READ: Robustness-oriented Edge Application Deployment in Edge Computing Environment

Li, Bo, He, Qiang, Cui, Quangming, Xia, Xiaoyu, Chen, Feifei, Jin, Hai and Yang, Yun 2020, READ: Robustness-oriented Edge Application Deployment in Edge Computing Environment, IEEE Transactions on Services Computing, pp. 1-14, doi: 10.1109/tsc.2020.3015316.

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Title READ: Robustness-oriented Edge Application Deployment in Edge Computing Environment
Author(s) Li, Bo
He, Qiang
Cui, Quangming
Xia, XiaoyuORCID iD for Xia, Xiaoyu orcid.org/0000-0003-3526-3217
Chen, FeifeiORCID iD for Chen, Feifei orcid.org/0000-0001-5455-3792
Jin, Hai
Yang, Yun
Journal name IEEE Transactions on Services Computing
Start page 1
End page 14
Total pages 14
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2020-08-10
ISSN 1939-1374
2372-0204
Keyword(s) edge computing
application deployment
robustness
optimal approach
approximation approach
integer programming
Summary Edge computing (EC) can overcome several limitations of cloud computing. In the EC environment, a service provider can deploy its application instances on edge servers to serve users with low latency. Given a limited budget K for deploying applications in a particular geographical area, some approaches have been proposed to achieves various optimization objectives, e.g., to maximize the servers' coverage, to minimize the average network latency, etc. However, the robustness of the services collectively delivered by the service provider's applications deployed on the edge servers has not been considered at all. This is a critical issue, especially in the highly distributed, dynamic and volatile EC environment. We make the first attempt to tackle this challenge. Specifically, we formulate this Robustness-oriented Edge Application Deployment(READ) problem as a constrained optimization problem and prove its NP-hardness. Then, we provide an integer programming based approach READ-O for solving it precisely, and an approximation algorithm READ-A for efficiently finding near-optimal solutions to large-scale problems. READ-A's approximation ratio is not worse than K/2, which is constant regardless of the total number of edge servers. Evaluation of the widely-used real-world dataset against five representative approaches demonstrates that our approaches can solve the READ problem effectively and efficiently.
Language eng
DOI 10.1109/tsc.2020.3015316
Indigenous content off
Field of Research 0803 Computer Software
0805 Distributed Computing
0806 Information Systems
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2020, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30140919

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