Regression-Based Analytics for Response Dynamics of SDN Solutions and Components
We consider Software-Defined Network (SDN) solutions that dynamically setup and teardown connections, and also their response dynamics of connectivity and TCP throughput. There is a wide variety of choices for controllers, switches, andsoftware modules, and objective analytics of measurements are needed to compare the response dynamics of solutions based on their combinations. Throughput and ping measurements during connection changes contain significant statistical variations due to the complexities of controllers, northbound scripts, and network devices. We propose analytical methods to estimate response regression functions, which provide a rigorous and objective comparison of different SDN solutions and their components, namely, controllers, switches, and OpenFlow versions. We apply this approach in two scenarios: (a) switching of long-haul connections emulated in hardware by ANUE devices over a testbed consisting of HP and Cisco switches, and (b) multi-site science infrastructure emulated using VMs and Mininet. The results provide useful practical insights including: (i) the dpctl method responds seconds faster than the OpenDayLight (ODL) method on average under OpenFlow 1.0, but performs similar to ODL under OpenFlow 1.3, and (ii) the ping response of dpctl is about 0.6 sec faster than ODL for the second scenario.
- Research Organization:
- Brookhaven National Lab. (BNL), Upton, NY (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (SC-21)
- DOE Contract Number:
- SC0012704
- OSTI ID:
- 1476282
- Report Number(s):
- BNL-209114-2018-COPA
- Resource Relation:
- Conference: Workshop on Emerging Trends in Softwarized Networks, in conjunction with IEEE Conference on Network Softwarization, Montreal Canada, 6/25/2018 - 6/28/2018
- Country of Publication:
- United States
- Language:
- English
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