Low-Latency Layer-Aware Proactive and Passive Container Migration in Meta Computing

doi:10.1109/ICMC60390.2024.00026

科研成果详情

题名	Low-Latency Layer-Aware Proactive and Passive Container Migration in Meta Computing
作者	Liu，Mengjie 1,2; Li，Yihua 3; Mou，Fangyi 4; Tang，Zhiqing 2; Lou，Jiong 5; Guo，Jianxiong 2,4; Jia，Weijia 2,4
发表日期	2024
会议名称	1st IEEE International Conference on Meta Computing, ICMC 2024
会议录名称	Proceedings - 2024 International Conference on Meta Computing, ICMC 2024
页码	176-185
会议日期	2024-06-20——2024-06-23
会议地点	Qingdao
摘要	Meta computing is a new computing paradigm that aims to efficiently utilize all network computing resources to provide fault-tolerant, personalized services with strong security and privacy guarantees. It also seeks to virtualize the Internet as many meta computers. In meta computing, tasks can be assigned to containers at edge nodes for processing, based on container images with multiple layers. The dynamic and resource-constrained nature of meta computing environments requires an optimal container migration strategy for mobile users to minimize latency. However, the problem of container migration in meta computing has not been thoroughly explored. To address this gap, we present low-latency, layer-aware container migration strategies that consider both proactive and passive migration. Specifically: 1) We formulate the container migration problem in meta computing, taking into account layer dependencies to reduce migration costs and overall task duration by considering four delays. 2) We introduce a reinforcement learning algorithm based on policy gradients to minimize total latency by identifying layer dependencies for action selection, making decisions for both proactive and passive migration. Expert demonstrations are introduced to enhance exploitation. 3) Experiments using real data trajectories show that the algorithm outperforms baseline algorithms, achieving lower total latency.
关键词	container migration Meta computing reinforcement learning task scheduling
DOI	10.1109/ICMC60390.2024.00026
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-105012162633
引用统计
文献类型	会议论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/13751
专题	北师香港浸会大学
通讯作者	Tang，Zhiqing
作者单位	1.Beijing Normal University,Faculty of Arts and Sciences,China 2.Institute of Artificial Intelligence and Future Networks,Beijing Normal University,China 3.University of Zurich,Department of Informatics,Zurich,Switzerland 4.BNU-HKBU United International College,Guangdong Key Lab of AI and Multi-Modal Data Processing,China 5.Shanghai Jiao Tong University,Department of Computer Science and Engineering,China
推荐引用方式 GB/T 7714	Liu，Mengjie,Li，Yihua,Mou，Fangyiet al. Low-Latency Layer-Aware Proactive and Passive Container Migration in Meta Computing[C], 2024: 176-185.