Energy aware heuristic multi objective job scheduling for big data in green cloud

Abstract

Cloud computing is the on-demand delivery of computing or IT newlineresources over the Internet on a pay-per-use basis. A cloud services provider newlinehosted the applications, servers (both physical and virtual clusters), data newlinestorage, software development tools, and network infrastructure and manages newlinethe newlineremote datacenter. Cloud computing technology provides the newlineinfrastructure needed to make these processes efficient and cost-effective. Big newlineData is concerned with the storage, processing, and analysis of huge volumes newlineof data. The term quotbig data analyticsquot refers to a set of methods, tools, and newlinesoftware applications used to collect, analyse, clean up, and extract newlineknowledge from a wide range of high-volume, high-velocity datasets and data newlinesources that include mobile devices, the web, electronic mail, social newlinenetworking sites, and interconnected intelligent devices. The big data newlinemanagement requires optimization in order to handle data in a way that newlineenhances the quality of the product, expedites decision-making, and newlineproactively uses new analytical abilities to optimize business operations. newlineThe minimization of energy consumption in datacenters plays a newlinevital role in cloud system when dealing with big data. It depends on the size newlineand type of workload being handled by the processors while executing the newlinetask. The job or task scheduling handled by the datacenters can reduce the newlineenergy consumption using a green cloud broker, which will decrease the newlineoperational cost and help the organization save money that boost the newlineeconomy, enhance the system reliability,and quality of life in a green newlineenvironment. Hadoop MapReduce addresses scalability and complexity newlinechallenges in managing big data by adding more jobs to a persisting virtual newlinecluster distributed across numerous racks in a cloud datacenter newline