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Growth of distributed systems using grid computing and softer aspects of E science

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  1. Abstract
  2. Introduction
  3. Grid computing
    1. what's grid computing?
    2. Grid computing model
  4. E-science: The softer aspects of the grid
    1. The current work in e-science
    2. Approaching e-science from a semiotic perspective
    3. Challenges to emerge from escience
  5. Conclusion
  6. Refrences

Grid computing and eScience are two major areas of growth of distributed systems. The grid concept refers to the virtualization of computing resources in the sense that end-users should have the illusion of using a single source of computing power without knowing the locality of the computation. Examples of this virtualization are the use of digital certificates to access systems on behalf of the user, third party file transfer between machines authenticated via certificates, client tools for workflow composition with the workflow being consigned by agents such as brokers. eScience is allied to the grid concept, it refers to new methods of utilizing grid and other forms of distributed computation with a particular emphasis on collaborative working by geographically distributed teams. This paper aims to: explain the concept of eScience and its importance in future problem solving IT infrastructure, explain the concept of grid computing and its relation to eScience. it also familiarize with the key abstractions underpinning the grid concepts; outline current grid solutions and how they are intended to evolve. Keywords: Grid Computing, Intra-grid, Inter-grid, eScience, softer

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