Jan-Erik Mångs

542 total citations
14 papers, 365 citations indexed

About

Jan-Erik Mångs is a scholar working on Computer Networks and Communications, Information Systems and Management Information Systems. According to data from OpenAlex, Jan-Erik Mångs has authored 14 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Networks and Communications, 10 papers in Information Systems and 1 paper in Management Information Systems. Recurrent topics in Jan-Erik Mångs's work include Cloud Computing and Resource Management (10 papers), IoT and Edge/Fog Computing (9 papers) and Caching and Content Delivery (3 papers). Jan-Erik Mångs is often cited by papers focused on Cloud Computing and Resource Management (10 papers), IoT and Edge/Fog Computing (9 papers) and Caching and Content Delivery (3 papers). Jan-Erik Mångs collaborates with scholars based in Sweden, Brazil and United Kingdom. Jan-Erik Mångs's co-authors include Bob Melander, Glauco Estácio Gonçalves, Patrícia Takako Endo, Judith Kelner, Djamel Sadok, Andreas Johnsson, Martin Nilsson, Mats Björkman, Nelson Mimura Gonzalez and Tereza Cristina Melo de Brito Carvalho and has published in prestigious journals such as IEEE Network.

In The Last Decade

Jan-Erik Mångs

13 papers receiving 327 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan-Erik Mångs Sweden 8 312 207 75 34 31 14 365
Chinmaya Kumar Dehury Estonia 11 258 0.8× 160 0.8× 80 1.1× 48 1.4× 32 1.0× 25 330
Nan Deng United States 9 387 1.2× 369 1.8× 69 0.9× 46 1.4× 20 0.6× 12 467
Sami Yangui France 9 235 0.8× 156 0.8× 49 0.7× 41 1.2× 33 1.1× 38 314
Fangfei Chen United States 8 345 1.1× 146 0.7× 51 0.7× 53 1.6× 40 1.3× 20 390
Yaser Mansouri Australia 8 317 1.0× 272 1.3× 39 0.5× 50 1.5× 26 0.8× 12 393
Shuang Chen United States 7 270 0.9× 224 1.1× 41 0.5× 50 1.5× 26 0.8× 17 331
Jimmy Clidaras United States 4 465 1.5× 448 2.2× 114 1.5× 32 0.9× 25 0.8× 4 567
János Czentye Hungary 13 380 1.2× 174 0.8× 101 1.3× 31 0.9× 28 0.9× 29 441
Meina Song China 8 224 0.7× 152 0.7× 59 0.8× 63 1.9× 36 1.2× 40 310
Atsuko Takefusa Japan 12 377 1.2× 205 1.0× 83 1.1× 34 1.0× 39 1.3× 57 501

Countries citing papers authored by Jan-Erik Mångs

Since Specialization
Citations

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

Fields of papers citing papers by Jan-Erik Mångs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan-Erik Mångs. 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-Erik Mångs. The network helps show where Jan-Erik Mångs may publish in the future.

Co-authorship network of co-authors of Jan-Erik Mångs

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

All Works

14 of 14 papers shown
1.
Gonzalez, Nelson Mimura, et al.. (2017). Towards Bandwidth Optimization in Fog Computing using FACE Framework. 491–498. 4 indexed citations
2.
Gonzalez, Nelson Mimura, et al.. (2016). Fog computing: Data analytics and cloud distributed processing on the network edges. 1–9. 32 indexed citations
3.
Gonzalez, Nelson Mimura, et al.. (2014). The Use of Distributed Processing and Cloud Computing in Agricultural Decision-Making Support Systems. 721–728. 9 indexed citations
4.
Gonzalez, Nelson Mimura, et al.. (2013). Cloud Distributed Processing Using Trade Wind. 437–438. 1 indexed citations
5.
Gonzalez, Nelson Mimura, et al.. (2013). Distributed Processing from Large Scale Sensor Network Using Hadoop. 417–418. 2 indexed citations
6.
Gonzalez, Nelson Mimura, et al.. (2013). How Advanced Cloud Services Can Improve Gaming Performance. 3. 289–292.
7.
Gonçalves, Glauco Estácio, Marcos dos Santos, Patrícia Takako Endo, et al.. (2012). D-CRAS: Distributed cloud resource allocation system. 32. 659–662. 7 indexed citations
8.
Curescu, Calin, James Kempf, Yves Lemieux, et al.. (2012). Cloud Computing and Telecommunications: Business Opportunities, Technologies and Experimental Setup. 1–6. 2 indexed citations
9.
Gonçalves, Glauco Estácio, Patrícia Takako Endo, Djamel Sadok, et al.. (2011). Resource Allocation in Clouds: Concepts, Tools and Research Challenges. 217(3). 995–1011. 17 indexed citations
10.
Miers, Charles C., Marcos A. Simplício, Nelson Mimura Gonzalez, et al.. (2011). Using <em>Trade Wind</em> to Sail in the Clouds. 1 indexed citations
11.
Endo, Patrícia Takako, Glauco Estácio Gonçalves, Djamel Sadok, et al.. (2011). Resource allocation for distributed cloud: concepts and research challenges. IEEE Network. 25(4). 42–46. 148 indexed citations
12.
Gonçalves, Glauco Estácio, Patrícia Takako Endo, Djamel Sadok, et al.. (2011). CloudML: An Integrated Language for Resource, Service and Request Description for D-Clouds. 399–406. 25 indexed citations
13.
Endo, Patrícia Takako, et al.. (2010). Open Source Cloud Computing Platforms. 37 indexed citations
14.
Nilsson, Martin, et al.. (2006). Real-Time Measurement of End-to-End Available Bandwidth using Kalman Filtering. 73–84. 80 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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