Guest editorial: Special issue on data intensive cloud computing

Abstract

Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, and cloud computing platforms. Big data is an emerging research area which requires new technologies to efficiently process large quantities of data within tolerable elapsed times. Cloud computingwhich promises to accommodate a huge volume of data and its processing is in a position as a promising technology to deal with big data issues. This special issue is focusing on this new strategic research area to address how to use cloud computing to process big data intensive applications. This special issue has selected five papers. The first three papers are related to workflows: service selection, monitoring and scheduling. The fourth paper is related to the emerging new applications on location selection, whereas the fifth paper is related to data security. We next present the summary of the papers presented in this special issue. The modern workflow management systems are developed using the serviceoriented approach, where independent services provided by different service providers