移动边缘计算场景下针对资源竞争的服务迁移优化方法

王海艳; 张霖; 骆健

doi:10.11959/j.issn.1000-436x.2024143

您当前的位置：

首页 >

文章列表页 >

移动边缘计算场景下针对资源竞争的服务迁移优化方法

学术论文 | 更新时间：2024-09-10

- 移动边缘计算场景下针对资源竞争的服务迁移优化方法
- Service migration optimization method for resource competition in mobile edge computing scenarios
- 通信学报 2024年45卷第8期页码：37-50
- 作者机构：
  
  1.南京邮电大学计算机学院，江苏南京 210023
  2.江苏省大数据安全与智能处理重点实验室，江苏南京 210023
- 作者简介：
  
  [ "王海艳（1974- ），女，江苏东台人，博士，南京邮电大学教授，主要研究方向为服务计算、可信计算、大数据应用与云计算技术、隐私保护技术等。" ]
  [ "张霖（1998- ），男，湖南怀化人，南京邮电大学硕士生，主要研究方向为边缘计算。" ]
  [ "骆健（1976- ），女，江西赣州人，南京邮电大学副教授，主要研究方向为服务计算、可信计算、服务推荐等。" ]
- 基金信息：
  
  国家自然科学基金资助项目(62272243)
- DOI：10.11959/j.issn.1000-436x.2024143
  中图分类号： TP393
- 收稿：2024-03-29，
  
  修回：2024-07-16，
  
  纸质出版：2024-08-25
- 稿件说明：
移动端阅览
王海艳,张霖,骆健.移动边缘计算场景下针对资源竞争的服务迁移优化方法[J].通信学报,2024,45(08):37-50.

WANG Haiyan,ZHANG Lin,LUO Jian.Service migration optimization method for resource competition in mobile edge computing scenarios[J].Journal on Communications,2024,45(08):37-50.
王海艳,张霖,骆健.移动边缘计算场景下针对资源竞争的服务迁移优化方法[J].通信学报,2024,45(08):37-50. DOI： 10.11959/j.issn.1000-436x.2024143.

WANG Haiyan,ZHANG Lin,LUO Jian.Service migration optimization method for resource competition in mobile edge computing scenarios[J].Journal on Communications,2024,45(08):37-50. DOI： 10.11959/j.issn.1000-436x.2024143.

摘要

针对移动边缘计算（MEC）场景中边缘服务器资源受限导致服务迁移存在资源竞争的问题，基于Lyapunov技术和博弈论，提出了一种针对资源竞争的服务迁移优化方法OMRC-LG。考虑到系统迁移成本有限且当用户数量过多时难以进行轨迹预测，将服务迁移问题建模为迁移成本约束下的最优化问题，并利用Lyapunov技术将最优化问题转化为不需要预测用户轨迹的在线问题处理。为了缓解资源竞争，提出了一种基于博弈论的分布式方法求解在线问题，通过共享用户服务迁移决策以获取准确的边缘服务器可用资源，并不断更新迁移决策，实现服务迁移优化。仿真结果表明，OMRC-LG方法在满足迁移成本约束的同时，降低了平均服务时延。

Abstract

To tackle the problem of resource competition among service migrations caused by limited edge server resources in mobile edge computing (MEC) scenarios

a service migration optimization method for resource competition based on Lyapunov and game theory (OMRC-LG) was proposed. Considering the system's limited migration costs and the difficulty of predicting trajectories when the number of users was large

the service migration was modeled as an optimization problem with migration cost constraints and used the Lyapunov technique to transform it into an online problem without user trajectory prediction. To alleviate resource competition among users

a distributed method based on game theory was proposed. By sharing user service migration decisions

the method obtained accurate information on available edge server resources and would continuously update these decisions to optimize service migration. Simulation results show that the OMRC-LG method can reduce the average service delay while satisfying the migration cost constraints.

关键词

Keywords

references

YOUSEFPOUR A , FUNG C , NGUYEN T , et al . All one needs to know about fog computing and related edge computing paradigms: a complete survey [J ] . Journal of Systems Architecture , 2019 , 98 : 289 - 330 .

LI C L , ZHANG Y , LUO Y L . Flexible heterogeneous data fusion strategy for object positioning applications in edge computing environment [J ] . Computer Networks , 2022 , 212 : 109083 .

REJIBA Z , MASIP-BRUIN X , MARÍN-TORDERA E . A survey on mobility-induced service migration in the fog, edge, and related computing paradigms [J ] . ACM Computing Surveys , 2020 , 52 ( 5 ): 1 - 33 .

