Twister Platform for MapReduce Applications on a Docker Container

Abstract

Docker is one of ways to provide more light-weight for agile computing resource based on container technique to handle this problem. For this work we have chosen this specific tool due to the increasing popularity of MapReduce and cloud container technologies such as Docker. This paper aims at automatically configuring Twister workloads for container-driven clouds. Basically this is the first attempt towards automatic configuration of Twister jobs on container-based cloud platform for many workloads.