| Autor: |
Dow Street, Rahul Amin, Thomas Goff, Igor Pedan, Bow-Nan Cheng, Chayil Timmerman, Larry Bressler, Terry Gibbons, Scott Arbiv |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
MILCOM |
| DOI: |
10.1109/milcom47813.2019.9020979 |
| Popis: |
The U.S. Department of Defense (DoD) has invested significantly in development and deployment of aerial high-capacity backbone (HCB) networks. Understanding the performance of these Mobile Ad-Hoc Networks (MANETs) is challenging, and requires insight into multiple layers of the protocol stack. Tons of data get generated at each layer of the stack. MIT LL has developed a data collection and visualization framework to parse through important data and help monitor and analyze the performance of these networks. The HCB data collection and analysis framework is comprised of pluggable data collection and reporting daemons, a persistent storage component based on a time-series database, and a visualization dashboard capable of displaying network performance metrics in real-time and playback modes. In this paper, we showcase the capabilities of this framework, identifying how it has helped further our research, and how it can be adapted to support other similar research programs that generate tons of data. 11DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited. This material is based upon work supported by the Department of the Navy under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of the Navy. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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