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

doi:10.1155/2021/9285802

	Adaptive In-Network Collaborative Caching for Enhanced Ensemble Deep Learning at Edge
	Qin, Yana 1,2; Wu, Danye 3; Xu, Zhiwei 1,2; Tian, Jie 4; Zhang, Yujun 2
	2021-09-26
发表期刊	MATHEMATICAL PROBLEMS IN ENGINEERING
ISSN	1024-123X
卷号	2021 页码:14
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.
DOI	10.1155/2021/9285802
收录类别	SCI
语种	英语
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
WOS类目	Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS记录号	WOS:000703342500006
出版者	HINDAWI LTD
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/17057
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.