Frank Lehrieder
- Computer Networks and Communications top 5%
- Electrical and Electronic Engineering
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Information Systems
- Co-authors
- Tobias HoßfeldSimon OechsnerMichael MenthMichael JarschelRastin PriesGyörgy DánChristian SchwartzWolfgang Kellerer
- Topics
- Caching and Content Delivery (17 papers)Peer-to-Peer Network Technologies (16 papers)Network Traffic and Congestion Control (13 papers)
- Cited by
- Computer Networks and CommunicationsArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- IEEE Communications Surveys & TutorialsIEEE/ACM Transactions on NetworkingComputer Networks
- Partner nations
- GermanySwedenSwitzerland
In The Last Decade
Frank Lehrieder
28 papers receiving 321 citations
Peers
Comparison fields: 5 of 33
- Computer Networks and Communications 306
- Electrical and Electronic Engineering 68
- Artificial Intelligence 66
- Computer Vision and Pattern Recognition 40
- Information Systems 28
Countries citing papers authored by Frank Lehrieder
This map shows the geographic impact of Frank Lehrieder'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 Frank Lehrieder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Lehrieder more than expected).
Fields of papers citing papers by Frank Lehrieder
This network shows the impact of papers produced by Frank Lehrieder. 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 Frank Lehrieder. The network helps show where Frank Lehrieder may publish in the future.
Co-authorship network of co-authors of Frank Lehrieder
This figure shows the co-authorship network connecting the top 25 collaborators of Frank Lehrieder. A scholar is included among the top collaborators of Frank Lehrieder 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 Frank Lehrieder. Frank Lehrieder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 8 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 5 | |
| 6 | 0 | |
| 7 | Comparison of Marking Algorithms for PCN-Based Admission Control | 0 |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 19 | |
| 11 | 9 | |
| 12 | 14 | |
| 13 | 11 | |
| 14 | 18 | |
| 15 | 3 | |
| 16 | 17 | |
| 17 | 7 | |
| 18 | 19 | |
| 19 | 14 | |
| 20 | Edge-Assisted Marked Flow Termination | 2 |
About Frank Lehrieder
Frank Lehrieder is a scholar working on Computer Networks and Communications, Artificial Intelligence and Computer Science Applications, having authored 30 papers that have together received 331 indexed citations. Recurring topics across this work include Caching and Content Delivery (17 papers), Peer-to-Peer Network Technologies (16 papers) and Network Traffic and Congestion Control (13 papers). The work is most often cited by research in Computer Networks and Communications (306 citations), Artificial Intelligence (66 citations) and Computer Vision and Pattern Recognition (40 citations). Frank Lehrieder has collaborated with scholars based in Germany, Sweden and Switzerland. Frequent co-authors include Tobias Hoßfeld, Simon Oechsner, Michael Menth, Michael Jarschel, Rastin Pries, György Dán, Christian Schwartz, Wolfgang Kellerer, Zoran Despotovic and Phuoc Tran‐Gia. Their work appears in journals such as IEEE Communications Surveys & Tutorials, IEEE/ACM Transactions on Networking and Computer Networks.
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.