Abstract
Implementing a distributed process using object oriented programming is challenging especially for clusters of nodes ensuring the availability. Java happens to be well suited for writing object oriented programs for applications which needs modularity and high degree of cohesion [2]. In this paper our objective is to propose appropriate programming paradigms for loosely coupled distributed and object-oriented systems with a specific focus on parallel programming and client-server object computing. We select a prototype tool made based on the research outcome as found in [1] for this purpose. This research prototype tool ‘Vishwa’ provides a very good starting point for graduate students, engineers and scientists in academia, industry and government to present their tasks using the aspects of parallel and distributed computing. The learning curve is shorter in the domain of grid due to the simplicity in deploying and processing with this tool. We also demonstrate with a case study for bringing out the easiness in splitting the given job into subtasks and executed in this type of grid environmentKeywords: Grid Computing, Distributed Computing, Object Oriented Programming, Speedup Ratio, Middleware.
Highlights
Grid computing technology has found its place in numerous scientific projects, has been adopted by numerous governments, and has been widely used for commercial projects
Grid computing is suitable for resource-demanding projects and enables scientists to work in a completely new way [3]
Grid computing is a type of data management and computer infrastructure, designed as a support primarily for scientific research
Summary
Grid computing technology has found its place in numerous scientific projects, has been adopted by numerous governments, and has been widely used for commercial projects. Grid computing is a type of data management and computer infrastructure, designed as a support primarily for scientific research. It is used in various commercial concepts, business research, entertainment and by governments of different countries. The grid computing concept integrates four components: information, computation, networking and communication [2]. It has been made as a vision as a global networking infrastructure connecting multiple high performance computational resources. Typical applications [5] were implemented as Supercomputing across globe like ‘ Distributed Tera scale Facility’ (DTF), Collaborative Computing ‘ as in GriPhyN (Grid Physics Network) and ‘ Global data repository and data intensive computing’ realized as ‘ iVDgL’ (international Virtual-Data grid Lab)
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