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Personal Decision Factors Considered By Information Technology Executives: Their Impacts On Business Intentions And Consequent Cloud Computing Services Adoption Rates, Marcus Lee Smith Jr
Personal Decision Factors Considered By Information Technology Executives: Their Impacts On Business Intentions And Consequent Cloud Computing Services Adoption Rates, Marcus Lee Smith Jr
Theses & Dissertations
During its infancy, the cloud computing industry was the province largely of small and medium-sized business customers. Despite their size, these companies required a professionally run, yet economical information technology (IT) operation. These customers used a total value strategy whereby they avoided paying for essential, yet underutilized, resources (e.g., full-time IT personnel and computing equipment with excess capacity) by outsourcing most, if not all, of their entire IT function. Since that time, the cloud industry has expanded the breadth of its service offerings greatly and the economies of scale have reduced the unit price point. In addition, research suggests other …
Automatic Scaling Hadoop In The Cloud For Efficient Process Of Big Geospatial Data, Zhenlong Li, Chaoweikai Yang, Kai Liu, Fei Hu, Baoxuan Jin
Automatic Scaling Hadoop In The Cloud For Efficient Process Of Big Geospatial Data, Zhenlong Li, Chaoweikai Yang, Kai Liu, Fei Hu, Baoxuan Jin
Faculty Publications
Efficient processing of big geospatial data is crucial for tackling global and regional challenges such as climate change and natural disasters, but it is challenging not only due to the massive data volume but also due to the intrinsic complexity and high dimensions of the geospatial datasets. While traditional computing infrastructure does not scale well with the rapidly increasing data volume, Hadoop has attracted increasing attention in geoscience communities for handling big geospatial data. Recently, many studies were carried out to investigate adopting Hadoop for processing big geospatial data, but how to adjust the computing resources to efficiently handle the …