Adaptive Load Sensing and Rebalancing for Distributed File System in Cloud Environment

Abstract

Large scale distributed systems such as cloud computing applications are becoming very common. These applications come with increasing challenges on how to transfer and where to store and compute data. This system presents an innovative idea in cloud computing. In a giant cloud we are able to add thousands of nodes together. The main aim is to allot files to those nodes while not creating significant load to any of the nodes, for that files square measure partitioned off into completely different modules. Another objective is to cut back the network inconsistencies and network traffic attributable to the unbalancing of hundreds. The reduction of network inconsistency can result in maximization of network information measure in order that so many numerous such a big amount of, such a giant amount of, such a lot of large applications will run in it. Because of ability to quantify property, we are able to add, delete, update new nodes in order that it supports heterogeneousness of the system. To enhance the potential of nodes we tend to use Distributed fi le system in Cloud Computing Applications.

Keywords

fi le system, Cloud, Chunk server, Rebalance

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