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Robustness-oriented k edge server placement

conference contribution
posted on 2024-11-03, 15:10 authored by Guangming Cui, Qiang He, Xiaoyu XiaXiaoyu Xia, Feifei Chen, Hai Jin, Yun Yang
Mobile Edge Computing (MEC) is an emerging and prospective computing paradigm that supports low-latency content delivery. In a MEC environment, edge servers are attached to base stations or access points in closer proximity to endusers to reduce the end-to-end latency in their access to online content. From an edge infrastructure provider's perspective, a cost-effective k edge server placement (kESP) places k edge servers within a particular geographic area to maximize their coverage. However, in the distributed MEC environment, edge servers are often subject to failures due to various reasons, e.g., software exceptions, hardware faults, cyberattacks, etc. End-users connected to a failed edge server have to access online content from the remote cloud if they are not covered by any other edge servers. This significantly jeopardizes endusers' quality of experience. Thus, the robustness of an edge server network must be considered in edge server placement. In this paper, we formally model this Robustness-oriented k Edge Server Placement (RkESP) problem, and prove that finding the optimal solution to this problem is .,Vl'-hard. Thus, we firstly propose an integer programming based optimal approach, namely Opt, to find optimal solutions to small-scale RkESP problems. Then, we propose an approximate approach, namely Approx, for solving large-scale RkESP problems efficiently with an O(k)-approximation ratio. Finally, the performance of the two approaches is experimentally evaluated against five state-of-the-art approaches on a real-world dataset and a large-scale synthesized dataset.

Funding

Domain-specific visual languages for big data analytics applications

Australian Research Council

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A data driven paradigm for service-oriented system engineering

Australian Research Council

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History

Start page

81

End page

90

Total pages

10

Outlet

Proceedings of the 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing

Name of conference

CCGRID 2020

Publisher

IEEE

Place published

United States

Start date

2020-05-11

End date

2020-05-14

Language

English

Copyright

© 2020 IEEE

Former Identifier

2006122251

Esploro creation date

2023-05-18

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