What Should We Learn? Special Issue on Big Data Infrastructure I

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What Should We Learn? Special Issue on Big Data Infrastructure I

By: 
Yang Li

Big data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Big Data is an emerging paradigm encompassing various kinds of complex and large scale information beyond the processing capability of conventional software and databases. Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud computing platforms, Hadoop and Spark. Due to the multisource, massive, heterogeneous, and dynamic characteristics of application data involved in a distributed environment, one of the most important characteristics of Big Data is to carry out computing on the petabyte (PB), even the exabyte (EB)-level data with a complex computing process. Therefore, large-scale scalable Big Data Infrastructure with corresponding programming language support and software models for efficient processing in distributed environments such as cloud is on demand.

In the special issue on Big Data Infrastructure (Part I) published in IEEE Transactions on Big Data in June 2018, the editors invite articles on innovative research to address challenges of Big Data Infrastructure with emerging computing platforms such as heterogeneous clouds, hybrid architectures, Hadoop or Spark with emphasis on addressing real-time requirements imposed by emerging Big Data applications such as sensing data, e-commerce data, business transactions and web logs, and etc.

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