Technology of Network & Communication
|
3403-3406

Hotspot prediction for edge server based on online-offline interactions

Xiang Kai1
Zeng Yuanyuan2
1. School of Information Management & Statistics, Hubei University of Economics, Wuhan 430205, China
2. School of Electronic Information, Wuhan University, Wuhan 430072, China

Abstract

With the popularization of real-time data processing and augmented reality applications, it is urgent to make research on the hotspot prediction for edge nodes in mobile edge computing paradigms to solve the access delay issues caused by the distribution, bandwidth and performance of servers. This paper proposed a novel edge hotspot detection scheme. It proposed to extract the offline population shift feature and online content access feature through CNN and LSTM, and then made interactions between the online-offline features by using attention mechanism. It predicted the hotspot degree of the edge node combining with the graph embedding of urban edge nodes. The scheme provided basis for edge node resource allocations. The performance evaluations were based on real dataset of southern city in China. The proposed scheme outperforms the other related work with much better accuracy for hotspot prediction.

Foundation Support

湖北省自然科学基金面上项目(2019CFB765)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.04.0115
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 11
Section: Technology of Network & Communication
Pages: 3403-3406
Serial Number: 1001-3695(2021)11-035-3403-04

Publish History

[2021-11-05] Printed Article

Cite This Article

项慨, 曾园园. 基于线上线下关联推理的边缘节点热点预测 [J]. 计算机应用研究, 2021, 38 (11): 3403-3406. (Xiang Kai, Zeng Yuanyuan. Hotspot prediction for edge server based on online-offline interactions [J]. Application Research of Computers, 2021, 38 (11): 3403-3406. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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