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Adaptive In-Network Collaborative Caching for Enhanced Ensemble Deep Learning at Edge

文献类型：期刊论文

作者Qin, Yana1,2; Wu, Danye3; Xu, Zhiwei1,2; Tian, Jie4; Zhang, Yujun2
刊名MATHEMATICAL PROBLEMS IN ENGINEERING
出版日期2021-09-26
卷号2021页码:14
ISSN号1024-123X
DOI10.1155/2021/9285802
英文摘要To enhance the quality and speed of data processing and protect the privacy and security of the data, edge computing has been extensively applied to support data-intensive intelligent processing services at edge. Among these data-intensive services, ensemble learning-based services can, in natural, leverage the distributed computation and storage resources at edge devices to achieve efficient data collection, processing, and analysis. Collaborative caching has been applied in edge computing to support services close to the data source, in order to take the limited resources at edge devices to support high-performance ensemble learning solutions. To achieve this goal, we propose an adaptive in-network collaborative caching scheme for ensemble learning at edge. First, an efficient data representation structure is proposed to record cached data among different nodes. In addition, we design a collaboration scheme to facilitate edge nodes to cache valuable data for local ensemble learning, by scheduling local caching according to a summarization of data representations from different edge nodes. Our extensive simulations demonstrate the high performance of the proposed collaborative caching scheme, which significantly reduces the learning latency and the transmission overhead.
资助项目Open Foundation of State Key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications)[SKLNST-2020-1-18] ; National Science Foundation of China[61962045] ; National Science Foundation of China[61962044] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDC02030500] ; Science and Technology Planning Project of Inner Mongolia Autonomous Region[2019GG372] ; Key Technologies RD Program of Inner Mongolia Autonomous Region[2020GG0094] ; Science Research Project of Inner Mongolia University of Technology[BS201934] ; Visiting Scholar Project of China Scholarship Council[201908150030] ; Visiting Scholar Project of China Scholarship Council[201904910802]
WOS研究方向Engineering ; Mathematics
语种英语
WOS记录号WOS:000703342500006
出版者HINDAWI LTD
源URL[http://119.78.100.204/handle/2XEOYT63/17056]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Xu, Zhiwei
作者单位1.Inner Mongolia Univ Technol, Coll Data Sci & Applicat, Hohhot 100080, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
3.Samsung R&D Inst China, Beijing, Peoples R China
4.New Jersey Inst Technol, Dept Comp Sci, 323 Dr Martin Luther King Jr Blvd, Newark, NJ 07102 USA
推荐引用方式
GB/T 7714		 Qin, Yana,Wu, Danye,Xu, Zhiwei,et al. Adaptive In-Network Collaborative Caching for Enhanced Ensemble Deep Learning at Edge[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2021,2021:14.
APA Qin, Yana,Wu, Danye,Xu, Zhiwei,Tian, Jie,&Zhang, Yujun.(2021).Adaptive In-Network Collaborative Caching for Enhanced Ensemble Deep Learning at Edge.MATHEMATICAL PROBLEMS IN ENGINEERING,2021,14.
MLA Qin, Yana,et al."Adaptive In-Network Collaborative Caching for Enhanced Ensemble Deep Learning at Edge".MATHEMATICAL PROBLEMS IN ENGINEERING 2021(2021):14.

入库方式： OAI收割

来源：计算技术研究所

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