Benjamin Sliwa

707 total citations
26 papers, 261 citations indexed

About

Benjamin Sliwa is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Aerospace Engineering. According to data from OpenAlex, Benjamin Sliwa has authored 26 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Electrical and Electronic Engineering, 15 papers in Computer Networks and Communications and 5 papers in Aerospace Engineering. Recurrent topics in Benjamin Sliwa's work include Vehicular Ad Hoc Networks (VANETs) (11 papers), Age of Information Optimization (6 papers) and Mobile Ad Hoc Networks (6 papers). Benjamin Sliwa is often cited by papers focused on Vehicular Ad Hoc Networks (VANETs) (11 papers), Age of Information Optimization (6 papers) and Mobile Ad Hoc Networks (6 papers). Benjamin Sliwa collaborates with scholars based in Germany, Denmark and United States. Benjamin Sliwa's co-authors include Christian Wietfeld, Michael Schreckenberg, Thomas Liebig, Nico Piatkowski, Christoph Ide, Stefan Böcker, Daniel Behnke, Preben Mogensen, Michael ten Hompel and Alexander Pasko and has published in prestigious journals such as IEEE Access, IEEE Transactions on Vehicular Technology and IEEE Transactions on Intelligent Transportation Systems.

In The Last Decade

Benjamin Sliwa

26 papers receiving 255 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Benjamin Sliwa Germany 11 145 128 46 43 42 26 261
Dongdai Zhou China 9 186 1.3× 110 0.9× 34 0.7× 13 0.3× 51 1.2× 23 297
Carlos Renato Storck Brazil 5 280 1.9× 170 1.3× 26 0.6× 18 0.4× 40 1.0× 17 357
Xiaoting Ma China 9 210 1.4× 187 1.5× 31 0.7× 14 0.3× 38 0.9× 22 334
Takaaki Umedu Japan 9 209 1.4× 195 1.5× 36 0.8× 29 0.7× 18 0.4× 39 325
Xiaosha Chen China 7 152 1.0× 126 1.0× 44 1.0× 11 0.3× 26 0.6× 13 260
Shanjin Ni China 10 354 2.4× 171 1.3× 31 0.7× 33 0.8× 54 1.3× 17 461
JoonBeom Kim United States 3 300 2.1× 151 1.2× 40 0.9× 16 0.4× 19 0.5× 3 385
Rajarajan Sivaraj United States 8 358 2.5× 327 2.6× 28 0.6× 22 0.5× 20 0.5× 13 431
Seilendria A. Hadiwardoyo Spain 12 227 1.6× 168 1.3× 50 1.1× 14 0.3× 129 3.1× 28 343
Chakkaphong Suthaputchakun United Kingdom 11 251 1.7× 230 1.8× 51 1.1× 23 0.5× 11 0.3× 24 332

Countries citing papers authored by Benjamin Sliwa

Since Specialization
Citations

This map shows the geographic impact of Benjamin Sliwa'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 Benjamin Sliwa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Sliwa more than expected).

Fields of papers citing papers by Benjamin Sliwa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin Sliwa. 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 Benjamin Sliwa. The network helps show where Benjamin Sliwa may publish in the future.

