Share Email Print

Proceedings Paper

OpenTap: software defined data acquisition
Author(s): Christian Macias; Venkat Dasari; Michael P. McGarry
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

We present OpenTap, a unified interface designed as an Infrastructure layer technology for a software-defined network measurement (SDNM) stack. OpenTap provides invocations for remotely capturing network data at various granularities, such as packet or NetFlow. OpenTap drivers can be developed that leverage open source network measurement tools such as tcpdump and nfdump. OpenTap software can be used to turn any computing device with network interfaces into a remotely controlled network data collection device. Although OpenTap was designed for SDNM, its interface generalizes to any data acquisition thereby providing software-defined data acquisition (SDDA). We illustrate this generality with OpenTap drivers that leverage Phidgets USB sensors to remotely capture environmental data such as temperature. We have completed an implementation of OpenTap that uses a REST API for the invocations. Using that implementation, we study a few use cases of OpenTap for automated network management and network traffic visualizations to characterize its utility for those applications. We find that OpenTap empowers rapid development of software for more complex network measurement functionality at the Control layer such as, joining network data with other sources, and creating network data aggregates such as traffic matrices. OpenTap significantly lowers the cost and development barrier to large-scale data acquisition thereby bringing data acquisition and analytics to an unprecedented number of users. Finally, at the Application layer, network measurement applications such as traffic matrix visualizations are easily implemented leveraging OpenTap at the Infrastructure layer in addition to the Control layer. All of these data processing software systems will be open source and available on GitHub by the time of the conference.

Paper Details

Date Published: 9 May 2018
PDF: 9 pages
Proc. SPIE 10652, Disruptive Technologies in Information Sciences, 1065207 (9 May 2018); doi: 10.1117/12.2305456
Show Author Affiliations
Christian Macias, The Univ. of Texas at El Paso (United States)
Venkat Dasari, U.S. Army Research Lab. (United States)
Michael P. McGarry, The Univ. of Texas at El Paso (United States)

Published in SPIE Proceedings Vol. 10652:
Disruptive Technologies in Information Sciences
Misty Blowers; Russell D. Hall; Venkateswara R. Dasari, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?