LEE K , KIM J , KWON I H , et al . Impact of secure container runtimes on file I/O performance in edge computing [J ] . Applied Sciences , 2023 , 13 ( 24 ): 13329 .

WANG S Q , URGAONKAR R , ZAFER M , et al . Dynamic service migration in mobile edge computing based on Markov decision process [J ] . IEEE/ACM Transactions on Networking , 2019 , 27 ( 3 ): 1272 - 1288 .

SHAMSADINI A , ENTEZARI-MALEKI R . Time-aware MDP-based service migration in 5G mobile edge computing [C ] // Proceedings of the 2022 27th International Computer Conference, Computer Society of Iran (CSICC) . Piscataway : IEEE Press , 2022 : 1 - 5 .

WANG S G , GUO Y , ZHANG N , et al . Delay-aware microservice coordination in mobile edge computing: a reinforcement learning approach [J ] . IEEE Transactions on Mobile Computing , 2021 , 20 ( 3 ): 939 - 951 .

LI C L , ZHANG Y , GAO X , et al . Energy-latency tradeoffs for edge caching and dynamic service migration based on DQN in mobile edge computing [J ] . Journal of Parallel and Distributed Computing , 2022 , 166 : 15 - 31 .

MA H R , ZHOU Z , CHEN X . Leveraging the power of prediction: predictive service placement for latency-sensitive mobile edge computing [J ] . IEEE Transactions on Wireless Communications , 2020 , 19 ( 10 ): 6454 - 6468 .

SHI Y , YI C Y , WANG R , et al . Service migration or task rerouting: a two-timescale online resource optimization for MEC [J ] . IEEE Transactions on Wireless Communications , 2024 , 23 ( 2 ): 1503 - 1519 .

LIANG Z Z , LIU Y , LOK T M , et al . Multi-cell mobile edge computing: joint service migration and resource allocation [J ] . IEEE Transactions on Wireless Communications , 2021 , 20 ( 9 ): 5898 - 5912 .

ZHOU X B , GE S X , QIU T , et al . Energy-efficient service migration for multi-user heterogeneous dense cellular networks [J ] . IEEE Transactions on Mobile Computing , 2023 , 22 ( 2 ): 890 - 905 .

DUAN J R , REN K , ZHOU W , et al . A service migration method for resource competition in mobile edge computing [C ] // Proceedings of the 2021 IEEE International Performance, Computing, and Communications Conference (IPCCC) . Piscataway : IEEE Press , 2021 : 1 - 8 .

ZHANG Q , GUI L , HOU F , et al . Dynamic task offloading and resource allocation for mobile-edge computing in dense cloud RAN [J ] . IEEE Internet of Things Journal , 2020 , 7 ( 4 ): 3282 - 3299 .

SATPATHY A , SAHOO M N , MISHRA A , et al . A service sustainable live migration strategy for multiple virtual machines in cloud data centers [J ] . Big Data Research , 2021 , 25 : 100213 .

OUYANG T , RUI L , XU C , et al . Adaptive user-managed service placement for mobile edge computing: an online learning approach [C ] // Proceedings of the IEEE Conference on Computer Communications . Piscataway : IEEE Press , 2019 : 1468 - 1476 .

NEELY M J . Stochastic network optimization with application to communication and queueing systems [M ] . Berlin : Springer , 2010 .

BARRON E N . Game theory: an introduction [M ] . New Jersey : John Wiley & Sons , 2024 .

OSBORNE M J , RUBINSTEIN A . A course in game theory [M ] . Cambridge : MIT Press , 1994 .

KUHN H W . Extensive games and the problem of information [J ] . Contributions to the Theory of Games , 1953 , 2 ( 28 ): 193 - 216 .

HU G S , JIA Y J , CHEN Z C . Multi-user computation offloading with D2D for mobile edge computing [C ] // Proceedings of the 2018 IEEE Global Communications Conference (GLOBECOM) . Piscataway : IEEE Press , 2018 : 1 - 6 .

XU M X , ZHOU Q H , WU H M , et al . PDMA: probabilistic service migration approach for delay-aware and mobility-aware mobile edge computing [J ] . Software: Practice and Experience , 2022 , 52 ( 2 ): 394 - 414 .

浏览量

1251

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于多智能体深度强化学习的智能网联汽车服务迁移优化方法

移动边缘计算场景下双时间尺度在线服务迁移方法

MEC中基于改进遗传模拟退火算法的虚拟网络功能部署策略

面向移动边缘计算的高效条件隐私保护认证密钥协商方案