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

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.