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Efficient dynamic service maintenance for edge services

Zhang, Yiwen, Li, Jin, Zhou, Zhangbing and Liu, Xiao 2018, Efficient dynamic service maintenance for edge services, IEEE Access, vol. 6, pp. 8829-8840, doi: 10.1109/ACCESS.2018.2806391.

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Title Efficient dynamic service maintenance for edge services
Author(s) Zhang, Yiwen
Li, Jin
Zhou, Zhangbing
Liu, XiaoORCID iD for Liu, Xiao orcid.org/0000-0001-8400-5754
Journal name IEEE Access
Volume number 6
Start page 8829
End page 8840
Total pages 12
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2018-02
ISSN 2169-3536
Keyword(s) Science & Technology
Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Telecommunications
Computer Science
Engineering
Mobile edge computing
edge service
service maintenance
skyline
skyline graph
RESOURCE-ALLOCATION
MOBILE
Summary The emergence of many new computing applications, such as Internet of Vehicles (IoV) and smart homes, has been made possible by the large pool of cloud resources and services. However, the cloud computing paradigm is unable to meet the requirements of delay-sensitive business applications, such as low latency, mobility support, and location awareness. In this context, Mobile Edge Computing (MEC) is introduced to improve the quality of experience (QoE) by bringing cloud resources and services closer to the user by leveraging available resources in the edge networks. However, the performance of MEC is dynamic in nature due to its location awareness, mobility and proximity. As a result, an effective mechanism is needed for providing efficient dynamic service maintenance for edge services. In this paper, we propose applying the Skyline Graph Model and employing the Directed Acyclic Graph theory to store and update mobile edge services. Specifically, the Skyline Graph (SG) algorithm is designed to solve the insertion, deletion, updating and searching of mobile edge services to achieve efficient maintenance for edge services. Comprehensive experiments are conducted on both real-world web services and simulated datasets to evaluate the effectiveness and efficiency of our approaches. The results show that our algorithms can achieve significantly better performance and robustness than the baseline algorithm.
Language eng
DOI 10.1109/ACCESS.2018.2806391
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2018, IEEE
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30106658

Document type: Journal Article
Collections: School of Information Technology
Open Access Collection
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.