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Erschienen in:
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2022 | OriginalPaper | Buchkapitel

SCESP: An Edge Server Placement Method Based on Spectral Clustering in Mobile Edge Computing

verfasst von : Lijuan Wang, Yingya Guo, Jiangyuan Yao, Siyu Zhou

Erschienen in: Advances in Artificial Intelligence and Security

Verlag: Springer International Publishing

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Abstract

With the rapid development of Internet of Things (IoT) and 5G, mobile edge computing is gaining popularity for its low computation latency, bandwidth costs and energy consumption. In mobile edge computing, the placement of edge servers is one of the most significant problems and attracts worldwide attention. However, two major problems of edge server placement: high access delay and unbalanced workload of edge servers, have not been completely solved yet. To better solve these two problems, this paper proposes a new Spectral-Clustering-based Edge Server Placement (SCESP) algorithm, which can effectively reduce the access delay and make the workload of each edge server more balanced. In the evaluation, we use the Shanghai Telecom’s base station dataset to test the performance of SCESP and extensive experiments demonstrate the superior performance of SCESP in reducing the access delay and balancing the edge server workload.

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Metadaten
Titel
SCESP: An Edge Server Placement Method Based on Spectral Clustering in Mobile Edge Computing
verfasst von
Lijuan Wang
Yingya Guo
Jiangyuan Yao
Siyu Zhou
Copyright-Jahr
2022
Buch
Advances in Artificial Intelligence and Security

Print ISBN: 978-3-031-06760-0

Electronic ISBN: 978-3-031-06761-7

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-3-031-06761-7_42

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