J
Jia Wang
Researcher at AT&T Labs
Publications - 144
Citations - 10291
Jia Wang is an academic researcher from AT&T Labs. The author has contributed to research in topics: Network packet & The Internet. The author has an hindex of 49, co-authored 135 publications receiving 9891 citations. Previous affiliations of Jia Wang include Hebei University & AT&T.
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Proceedings ArticleDOI
Towards automated performance diagnosis in a large IPTV network
TL;DR: This paper focuses on characterizing and troubleshooting performance issues in one of the largest IPTV networks in North America, and develops a novel diagnosis tool called Giza that is specifically tailored to the enormous scale and hierarchical structure of the IPTV network.
Proceedings ArticleDOI
On AS-level path inference
TL;DR: RouteScope-a tool for inferring AS-level paths by finding the shortest policy paths in an AS graph obtained from BGP tables collected from multiple vantage points and a novel scheme to infer the first AS hop by exploiting the TTL information in IP packets is described.
Proceedings ArticleDOI
Finding a needle in a haystack: pinpointing significant BGP routing changes in an IP network
TL;DR: The design and evaluation of an online system that converts millions of BGP update messages a day into a few dozen actionable reports about significant routing disruptions are presented and validation using other data sources confirms the accuracy of the algorithms and the tool's additional value in detecting routing disruptions.
Proceedings ArticleDOI
A light-weight distributed scheme for detecting ip prefix hijacks in real-time
TL;DR: This work proposes a different approach to hijacking detection that utilizes information collected mostly from the data plane and is able to detect prefix hijacking with high accuracy in a light-weight, distributed, and real-time fashion.
Proceedings ArticleDOI
Understanding the impact of network dynamics on mobile video user engagement
TL;DR: This paper presents the first large-scale study characterizing the impact of cellular network performance on mobile video user engagement from the perspective of a network operator, and quantifies the effect that 31 different network factors have on user behavior in mobile video.