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Gábor Rétvári

Researcher at Budapest University of Technology and Economics

Publications -  100
Citations -  1216

Gábor Rétvári is an academic researcher from Budapest University of Technology and Economics. The author has contributed to research in topics: Routing protocol & Static routing. The author has an hindex of 18, co-authored 93 publications receiving 1025 citations. Previous affiliations of Gábor Rétvári include Ericsson.

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Journal ArticleDOI

Survey of Performance Acceleration Techniques for Network Function Virtualization

TL;DR: This paper provides a comprehensive overview of the host-based network function virtualization (NFV) ecosystem, covering a broad range of techniques, from low-level hardware acceleration and bump-in-the-wire offloading approaches to high-level software acceleration solutions, including the virtualization technique itself.
Proceedings ArticleDOI

Compressing IP forwarding tables: towards entropy bounds and beyond

TL;DR: In this paper, a static entropy-compressed FIB representation with asymptotically optimal lookup is presented, with essentially zero cost on longest prefix match and FIB update.
Proceedings ArticleDOI

IP fast ReRoute: Loop Free Alternates revisited

TL;DR: This paper revisits LFA in order to give theoretical insights and practical hints to LFA failure coverage analysis and concludes that cleverly adding just a couple of new links can improve the quality of LFA protection drastically.
Journal ArticleDOI

Navigable networks as Nash equilibria of navigation games

TL;DR: It is shown that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks and these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain.
Proceedings ArticleDOI

Dataplane Specialization for High-performance OpenFlow Software Switching

TL;DR: This paper introduces ESwitch, a novel switch architecture that uses on-the-fly template-based code generation to compile any OpenFlow pipeline into efficient machine code, which can then be readily used as fast path.