Big Data Analytics Test Bed
Abstract
The proliferation of big data has significantly expanded the quantity and breadth of information throughout the DoD. The task of processing and analyzing this data has become difficult, if not infeasible, using traditional relational databases. The Navy has a growing priority for information processing, exploitation, and dissemination, which makes use of the vast network of sensors that produce a large amount of big data. This capstone report explores the feasibility of a scalable Tactical Cloud architecture that will harness and utilize the underlying open-source tools for big data analytics. A virtualized cloud environment was built and analyzed at the Naval Postgraduate School, which offers a test bed, suitable for studying novel variations of these architectures. Further, the technologies directly used to implement the test bed seek to demonstrate a sustainable methodology for rapidly configuring and deploying virtualized machines and provides an environment for performance benchmark and testing. The capstone findings indicate the strategies and best practices to automate the deployment, provisioning and management of big data clusters. The functionality we seek to support is a far more general goal: finding open-source tools that help to deploy and configure large clusters for on-demand big data analytics.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2013
- Accession Number
- ADA589903
Entities
People
- Deyan M. Dontchev
- Javon S. Burden
- Rachel A. Doucet
- Thomas L. Skoff
Organizations
- Naval Postgraduate School