of Jiangsu Province, The Key Research and Development Program of Jiangsu Province
- DOI：10.11959/j.issn.1000-0801.2024144
  CLC： TN92
- Received：26 November 2023，
  
  Revised：20 April 2024，
  
  Published：20 May 2024
- 稿件说明：
移动端阅览
王晔,王逸飞,陈康等.6G网络任务卸载与细粒度切片资源调度联合优化算法[J].电信科学,2024,40(05):86-99.

WANG Ye,WANG Yifei,CHEN Kang,et al.Joint optimization algorithm for 6G network task offloading and fine-grained slice resource scheduling[J].Telecommunications Science,2024,40(05):86-99.
王晔,王逸飞,陈康等.6G网络任务卸载与细粒度切片资源调度联合优化算法[J].电信科学,2024,40(05):86-99. DOI： 10.11959/j.issn.1000-0801.2024144.

WANG Ye,WANG Yifei,CHEN Kang,et al.Joint optimization algorithm for 6G network task offloading and fine-grained slice resource scheduling[J].Telecommunications Science,2024,40(05):86-99. DOI： 10.11959/j.issn.1000-0801.2024144.

摘要

针对未来全域、全场景多样化的业务需求，6G网络需要提供场景化、个性化的服务能力。针对未来细粒度业务服务质量保障问题，提出了6G网络任务卸载与细粒度切片资源调度联合优化算法，联合考虑多MEC的计算卸载和网络切片的资源调度，在有限的资源内，最小化任务的执行时延和能耗成本，并采用异步训练的A3C强化学习算法进行求解。仿真结果表明，对比传统算法，该算法可以在满足用户业务需求的情况下降低计算成本，并且算法收敛速度快，可以实现快速决策。

Abstract

In response to the diverse business needs of the future in all domains and scenarios

6G networks need to provide scenario-based and personalized service capabilities. Aiming at the problem of quality assurance of fine-grained business services in the future

a joint optimization algorithm for 6G network task offloading and fine-grained slice resource scheduling was proposed

which jointly considered the calculation offloading of multiple MECs and the resource scheduling of network slices

and minimized the execution delay and energy consumption cost of the task within limited resources. Then the A3C reinforcement learning algorithm of asynchronous training was used to solve it. The simulation results show that

compared with the traditional algorithm

the proposed algorithm can reduce the computing cost while meeting the business needs of users. Additionally

the algorithm converges fast and can realize fast decision-making.

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Keywords

references

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ZHANG J , XIA W W , YAN F , et al . Joint computation offloading and resource allocation optimization in heterogeneous networks with mobile edge computing [J ] . IEEE Access , 2018 ( 6 ): 19324 - 19337 .

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