Joel Scheuner

583 total citations
23 papers, 360 citations indexed

About

Joel Scheuner is a scholar working on Computer Networks and Communications, Information Systems and Software. According to data from OpenAlex, Joel Scheuner has authored 23 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Networks and Communications, 21 papers in Information Systems and 2 papers in Software. Recurrent topics in Joel Scheuner's work include Cloud Computing and Resource Management (18 papers), IoT and Edge/Fog Computing (16 papers) and Software System Performance and Reliability (10 papers). Joel Scheuner is often cited by papers focused on Cloud Computing and Resource Management (18 papers), IoT and Edge/Fog Computing (16 papers) and Software System Performance and Reliability (10 papers). Joel Scheuner collaborates with scholars based in Sweden, Switzerland and Germany. Joel Scheuner's co-authors include Philipp Leitner, Erwin van Eyk, Alexandru Iosup, Simon Eismann, Cristina L. Abad, Harald C. Gall, Jürgen Cito, Nikolas Herbst, Johannes Grohmann and David Bermbach and has published in prestigious journals such as IEEE Transactions on Software Engineering, IEEE Software and Journal of Systems and Software.

In The Last Decade

Joel Scheuner

23 papers receiving 353 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joel Scheuner Sweden 11 306 298 32 28 23 23 360
Giovanni Quattrocchi Italy 9 221 0.7× 192 0.6× 59 1.8× 13 0.5× 8 0.3× 27 276
Jørgen Thelin United States 7 200 0.7× 151 0.5× 48 1.5× 16 0.6× 11 0.5× 10 255
Thomas Ledoux France 7 167 0.5× 172 0.6× 48 1.5× 7 0.3× 11 0.5× 26 225
Alexandru Uta Netherlands 9 204 0.7× 188 0.6× 43 1.3× 18 0.6× 4 0.2× 28 246
Dharmesh Kakadia India 6 228 0.7× 213 0.7× 36 1.1× 14 0.5× 4 0.2× 7 274
Simon Loesing Switzerland 6 399 1.3× 366 1.2× 44 1.4× 15 0.5× 5 0.2× 7 440
Johannes Wettinger Germany 10 303 1.0× 322 1.1× 61 1.9× 33 1.2× 25 1.1× 21 394
Hamoun Ghanbari Canada 10 273 0.9× 240 0.8× 100 3.1× 7 0.3× 40 1.7× 16 320
Chengzhi Lu China 7 331 1.1× 298 1.0× 64 2.0× 11 0.4× 6 0.3× 14 383
Diego Didona Portugal 14 423 1.4× 272 0.9× 62 1.9× 11 0.4× 13 0.6× 29 474

Countries citing papers authored by Joel Scheuner

Since Specialization
Citations

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

Fields of papers citing papers by Joel Scheuner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joel Scheuner

This figure shows the co-authorship network connecting the top 25 collaborators of Joel Scheuner. A scholar is included among the top collaborators of Joel Scheuner 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 Joel Scheuner. Joel Scheuner 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.
Scheuner, Joel, et al.. (2024). FUSIONIZE++: Improving Serverless Application Performance Using Dynamic Task Inlining and Infrastructure Optimization. IEEE Transactions on Cloud Computing. 12(4). 1172–1185. 3 indexed citations
2.
Scheuner, Joel, et al.. (2022). TriggerBench: A Performance Benchmark for Serverless Function Triggers. Chalmers Research (Chalmers University of Technology). 96–103. 4 indexed citations
3.
Scheuner, Joel, et al.. (2022). CrossFit: Fine-grained Benchmarking of Serverless Application Performance across Cloud Providers. Chalmers Research (Chalmers University of Technology). 51–60. 4 indexed citations
4.
Eismann, Simon, Joel Scheuner, Erwin van Eyk, et al.. (2021). The State of Serverless Applications: Collection, Characterization, and Community Consensus. IEEE Transactions on Software Engineering. 48(10). 4152–4166. 58 indexed citations
5.
Scheuner, Joel & Philipp Leitner. (2020). The State of Research on Function-as-a-Service Performance Evaluation: A Multivocal Literature Review.. arXiv (Cornell University). 2 indexed citations
6.
Eismann, Simon, Joel Scheuner, Erwin van Eyk, et al.. (2020). A Review of Serverless Use Cases and their Characteristics. arXiv (Cornell University). 31 indexed citations
7.
Carver, Jeffrey C., Birgit Penzenstadler, Joel Scheuner, & Miroslaw Staron. (2020). (Research) Insights for Serverless Application Engineering. IEEE Software. 38(1). 123–125. 2 indexed citations
8.
Eyk, Erwin van, Joel Scheuner, Simon Eismann, Cristina L. Abad, & Alexandru Iosup. (2020). Beyond Microbenchmarks: The SPEC-RG Vision for a Comprehensive Serverless Benchmark. Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam). 26–31. 12 indexed citations
9.
Scheuner, Joel & Philipp Leitner. (2020). Function-as-a-Service performance evaluation: A multivocal literature review. Journal of Systems and Software. 170. 110708–110708. 57 indexed citations
10.
Eismann, Simon, Joel Scheuner, Erwin van Eyk, et al.. (2020). SPEC RG Technical Report: A Review of Serverless Use Cases and their Characteristics - Dataset. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
11.
Scheuner, Joel, et al.. (2019). Software microbenchmarking in the cloud. How bad is it really?. Empirical Software Engineering. 24(4). 2469–2508. 38 indexed citations
12.
Scheuner, Joel & Philipp Leitner. (2019). Performance Benchmarking of Infrastructure-as-a-Service (IaaS) Clouds with Cloud WorkBench. Chalmers Research (Chalmers University of Technology). 53–56. 2 indexed citations
13.
Scheuner, Joel & Philipp Leitner. (2019). Performance Benchmarking of Infrastructure-as-a-Service (IaaS) Clouds with Cloud WorkBench (Tutorial). Chalmers Research (Chalmers University of Technology). 257–258. 1 indexed citations
14.
Scheuner, Joel & Philipp Leitner. (2019). Transpiling Applications into Optimized Serverless Orchestrations. Chalmers Research (Chalmers University of Technology). 72–73. 5 indexed citations
15.
Scheuner, Joel & Philipp Leitner. (2018). A Cloud Benchmark Suite Combining Micro and Applications Benchmarks. Chalmers Research (Chalmers University of Technology). 161–166. 2 indexed citations
16.
Scheuner, Joel & Philipp Leitner. (2018). Estimating Cloud Application Performance Based on Micro-Benchmark Profiling. Chalmers Research (Chalmers University of Technology). 90–97. 23 indexed citations
17.
Inzinger, Christian, et al.. (2017). An Approach and Case Study of Cloud Instance Type Selection for Multi-tier Web Applications. 534–543. 9 indexed citations
18.
Scheuner, Joel, et al.. (2016). Probr - A Generic and Passive WiFi Tracking System. 22 indexed citations
19.
Leitner, Philipp & Joel Scheuner. (2015). Bursting with Possibilities -- An Empirical Study of Credit-Based Bursting Cloud Instance Types. Zurich Open Repository and Archive (University of Zurich). 7. 227–236. 22 indexed citations
20.
Scheuner, Joel, Jürgen Cito, Philipp Leitner, & Harald C. Gall. (2015). Cloud WorkBench. Zurich Open Repository and Archive (University of Zurich). 239–242. 22 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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