Making historical connections: Building Application Layer Traffic Optimization (ALTO) network and cost maps from public broadband data
作者： Vijay K. Gurbani , David Goergen , Radu State , Thomas Engel
DOI: 10.1109/CNSM.2014.7014158
关键词: Network topology 、 Network architecture 、 Computer science 、 Computer network 、 Identifier 、 Social network analysis (criminology) 、 Broadband 、 Broadband networks 、 Network mapping 、 Service provider
摘要: The Application Layer Traffic Optimization (ALTO) protocol allows network service providers to make available a pair of maps applications such that the can intelligently (compared randomly) connect desired resource. map aggregates provider into defined identifiers (PID) and cost provides pair-wise link between each PID. Clearly, has an authoritative view its is able provide ALTO server distributes maps. However, also envisions third-parties as being In this paper, we demonstrate how third-party by mining public information. Specifically, build our from United States Federal Communications Commission broadband data set, which contains expressive (multi-tier wireline measurements) rich (measurements for specific application uses) dataset. all, examined over 1 billion records spread 90 GBytes part analysis. We borrow concepts financial engineering social analysis show topology be created, furthermore, peer-to-peer systems insulate themselves going dark choosing supernodes effectively historical data.
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