Dependency-Aware Microservice Deployment for Edge Computing: A Deep Reinforcement Learning Approach With Network Representation

IF 7.7 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Transactions on Mobile Computing Pub Date : 2024-09-02 DOI:10.1109/TMC.2024.3453069
Chenyang Wang;Hao Yu;Xiuhua Li;Fei Ma;Xiaofei Wang;Tarik Taleb;Victor C. M. Leung
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Abstract

The popularity of microservices in industry has sparked much attention in the research community. Despite significant progress in microservice deployment for resource-intensive services and applications at the network edge, the intricate dependencies among microservices are often overlooked, and some studies underestimate the importance of system context extraction in deployment strategies. This paper addresses these issues by formulating the microservice deployment problem as a max-min problem, considering system cost and quality of service (QoS) jointly. We first study the attention-based microservice representation (AMR) method to achieve effective system context extraction. In this way, the contributions of different computing power providers (users, edge servers, or cloud servers) in the networks can be effectively paid attention to. Subsequently, we propose the attention-modified soft actor-critic (ASAC) algorithm to tackle the microservice deployment problem. ASAC leverages attention mechanisms to enhance decision-making and adapt to changing system dynamics. Our simulation results demonstrate ASAC's effectiveness, prioritizing average system cost and reward compared to the other state-of-the-art algorithms.
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边缘计算的依赖感知微服务部署:利用网络表示的深度强化学习方法
微服务在业界的流行引发了研究界的广泛关注。尽管针对网络边缘资源密集型服务和应用的微服务部署取得了重大进展,但微服务之间错综复杂的依赖关系往往被忽视,一些研究低估了系统上下文提取在部署策略中的重要性。为了解决这些问题,本文将微服务部署问题表述为最大最小问题,同时考虑系统成本和服务质量(QoS)。我们首先研究了基于注意力的微服务表示(AMR)方法,以实现有效的系统上下文提取。这样,网络中不同计算能力提供者(用户、边缘服务器或云服务器)的贡献就能得到有效关注。随后,我们提出了注意力修正软行为批评算法(ASAC)来解决微服务部署问题。ASAC 利用注意力机制来加强决策,并适应不断变化的系统动态。我们的仿真结果证明了 ASAC 的有效性,与其他最先进的算法相比,它优先考虑了平均系统成本和回报。
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来源期刊
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing 工程技术-电信学
CiteScore
12.90
自引率
2.50%
发文量
403
审稿时长
6.6 months
期刊介绍: IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.
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