Toward Automated Network Management and Operations
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Network management plays a fundamental role in the operation and well-being of today's networks. Despite the best effort of existing support systems and tools, management operations in large service provider and enterprise networks remain mostly manually performed by network operators. Due to the larger scale of modern networks, more complex network functionalities, and higher network dynamics, human operators are increasingly short-handed. As a result, network misconfigurations frequently occur, causing violated service-level agreements and degraded user experience. In this dissertation, we develop various tools and systems to understand, automate, augment, and evaluate network management operations. Our thesis is that by introducing formal abstractions, like DFA, Petri-Net and database, we can build new support systems that systematically capture domain knowledge, automate network management operations, enforce network-wide properties to prevent misconfigurations, and at the same
time reduce manual effort. The common approach of our systems is to build a knowledge plane, which is based on the proposed abstractions, allowing network-wide reasoning and guidance to the progression of network operations. More importantly, they require no modification to the existing Internet infrastructure and network devices, thus allow quicker adoption. Finally, to address the current limitations and difficulty in evaluating novel network management systems, we design a distributed network testing platform, which relies on network and device virtualization to provide realistic environments and isolationto production networks.