Jan Medved
- Computer Networks and Communications top 2%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Information Systems top 10%
- Signal Processing
- Co-authors
- Robert VargaKen GrayTony BatesPei CaoWing Hong ChanIna MineiStefano PrevidiBruce S. Davie
- Topics
- Caching and Content Delivery (3 papers)Software-Defined Networks and 5G (3 papers)Network Traffic and Congestion Control (3 papers)
- Partner nations
- United StatesChina
In The Last Decade
Jan Medved
14 papers receiving 711 citations
Hit Papers
Peers
Comparison fields: 5 of 31
- Computer Networks and Communications 715
- Electrical and Electronic Engineering 200
- Artificial Intelligence 119
- Information Systems 92
- Signal Processing 30
Countries citing papers authored by Jan Medved
This map shows the geographic impact of Jan Medved's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jan Medved with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Medved more than expected).
Fields of papers citing papers by Jan Medved
This network shows the impact of papers produced by Jan Medved. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jan Medved. The network helps show where Jan Medved may publish in the future.
Co-authorship network of co-authors of Jan Medved
This figure shows the co-authorship network connecting the top 25 collaborators of Jan Medved. A scholar is included among the top collaborators of Jan Medved based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jan Medved. Jan Medved is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | A Data Model for Network Topologies | 5 |
| 2 | OpenDaylight: Towards a Model-Driven SDN Controller architecturebreakdown → | 407 |
| 3 | Topology API Use Cases | 4 |
| 4 | Routing Information Base Info Model | 1 |
| 5 | MPLS-TP Pseudowire Configuration using OpenFlow 1.3 | 2 |
| 6 | North-Bound Distribution of Link-State and TE Information using BGP | 22 |
| 7 | PCEP Extensions for Stateful PCE | 45 |
| 8 | Topology API Requirements | 1 |
| 9 | Use Cases for ALTO within CDNs | 8 |
| 10 | CDNI Footprint Advertisement | 1 |
| 11 | ALTO Network-Server and Server-Server APIs | 2 |
| 12 | ALTO and Content Delivery Networks | 1 |
| 13 | Advertising Link-State Information in BGP | 1 |
| 14 | 13 | |
| 15 | 244 |
About Jan Medved
Jan Medved is a scholar working on Software, Computer Networks and Communications and Hardware and Architecture, having authored 15 papers that have together received 757 indexed citations. Recurring topics across this work include Caching and Content Delivery (3 papers), Software-Defined Networks and 5G (3 papers) and Network Traffic and Congestion Control (3 papers). The work is most often cited by research in Computer Networks and Communications (715 citations), Information Systems (92 citations) and Artificial Intelligence (119 citations). Jan Medved has collaborated with scholars based in United States and China. Frequent co-authors include Robert Varga, Ken Gray, Tony Bates, Pei Cao, Wing Hong Chan, Ina Minei, Stefano Previdi, Bruce S. Davie, Adrian Farrel and Thomas Nadeau.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.