Comparative Analysis, Security Aspects & Optimization of Workload in Gfs Based Map Reduce Framework in Cloud System

This paper discusses a propose cloud infrastructure that combines On-Demand allocation of resources with improved utilization, opportunistic provisioning of cycles from idle cloud nodes to other processes It provides fault tolerance while running on inexpensive commodity hardware, and it delivers high aggregate performance to a large number of clients.Because for cloud computing to avail all the demanded services to the cloud consumers is very difficult. It is a major issue to meet cloud consumer's requirements. Hence On-Demand cloud infrastructure using map reduce configuration with improved CPU utilization and storage utilization is proposed using Google File System by using Map-Reduce. Hence all cloud nodes which remains idle are all in use and also improvement in security challenges and achieves load balancing and fast processing of large data in less amount of time. Here we compare the FTP and GFS for file uploading and file downloading; and enhance the CPU utilization and storage utilization and fault tolerance,. Cloud computing moves the application software and databases to the large data centres, where the management of the data and services may not be fully trustworthy. Therefore this security problem is solve by encrypting the data using encryption/decryption algorithm and Map-Reducing algorithm which solve the problem of utilization of all idle cloud nodes for larger data.