With the rapid growth of emerging applications like social network, semantic web, sensor networks and LBS (Location Based Service) applications, a variety of data to be processed continues to witness a quick increase. Effective management and processing of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as...

Today’s cloud data applications, including Hadoop, Big Data, Search or Storage, are distributed applications running on server clusters with many-to-many communication patterns. The key to achieving predictable performance for these distributed applications is to provide consistent network bandwidth and latency to the various traffic flows since in most cases it is the slowest flow or query com...

Big data (BD) analytics has brought progressive improvement in the business environment. It provides businesses with optimized production, personalization and way production is dispersed. Nevertheless, conflicts arise use of these methods certain industries, like retail items, which usually basis on large-scale prolonged supply chain. The study develops a theoretical structure to investigate if...

Industry analysts describe Big Data in terms of three V’s: volume, velocity, variety. The data is too big to process with current tools; it arrives too fast for optimal storage and indexing; and it is too heterogeneous to fit into a rigid schema. There is a huge pressure on database researchers to study, explain, and solve the technical challenges in big data, but we find no inspiration in the ...