Secure MapReduce Power Iteration in the Cloud
Source: Wright State Athletics
With the development and wide deployment of web services, mobile applications, and sensor networks, data are now collected from many distributed sources to form big datasets. This paradigm poses a number of challenges on data storage and analysis. Typical data collectors have limited capacity to store and process large volumes of data and collected data may be highly sensitive requiring secure storage and processing. Processing and analyzing such large-scale data may also require a significant investment on the computing infrastructure which can be prohibitively expensive for many users. With these problems in mind, the authors envision a cloud-based data storage and processing framework that enables users to economically and securely handle big datasets.