SOCA-DOM:A Mobile System-on-Chip Array System for Analyzing Big Data on the Move  

作　　者：Le-Le Li Jiang-Yi Liu Jian-Ping Fan Xue-Hai Qian Kai Hwang Yeh-Ching Chung Zhi-Bin Yu 李乐乐;刘江佾;樊建平;钱学海;黄铠;钟叶青;喻之斌(Center for Heterogeneous and Intelligent Computing,Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences,Shenzhen 518055,China;School of Science and Engineering,The Chinese University of Hong Kong,Shenzhen,Shenzhen 518172,China;Center for High Performance Computing,Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences Shenzhen 518055,China;Ming Hsieh Department of Electrical and Computer Engineering,University of Southern California,Los Angeles CA 90089-0001,U.S.A.;Department of Computer Science,University of Southern California,Los Angeles,CA 90089-0001,U.S.A.;School of Data and Science,The Chinese University of Hong Kong,Shenzhen,Shenzhen 518172,China)

机构地区：[1]Center for Heterogeneous and Intelligent Computing,Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences,Shenzhen 518055,China [2]School of Science and Engineering,The Chinese University of Hong Kong,Shenzhen,Shenzhen 518172,China [3]Center for High Performance Computing,Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences Shenzhen 518055,China [4]Ming Hsieh Department of Electrical and Computer Engineering,University of Southern California,Los Angeles CA 90089-0001,U.S.A. [5]Department of Computer Science,University of Southern California,Los Angeles,CA 90089-0001,U.S.A. [6]School of Data and Science,The Chinese University of Hong Kong,Shenzhen,Shenzhen 518172,China

出　　处：《Journal of Computer Science & Technology》2022年第6期1271-1289,共19页计算机科学技术学报（英文版）

基　　金：the Key Research and Development Program of Guangdong Province of China under Grant No.2019B010155003;the National Natural Science Foundation of China under Grant Nos.61672511,61702495,and 61802384;the Shenzhen Institute of Artificial Intelligence and Robotics for Society,The Chinese University of Hong Kong,Shenzhen,and the Alibaba Innovative Research Project for Large-Scale Graph Pattern Discovery,Analysis,and Query Techniques.

摘　　要：Recently,analyzing big data on the move is booming.It requires that the hardware resource should be low volume,low power,light in weight,high-performance,and highly scalable whereas the management software should be flexible and consume little hardware resource.To meet these requirements,we present a system named SOCA-DOM that encompasses a mobile system-on-chip array architecture and a two-tier“software-defined”resource manager named Chameleon.First,we design an Ethernet communication board to support an array of mobile system-on-chips.Second,we propose a two-tier software architecture for Chameleon to make it flexible.Third,we devise data,configuration,and control planes for Chameleon to make it“software-defined”and in turn consume hardware resources on demand.Fourth,we design an accurate synthetic metric that represents the computational power of a computing node.We employ 12 Apache Spark benchmarks to evaluate SOCA-DOM.Surprisingly,SOCA-DOM consumes up to 9.4x less CPU resources and 13.5x less memory than Mesos which is an existing resource manager.In addition,we show that a 16-node SOCA-DOM consumes up to 4x less energy than two standard Xeon servers.Based on the results,we conclude that an array architecture with fine-grained hardware resources and a software-defined resource manager works well for analyzing big data on the move.

关 键 词：edge computing mobile architecture resource management big data analytics software-defined systems 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]