Co-authorship network of co-authors of Benjamin Sliwa

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin Sliwa. A scholar is included among the top collaborators of Benjamin Sliwa 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 Benjamin Sliwa. Benjamin Sliwa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Sliwa, Benjamin, et al.. (2022). DRaGon: Mining Latent Radio Channel Information from Geographical Data Leveraging Deep Learning. 2022 IEEE Wireless Communications and Networking Conference (WCNC). 2459–2464. 10 indexed citations
2.
Sliwa, Benjamin, et al.. (2022). System Modeling and Performance Evaluation of Predictive QoS for Future Tele-Operated Driving. 1–8. 7 indexed citations
3.
Sliwa, Benjamin, et al.. (2021). Adapting a cellular automata model to describe heterogeneous traffic with human-driven, automated, and communicating automated vehicles. Physica A Statistical Mechanics and its Applications. 570. 125792–125792. 39 indexed citations
4.
Sliwa, Benjamin, et al.. (2021). Towards Machine Learning-Enabled Context Adaption for Reliable Aerial Mesh Routing. 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall). 1–7. 2 indexed citations
5.
Sliwa, Benjamin, et al.. (2021). Client-Based Intelligence for Resource Efficient Vehicular Big Data Transfer in Future 6G Networks. IEEE Transactions on Vehicular Technology. 70(6). 5332–5346. 22 indexed citations
6.
Böcker, Stefan, et al.. (2021). Rapid Network Planning of Temporary Private 5G Networks with Unsupervised Machine Learning. 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall). 1–6. 13 indexed citations
7.
Brüggen, Georg von der, Kuan-Hsun Chen, Benjamin Sliwa, et al.. (2020). Offloading Safety- and Mission-Critical Tasks via Unreliable Connections. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 22. 1 indexed citations
8.
Sliwa, Benjamin, et al.. (2020). Reflecting Surfaces for Beyond Line-Of-Sight Coverage in Millimeter Wave Vehicular Networks. 1–4. 12 indexed citations
9.
Sliwa, Benjamin, et al.. (2019). Lightweight Simulation of Hybrid Aerial- and Ground-Based Vehicular Communication Networks. arXiv (Cornell University). 1–7. 8 indexed citations
10.
Sliwa, Benjamin, et al.. (2019). Performance Evaluation and Optimization of B.A.T.M.A.N. V Routing for Aerial and Ground-Based Mobile Ad-Hoc Networks. arXiv (Cornell University). 1–7. 18 indexed citations
11.
Sliwa, Benjamin & Christian Wietfeld. (2019). Empirical Analysis of Client-Based Network Quality Prediction in Vehicular Multi-MNO Networks. arXiv (Cornell University). 1–7. 14 indexed citations
12.
Sliwa, Benjamin, et al.. (2019). Boosting Vehicle-to-Cloud Communication by Machine Learning-Enabled Context Prediction. IEEE Transactions on Intelligent Transportation Systems. 21(8). 3497–3512. 26 indexed citations
13.
Behnke, Daniel, et al.. (2018). Efficient and Reliable Car-to-Cloud Data Transfer Empowered by BBR-Enabled Network Coding. 2. 1–5. 1 indexed citations
14.
Sliwa, Benjamin, et al.. (2018). A radio-fingerprinting-based vehicle classification system for intelligent traffic control in smart cities. arXiv (Cornell University). 37. 1–5. 3 indexed citations
15.
Sliwa, Benjamin, et al.. (2018). Performance Comparison of Dynamic Vehicle Routing Methods for Minimizing the Global Dwell Time in Upcoming Smart Cities. arXiv (Cornell University). 1–7. 3 indexed citations
16.
Sliwa, Benjamin, et al.. (2018). Efficient Machine-Type Communication Using Multi-Metric Context-Awareness for Cars Used as Mobile Sensors in Upcoming 5G Networks. arXiv (Cornell University). 1–6. 16 indexed citations
17.
Sliwa, Benjamin, et al.. (2018). Machine Learning Based Context-Predictive Car-to-Cloud Communication Using Multi-Layer Connectivity Maps for Upcoming 5G Networks. arXiv (Cornell University). 1–7. 13 indexed citations
18.
Sliwa, Benjamin, et al.. (2017). A Simple Scheme for Distributed Passive Load Balancing in Mobile Ad-Hoc Networks. arXiv (Cornell University). 1–5. 5 indexed citations
19.
Sliwa, Benjamin, Christoph Ide, & Christian Wietfeld. (2016). An OMNeT++ based Framework for Mobility-aware Routing in Mobile Robotic Networks. arXiv (Cornell University). 2 indexed citations
20.
Sliwa, Benjamin, et al.. (2000). Volume sculpting with 4D spline volumes. 1 indexed citations

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.

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