Automatic data plane testing
- Today's networks require much human intervention to keep them working. Every day network engineers wrestle with router misconfigurations, fiber cuts, faulty interfaces, mislabeled cables, software bugs, intermittent links and a myriad other issues that cause networks to misbehave, or fail completely. Network engineers hunt down bugs using the most rudimentary tools and track down root causes using a combination of accrued wisdom and intuition.We found that many network problems are associated with data plane behaviors, i.e., how the network transports data plane packets. This dissertation discusses the design and implementation of automatic data plane testing tools under various network scenarios. We first present Automatic Test Packet Generation (ATPG), a foundation framework of data plane testing when all data plane information is available and accurate. ATPG reads router configurations and generates a device-independent model. The model is used to generate a minimum set of test packets to (minimally) exercise every link in the network or (maximally) exercise every rule in the network. Test packets are sent periodically, and detected failures trigger a separate mechanism to localize the fault. NetSonar extends ATPG by allowing incomplete or inaccurate data plane information as inputs. Earlier test techniques were either white box (assumes complete forwarding knowledge) or black box (assumes no knowledge). We argue that the former is infeasible in large networks, and the latter is inefficient and incomplete. NetSonar is the first graybox tester for networks and the first tester deployed in a production network. NetSonar uses only coarse forwarding information and does not require knowledge of load balancing hash functions. Finally, we move our focus to data center networks with thousands of switches and millions of forwarding table entries. Data center owners use static analysis tools that examine the topology and forwarding tables to check for loops, black-holes and reachability failures. However, the existing tools do not scale to a large data center network. Moreover, no existing tool addresses the problem of potential false positives when analyzing a network snapshot, when the network state is constantly in flux. We present Libra, a tool for verifying forwarding tables in large data center networks that simplifies ATPG's data plane model to significantly improve verification performance.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|Stanford University, Department of Electrical Engineering.
|Varghese, George, 1960-
|Varghese, George, 1960-
|Statement of responsibility
|Submitted to the Department of Electrical Engineering.
|Thesis (Ph.D.)--Stanford University, 2014.
- © 2014 by Hongyi Zeng
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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