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A Review of Data Intensive Computing

Data intensive computing is a common research problem in science, industry and computer academia. In recent twenty years, the explosive growth of science data has appeared all over the world. Typical data intensive computing applications include Internet text data processing, scientific research data processing, large scale graph computing, inverse and perspective problems. Data intensive computing research faces challenges of scalability of massive data management and processing, integrated data processing technology, system management, new transaction demand, unstructured data processing, service mode, good fault tolerance and high availability. Appropriate data intensive computing programming model needs to be suitable for large scale data sets parallel computing, multiple virtual machine task scheduling and constructing new data intensive computing applications. As a typical data intensive application, aerosol inverse computing I/O data volume is analyzed. Although industry and academia has brought some methods for data intensive applications, scientific discovery problems with both data intensive and computation intensive features are still no appropriate solution at present. Keywordsdata intensive computing, Big data, parallel