Jesse Chen

Date of Award


Document Type



Santa Clara : Santa Clara University, 2021.

Degree Name

Master of Science (MS)


Computer Science and Engineering

First Advisor

Behnam Dezfouli


The southbound control protocols used in Software Defined Networks (SDNs) allow for centralized control and management of the data plane. However, these protocols introduce additional traffic and delay between network controllers and switches. Despite the well understood capabilities of SDNs, current representations of control traffic overhead consist of approximations at best. In addition to high reactivity to incoming flows, the need for resource allocation and deterministic messaging delay necessitates a thorough understanding and modeling of the amount of control traffic and its effect on latency. Software switching facilitates the development of edge and fog computing networks by allowing the use of commodity hardware for both data processing and packet switching. Despite these benefits, characterizing and ensuring deterministic performance with software switches is harder, in comparison to physical switching appliances. In particular, achieving deterministic performance is essential to adopt software switching in mission-critical applications, especially those deployed in edge and fog computing architectures. In this work, we capture the network overhead of various switch configurations on a testbed and extract mathematical models to predict expected overhead for arbitrary switch configurations. We demonstrate that controllerswitch traffic patterns are non-negligible and can be accurately modelled to compute the bandwidth utilization of controller-switch communication. We then study the impact of Open vSwitch (OVS) packet scheduler configurations on bandwidth slicing and predictable packet latency. We demonstrate that latency and predictability are dependent on the implementation of the packet scheduling mechanism and that the packet schedulers used in OVS Kernel-Path and OVS-DPDK each focus on different aspects of switching performance.

Available for download on Thursday, June 16, 2022