Data Shuffling in Wireless Distributed Computing via Low-Rank Optimization

doi:10.1109/TSP.2019.2912139

	Data Shuffling in Wireless Distributed Computing via Low-Rank Optimization
	Kai Yang 1; Yuanming Shi2 ; Zhi Ding 3
	2019-06-15
发表期刊	IEEE TRANSACTIONS ON SIGNAL PROCESSING
ISSN	1053-587X
卷号	67 期号:12 页码:3087-3099
发表状态	已发表
DOI	10.1109/TSP.2019.2912139
摘要	Intelligent mobile platforms such as smart vehicles and drones have recently become the focus of attention for onboard deployment of machine learning mechanisms to enable low latency decisions with low risk of privacy breach. However, most such machine learning algorithms are both computation-and-memory intensive, which makes it highly difficult to implement the requisite computations on a single device of limited computation, memory, and energy resources. Wireless distributed computing presents new opportunities by pooling the computation and storage resources among devices. For low-latency applications, the key bottleneck lies in the exchange of intermediate results among mobile devices for data shuffling. To improve communication efficiency, we propose a co-channel communication model and design transceivers by exploiting the locally computed intermediate values as side information. A low-rank optimization model is proposed to maximize the achieved degrees-of-freedom (DoF) by establishing the interference alignment condition for data shuffling. Unfortunately, existing approaches to approximate the rank function fail to yield satisfactory performance due to the poor structure in the formulated low-rank optimization problem. In this paper, we develop an efficient difference-of-convex-functions (DC) algorithm to solve the presented low-rank optimization problem by proposing a novel DC representation for the rank function. Numerical experiments demonstrate that the proposed DC approach can significantly improve the communication efficiency whereas the achievable DoF almost remains unchanged when the number of mobile devices grows.
关键词	Wireless distributed computing data shuffling interference alignment low-rank optimization difference-of-convex-functions DC programming Ky Fan 2-k norm
URL	查看原文
收录类别	SCI ; SCIE ; EI
语种	英语
资助项目	National Science Foundation[CNS-1702752] ; National Science Foundation[ECCS1711823]
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:000467582800001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
EI入藏号	20192006930946
EI主题词	Degrees of freedom (mechanics) ; Digital storage ; Distributed computer systems ; Energy resources ; Functions ; Learning algorithms ; Machine learning ; Optimization
EI分类号	Energy Resources and Renewable Energy Issues:525.1 ; Radio Systems and Equipment:716.3 ; Data Storage, Equipment and Techniques:722.1 ; Digital Computers and Systems:722.4 ; Mathematics:921 ; Optimization Techniques:921.5 ; Mechanics:931.1
WOS关键词	INTERFERENCE ALIGNMENT
原始文献类型	Article
来源库	IEEE
引用统计
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/31165
专题	信息科学与技术学院信息科学与技术学院_PI研究组_石远明组
作者单位	1.University of Chinese Academy of Sciences, Beijing, China 2.School of Information Science and Technology, ShanghaiTech University, Shanghai, China 3.Department of Electrical and Computer Engineering, University of California at Davis, Davis, CA, USA
推荐引用方式 GB/T 7714	Kai Yang,Yuanming Shi,Zhi Ding. Data Shuffling in Wireless Distributed Computing via Low-Rank Optimization[J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING,2019,67(12):3087-3099.
APA	Kai Yang,Yuanming Shi,&Zhi Ding.(2019).Data Shuffling in Wireless Distributed Computing via Low-Rank Optimization.IEEE TRANSACTIONS ON SIGNAL PROCESSING,67(12),3087-3099.
MLA	Kai Yang,et al."Data Shuffling in Wireless Distributed Computing via Low-Rank Optimization".IEEE TRANSACTIONS ON SIGNAL PROCESSING 67.12(2019):3087-3099.