Development of Resource Management Techniques for Big Data Environment

Abstract

Big Data is one of the promising domains in the field computer science. It has shown its significance in many variations. This domain has lot of research opportunities to address to various issues. There are two major operations performed on the Big Data: storing and processing. The research is on the processing of the data in the domain. To process data many entities are required. Data processing is an important task which should be performed with less time consuming. In order to execute the data in a faster rate, there is a need to improve the features involved with it. Since the resources are part of the job execution. An analysis has to be made on the various resources used during job execution. The resources are used during job execution. The resources include memory, bandwidth, disk space. These resources are precious and was handled in an optimized way to yield the better results. The main focus of the research is to observe the existing scheduling algorithms and enhancements of the same. There are many scheduling algorithms available in the domain. Capacity scheduler is one of the scheduling algorithms used widely. The research on the improvements on the scheduling algorithms. Also, to check how to reduce the time taken to execute the MapReduce programs. newline