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dc.contributor.authorKanuparthy, Partha V.en_US
dc.date.accessioned2013-01-17T22:06:10Z
dc.date.available2013-01-17T22:06:10Z
dc.date.issued2012-11-15en_US
dc.identifier.urihttp://hdl.handle.net/1853/45938
dc.description.abstractInference, measurement and estimation of network path properties is a fundamental problem in distributed systems and networking. We consider a specific subclass of problems which do not require special support from the hardware or software, deployment of special devices or data from the network. Network inference is a challenging problem since Internet paths can have complex and heterogeneous configurations. Inference enables end users to understand and troubleshoot their connectivity and verify their service agreements; it has policy implications from network neutrality to broadband performance; and it empowers applications and services to adapt to network paths to improve user quality of experience. In this dissertation we develop end-to-end user-level methods, tools and services for network inference. Our contributions are as follows. We show that domain knowledge-based methods can be used to infer performance of different types of networks, containing wired and wireless links, and ranging from local area to inter-domain networks. We develop methods to infer network properties: 1. Traffic discrimination (DiffProbe), 2. Traffic shapers and policers (ShaperProbe), and 3. Shared links among multiple paths (Spectral Probing). We develop methods to understand network performance: 1. Diagnose wireless performance pathologies (WLAN-probe), and 2. Diagnose wide-area performance pathologies (Pythia). Among our contributions: We have provided ShaperProbe as a public service and it has received over 1.5 million runs from residential and commercial users, and is used to check service level agreements by thousands of residential broadband users a day. The Federal Communications Commission (FCC) has recognized DiffProbe and ShaperProbe with the best research award in the Open Internet Apps Challenge in 2011. We have written an open source performance diagnosis system, Pythia, and it is being deployed in ISPs such as the US Department of Energy ESnet in wide-area inter-domain settings. The contributions of this dissertation enable Internet transparency, performance troubleshooting and improving distributed systems performance.en_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectDiagnosisen_US
dc.subjectMeasurementen_US
dc.subjectInferenceen_US
dc.subjectToolsen_US
dc.subjectSystemsen_US
dc.subject.lcshInternet
dc.subject.lcshNetwork performance (Telecommunication)
dc.subject.lcshSystems engineering
dc.titleEnd-to-end inference of internet performance problemsen_US
dc.typeDissertationen_US
dc.description.degreePhDen_US
dc.contributor.departmentComputingen_US
dc.description.advisorCommittee Chair: Dovrolis, Constantine; Committee Member: Ammar, Mostafa; Committee Member: Claffy, Kimberly; Committee Member: Papagiannaki, Konstantina; Committee Member: Zegura, Ellenen_US


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