A Study on the Viability of Hadoop Usage on the Umfort Cluster for the Processing and Storage of CReSIS Polar Data
The primary focus of this research was to explore the capabilities of Hadoop as a software package to process, store and manage CReSIS polar data in a clustered environment. The investigation involved Hadoop functionality and usage through reviewed publications. The team’s research was aimed at determining if Hadoop was a viable software package to implement on the Elizabeth City State University (ECSU) Umfort computing cluster. Utilizing case studies processing, storage, management, and job distribution methods were compared. A final determination of the benefits of Hadoop for the storing and processing of data on the Umfort cluster was then made.


Hybrid Cloud Security: Replication and Direction of Sensitive Data Blocks
The primary focus of this research was to analyze the Hybrid Cloud security platform as proposed by Dr. Xiaofeng Wang and his research team. Large scale data sets in cloud computing environments carry inherent security concerns. The proposed platform involves code implementation and modification within the Hadoop Distributed File System as it pertains to parallel data processing. A hybrid cloud solution involves separating sensitive data which is confined to a private domain (private cloud), from non-sensitive data (public cloud). The specific research task was to create and modify java source code within the Hadoop Distributed File System, to implement alternative replication factors and test to verify that data was replicated to the proper domain (public or private) based on its security tag. Code was modified to change the replication factor of data and tested. Modified code was tested to see that data was distributed to public and private domains as tagged. This project is supported in part by National Science Foundation Grant CNS-0716292.