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Xenofontas Dimitropoulos

Researcher at University of Crete

Publications -  126
Citations -  4278

Xenofontas Dimitropoulos is an academic researcher from University of Crete. The author has contributed to research in topics: The Internet & Border Gateway Protocol. The author has an hindex of 34, co-authored 125 publications receiving 3966 citations. Previous affiliations of Xenofontas Dimitropoulos include Foundation for Research & Technology – Hellas & IBM.

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Re-mapping the Internet: Bring the IXPs into Play.

TL;DR: A network graph model based on IXPs and their AS memberships is introduced, which aims to complement previous modeling efforts, shed light on unexplored characteristics of the Internet topology, and support new research directions.
Proceedings ArticleDOI

FaRNet: fast recognition of high multi-dimensional network traffic patterns

TL;DR: This paper introduces a fundamentally new approach for extracting HHHs based on generalized frequent item-set mining (FIM), which allows to process traffic data much more efficiently and scales to much higher dimensional data than present schemes.
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Improving Networked Music Performance Systems Using Application-Network Collaboration

TL;DR: The proposed approach introduces an integration of dynamic audio and network configuration to satisfy the EPT constraint, and the basic idea is that, the major components participating in an NMP system, the application and the network interact during the live music performance.
Proceedings ArticleDOI

O Peer, Where Art Thou? Uncovering Remote Peering Interconnections at IXPs

TL;DR: This work introduces and validate a heuristic methodology for discovering remote peers at IXPs and observes that remote peering is a significantly common practice in all the studied IXPs; for the largest IXPs, remote peers account for 40% of their member base.
Proceedings ArticleDOI

K-sparse approximation for traffic histogram dimensionality reduction

TL;DR: This work reorders the traffic histogram and uses the top-K coefficients of the reordered histogram to approximate the original histogram, which exhibits a power-law distribution, based on which a relationship between K and the resulting approximation error is established.