Maestro: Achieving scalability and coordination in centralizaed network control plane

Date
2012
Journal Title
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Abstract

Modem network control plane that supports versatile communication services (e.g. performance differentiation, access control, virtualization, etc.) is highly complex. Different control components such as routing protocols, security policy enforcers, resource allocation planners, quality of service modules, and more, are interacting with each other in the control plane to realize complicated control objectives. These different control components need to coordinate their actions, and sometimes they could even have conflicting goals which require careful handling. Furthermore, a lot of these existing components are distributed protocols running on large number of network devices. Because protocol state is distributed in the network, it is very difficult to tightly coordinate the actions of these distributed control components, thus inconsistent control actions could create serious problems in the network. As a result, such complexity makes it really difficult to ensure the optimality and consistency among all different components. Trying to address the complexity problem in the network control plane, researchers have proposed different approaches, and among these the centralized control plane architecture has become widely accepted as a key to solve the problem. By centralizing the control functionality into a single management station, we can minimize the state distributed in the network, thus have better control over the consistency of such state. However, the centralized architecture has fundamental limitations. First, the centralized architecture is more difficult to scale up to large network size or high requests rate. In addition, it is equally important to fairly service requests and maintain low request-handling latency, while at the same time having highly scalable throughput. Second, the centralized routing control is neither as responsive nor as robust to failures as distributed routing protocols. In order to enhance the responsiveness and robustness, one approach is to achieve the coordination between the centralized control plane and distributed routing protocols. In this thesis, we develop a centralized network control system, called Maestro, to solve the fundamental limitations of centralized network control plane. First we use Maestro as the central controller for a flow-based routing network, in which large number of requests are being sent to the controller at very high rate for processing. Such a network requires the central controller to be extremely scalable. Using Maestro, we systematically explore and study multiple design choices to optimally utilize modern multi-core processors, to fairly distribute computation resource, and to efficiently amortize unavoidable overhead. We show a Maestro design based on the abstraction that each individual thread services switches in a round-robin manner, can achieve excellent throughput scalability while maintaining far superior and near optimal max-min fairness. At the same time, low latency even at high throughput is achieved by Maestro's workload-adaptive request batching. Second, we use Maestro to achieve the coordination between centralized controls and distributed routing protocols in a network, to realize a hybrid control plane framework which is more responsive and robust than a pure centralized control plane, and more globally optimized and consistent than a pure distributed control plane. Effectively we get the advantages of both the centralized and the distributed solutions. Through experimental evaluations, we show that such coordination between the centralized controls and distributed routing protocols can improve the SLA compliance of the entire network.

Description
Degree
Doctor of Philosophy
Type
Thesis
Keywords
Applied sciences, Centralizaed network control plane, Network management, Open flow, Performance optimization, Computer science
Citation

Cai, Zheng. "Maestro: Achieving scalability and coordination in centralizaed network control plane." (2012) Diss., Rice University. https://hdl.handle.net/1911/70214.

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