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This paper describes the research work done for during PhD study. Cluster computing, grid computing and cloud computing are distributed computing environments (DCEs) widely accepted for the next generation Web based commercial and scientific applications. These applications work around the globally distributed data of petabyte scale that can only be processed by the aggregating the capability of globally distributed resources. The resource management and process scheduling in large scale distributed computing environment are a challenging task. In this research work we have devised new scheduling algorithms and resource management strategies specially designed for the cluster and grid cloud and peer-to-peer computing. The research work finally presented the distributed computing solutions to one scientific and one commercial application viz. e-Learning and data mining.

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This paper presents a Generic Data Access and Integration Service GDAIS for various distributed computing environments. The service can be deployed within Peer-to-Peer, Cluster, Grid and Cloud computing environment. Grid service environment has been utilized to develop GDAIS and it provides the generic data access facility to the clients. The clients can manipulate data stored in various data stores in transparent manner. The service supports simplified access to a variety of sources like the files on file system, web services and various databases like XML databases, relation databases, object oriented databases and object relational databases. A uniform API to manipulate data from disparate and heterogeneous data sources is developed. Various operations that can be performed are 'read', 'select', 'insert', 'update',' delete' and 'bulk insert'. These APIs are developed as web services.