Distributed Computing and Networking By ,Prasad Jayanti,Sanjoy Kumar Saha
In recent years, the rapid advances being made in computer technology have ensured that large sections of the world population have been able to gain easy access to computers on account of falling costs worldwide, and their use is now commonplace in all walks of life. Government agencies, scientific, business and commercial organizations are routinely using computers not just for computational purposes but also for storage, in massive databases, of the immense volumes of data that they routinely generate, or require from other sources. Large-scale computer networking has ensured that such data has become accessible to more and more people. In other words, we are in the midst of an information explosion, and there is urgent need for methodologies that will help us bring some semblance of order into the phenomenal volumes of data that can readily be accessed by us with a few clicks of the keys of our computer keyboard. Traditional statistical data summarization and database management techniques are just not adequate for handling data on this scale, and for extracting intelligently, information or, rather, knowledge that may be useful for exploring the domain in question or the phenomena responsible for the data, and providing support to decision-making processes. This quest had thrown up some new phrases, for example, data mining [1, 2] and knowledge discovery in databases (KDD).
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