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.

Le-Le Li;Jiang-Yi Liu;Jian-Ping Fan;Xue-Hai Qian;Kai Hwang;Yeh-Ching Chung;Zhi-Bin Yu

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

计算机科学技术学报（英文版）

[1]Le-Le Li;Jiang-Yi Liu;Jian-Ping Fan;Xue-Hai Qian;Kai Hwang;Yeh-Ching Chung;Zhi-Bin Yu-.SOCA-DOM:A Mobile System-on-Chip Array System for Analyzing Big Data on the Move)[J].计算机科学技术学报（英文版）,2022(06):1271-1289

Mesos

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