Efficient data stream management Using adaptive clustered indexing And dynamic heuristic Optimization approach

Abstract

Data streams are of infinite size and continuously flow at very high newlinespeeds.Realtime data streams produce a continuous flow of data that is newlinedynamic and time variant In the modern era highly dynamic heterogeneous newlineand large volumes of data are continuously generated from various newlineapplications such as sensor networks social media telecommunications newlinestock market analysis the internet and network monitoring Continuous newlinestream data processing is one of the challenging issues to process realtime newlinedata which comes as streams and dynamically change according to the rate of newlineincoming data Effective processor is needed to process large amounts of newlinetimedependent data Huge volume of data can be processed and handled newlineeffectively by splitting the data into partitions as clusters and efficient newlineindexing newline newline