On Service Migrations in the Cloud for Mobile Accesses

Author:

Wang Yang1,Veeravalli Bharadwaj2,Tham Chen-Khong2,He Shuibing3,Xu Chengzhong1

Affiliation:

1. Shenzhen Institutes of Advanced Technology, Shenzhen, China

2. National University of Singapore, Singapore

3. Wuhan University, China

Abstract

We study the problem of dynamically migrating a service in the cloud to satisfy an online sequence of mobile batch-request demands in a cost-effective way. The service may have single or multiple replicas, each running on a virtual machine. As the origin of mobile accesses frequently changes over time, this problem is particularly important for time-bounded services to achieve enhanced Quality of Service and cost effectiveness. Moving the service closer to the client locations not only reduces the service access latency but also minimizes the network costs for service providers. However, these benefits are not free. The migration comes at a cost of bulk-data transfer and service disruption, and hence, increasing the overall service costs. To gain the benefits of service migration while minimizing the caused monetary costs, we propose an efficient search-based algorithm Dmig to migrate a single server, and then extend it as a scalable algorithm, called mDmig , to the multi-server situation, a more general case in the cloud. Both algorithms are fully distributed, symmetric, and characterized by the effective use of historical access information to conduct virtual migration so that the limitations of local search in the cost reduction can be overcome. To evaluate the algorithms, we compared them with some existing algorithms and an off-line algorithm. Our simulation results showed that the proposed algorithms exhibit better performance in service migration by adapting to the changes of mobile access patterns in a cost-effective way.

Funder

Shenzhen Science and Technology Innovation

NSFC

National Key Research and Development Program of China

Science and Technology Planning Project of Guangdong Province

Publisher

Association for Computing Machinery (ACM)

Subject

Software,Computer Science (miscellaneous),Control and Systems Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Cost-Driven Data Caching in the Cloud: An Algorithmic Approach;IEEE INFOCOM 2021 - IEEE Conference on Computer Communications;2021-05-10

2. Towards cost-effective service migration in mobile edge: A Q-learning approach;Journal of Parallel and Distributed Computing;2020-12

3. Applicability analysis of the wave energy converter in low wave energy density sea areas;IOP Conference Series: Earth and Environmental Science;2020-07-01

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