Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Operating system support for planetary-scale network services
NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
iPlane: an information plane for distributed services
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Accurate and efficient SLA compliance monitoring
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Detecting in-flight page changes with web tripwires
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Uncovering performance differences among backbone ISPs with Netdiff
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Answering what-if deployment and configuration questions with wise
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The internet is not a big truck: toward quantifying network neutrality
PAM'07 Proceedings of the 8th international conference on Passive and active network measurement
Perspectives on tracing end-hosts: a survey summary
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Diffprobe: detecting ISP service discrimination
INFOCOM'10 Proceedings of the 29th conference on Information communications
Proceedings of the 2010 ACM SIGCOMM workshop on Home networks
Glasnost: enabling end users to detect traffic differentiation
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
Netalyzr: illuminating the edge network
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
ACM SIGCOMM Computer Communication Review
SEPIA: privacy-preserving aggregation of multi-domain network events and statistics
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Privacy-preserving distributed network troubleshooting—bridging the gap between theory and practice
ACM Transactions on Information and System Security (TISSEC)
Chkdiff: checking traffic differentiation at internet access
Proceedings of the 2012 ACM conference on CoNEXT student workshop
Splitting the bill for mobile data with SIMlets
Proceedings of the 14th Workshop on Mobile Computing Systems and Applications
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We present NANO, a system that detects when ISPs apply policies that discriminate against specific classes of applications, users, or destinations. Existing systems for detecting discrimination are typically specific to an application or to a particular discrimination mechanism and rely on active measurement tests. Unfortunately, ISPs can change discrimination policies and mechanisms, and they can evade these tests by giving probe traffic higher priority. NANO detects ISP discrimination by passively collecting performance data from clients. To distinguish discrimination from other causes of degradation (e.g., overload, misconfiguration, failure), NANO establishes a causal relationship between an ISP and observed performance by adjusting for confounding factors. NANO agents deployed at participating clients across the Internet collect performance data for selected services and report this information to centralized servers, which analyze the measurements to establish causal relationship between an ISP and performance degradations. We have implemented NANO and deployed clients in a controlled environment on Emulab. We run a combination of controlled experiments on Emulab and wide-area experiments on PlanetLab that show that NANO can determine the extent and criteria for discrimination for a variety of discrimination policies and applications.