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Anja Feldmann
Researcher at Max Planck Society
Publications - 368
Citations - 18932
Anja Feldmann is an academic researcher from Max Planck Society. The author has contributed to research in topics: The Internet & Antigen. The author has an hindex of 67, co-authored 340 publications receiving 17422 citations. Previous affiliations of Anja Feldmann include Saarland University & AT&T.
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Proceedings ArticleDOI
On dominant characteristics of residential broadband internet traffic
TL;DR: Observations from monitoring the network activity for more than 20,000 residential DSL customers in an urban area find that HTTP - not peer-to-peer - traffic dominates by a significant margin and that the DSL lines are frequently not the bottleneck in bulk-transfer performance.
Journal ArticleDOI
Deriving traffic demands for operational IP networks: methodology and experience
TL;DR: This paper presents a model of traffic demands to support traffic engineering and performance debugging of large Internet Service Provider networks, and shows how to infer interdomain traffic demands using measurements collected at a smaller number of edge links-the peering links connecting the neighboring providers.
Proceedings ArticleDOI
Live wide-area migration of virtual machines including local persistent state
TL;DR: By combining a block-level solution with pre-copying and write throttling, it is shown that an entire running web server can be transferred, including its local persistent state, with minimal disruption.
Proceedings ArticleDOI
Data networks as cascades: investigating the multifractal nature of Internet WAN traffic
TL;DR: A simple construction based on cascades that allows for a plausible physical explanation of the observed multifractal scaling behavior of data traffic and suggests that the underlying multiplicative structure is a traffic invariant for WAN traffic that co-exists with self-similarity is provided.
Proceedings ArticleDOI
Dynamics of IP traffic: a study of the role of variability and the impact of control
TL;DR: It is shown that scaling analysis has the ability to extract relevant information about the time-scale dynamics of Internet traffic, thereby, it is hoped, making these techniques available to a larger segment of the networking research community.