Fine-Grained Control of Control-Plane Performance: Use Cases and Mechanisms
draft-li-cp-usecases-00

Abstract

It is commonly assumed that a system controller or network management system has complete knowledge of the data plane, especially in a software-defined network (SDN). That is, the controller knows performance metrics such as the flow table size of each switch, the rate of rule updates between a switch control plane and its data plane, and the maximum latency to install a rule in the flow table of a switch. However, in reality, this is not the case. Measurement studies show that the flow table size depends on the structure of the rules installed. The flow table size is much smaller if there are many wild card rules. The setup latency also depends on the already installed rules. If there are many wild card rules installed, the latency can be much higher. Currently, data centers pre-setup the rules long before the actual associated traffic starts to flow through the network. This puts constraints on the use cases. In this document, we first show that many use cases demand a more predictable control plane. The use cases are applied to networks that require control-plane performance information for dynamic configuration, as well as SDN networks. We then discuss potential mechanisms to enable fine-grained control of control-plane performance.

Authors

Li Erran Li
Yan Luo
Haibin Song
Y. Richard Yang

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