Germán Moltó

1.6k total citations
83 papers, 879 citations indexed

About

Germán Moltó is a scholar working on Computer Networks and Communications, Information Systems and Information Systems and Management. According to data from OpenAlex, Germán Moltó has authored 83 papers receiving a total of 879 indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Networks and Communications, 43 papers in Information Systems and 26 papers in Information Systems and Management. Recurrent topics in Germán Moltó's work include Cloud Computing and Resource Management (37 papers), Distributed and Parallel Computing Systems (36 papers) and Scientific Computing and Data Management (26 papers). Germán Moltó is often cited by papers focused on Cloud Computing and Resource Management (37 papers), Distributed and Parallel Computing Systems (36 papers) and Scientific Computing and Data Management (26 papers). Germán Moltó collaborates with scholars based in Spain, Italy and Mexico. Germán Moltó's co-authors include Miguel Caballer, Carlos Alfonso, Amanda Calatrava, Ignácio Blanquer, Diana Naranjo, José M. Alonso, Vicente Hernández, Eloy Romero, Fernando Alvarruiz and J. Damián Segrelles and has published in prestigious journals such as SHILAP Revista de lepidopterología, Optics Express and IEEE Access.

In The Last Decade

Germán Moltó

77 papers receiving 847 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Germán Moltó Spain 18 614 566 151 87 68 83 879
John P. Morrison Ireland 13 402 0.7× 300 0.5× 91 0.6× 111 1.3× 95 1.4× 101 644
Vijay Gadepally United States 13 221 0.4× 178 0.3× 55 0.4× 251 2.9× 33 0.5× 53 670
Sabri Pllana Austria 17 541 0.9× 345 0.6× 154 1.0× 150 1.7× 263 3.9× 51 811
Aibo Song China 12 360 0.6× 357 0.6× 36 0.2× 155 1.8× 27 0.4× 67 609
Xiaozhou Li Finland 13 1.0k 1.6× 450 0.8× 78 0.5× 157 1.8× 151 2.2× 66 1.2k
Avraham Leff United States 10 467 0.8× 235 0.4× 17 0.1× 94 1.1× 84 1.2× 39 661
Nuno Preguiça Portugal 13 694 1.1× 350 0.6× 36 0.2× 117 1.3× 106 1.6× 64 787
Tamás Kiss United Kingdom 15 544 0.9× 353 0.6× 276 1.8× 64 0.7× 84 1.2× 77 725
Jeremy Singer United Kingdom 14 394 0.6× 360 0.6× 29 0.2× 193 2.2× 147 2.2× 71 726
Martin Randles United Kingdom 13 496 0.8× 434 0.8× 15 0.1× 120 1.4× 29 0.4× 53 737

Countries citing papers authored by Germán Moltó

Since Specialization
Citations

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

Fields of papers citing papers by Germán Moltó

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Germán Moltó

This figure shows the co-authorship network connecting the top 25 collaborators of Germán Moltó. A scholar is included among the top collaborators of Germán Moltó 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 Germán Moltó. Germán Moltó 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.
Nguyen, Giang V., Amanda Calatrava, В. Козлов, et al.. (2024). Landscape of machine learning evolution: privacy-preserving federated learning frameworks and tools. Artificial Intelligence Review. 58(2). 5 indexed citations
2.
Ardagna, Danilo, et al.. (2024). OSCAR-P and aMLLibrary: Profiling and predicting the performance of FaaS-based applications in computing continua. Journal of Systems and Software. 221. 112282–112282. 1 indexed citations
3.
Caballer, Miguel, et al.. (2023). Rescheduling serverless workloads across the cloud-to-edge continuum. Future Generation Computer Systems. 153. 457–466. 5 indexed citations
4.
Ardagna, Danilo, et al.. (2023). OSCAR-P and aMLLibrary. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 139–146. 4 indexed citations
5.
Naranjo, Diana, et al.. (2023). On the Acceleration of FaaS Using Remote GPU Virtualization. 157–164. 1 indexed citations
6.
Moltó, Germán, et al.. (2021). GPU-Enabled Serverless Workflows for Efficient Multimedia Processing. Applied Sciences. 11(4). 1438–1438. 13 indexed citations
7.
Moltó, Germán, et al.. (2021). TaScaaS: A Multi-Tenant Serverless Task Scheduler and Load Balancer as a Service. IEEE Access. 9. 125215–125228. 6 indexed citations
8.
Caballer, Miguel, et al.. (2021). Deployment of Elastic Virtual Hybrid Clusters Across Cloud Sites. Journal of Grid Computing. 19(1). 6 indexed citations
9.
Moltó, Germán, et al.. (2020). Toward Bio-Inspired Auto-Scaling Algorithms: An Elasticity Approach for Container Orchestration Platforms. IEEE Access. 8. 52139–52150. 17 indexed citations
10.
Moltó, Germán, Diana Naranjo, & J. Damián Segrelles. (2020). Insights from Learning Analytics for Hands-On Cloud Computing Labs in AWS. Applied Sciences. 10(24). 9148–9148. 1 indexed citations
11.
Naranjo, Diana, et al.. (2019). A Visual Dashboard to Track Learning Analytics for Educational Cloud Computing. Sensors. 19(13). 2952–2952. 17 indexed citations
12.
Moltó, Germán, et al.. (2019). A framework and a performance assessment for serverless MapReduce on AWS Lambda. Future Generation Computer Systems. 97. 259–274. 51 indexed citations
13.
Calatrava, Amanda, et al.. (2019). A self-managed Mesos cluster for data analytics with QoS guarantees. Future Generation Computer Systems. 96. 449–461. 6 indexed citations
14.
Segrelles, J. Damián, Alicia Martínez, Nuria Castilla Cabanes, & Germán Moltó. (2017). Virtualized Computational Environments on the cloud to foster group skills through PBL: A case study in architecture. Computers & Education. 108. 131–144. 10 indexed citations
15.
Alfonso, Carlos, Amanda Calatrava, & Germán Moltó. (2017). Container-based virtual elastic clusters. Journal of Systems and Software. 127. 1–11. 39 indexed citations
16.
Milián, Carles, I. Torres-Gómez, M. Torres‐Cisneros, et al.. (2017). Optimization for maximum Raman frequency conversion in supercontinuum sources using genetic algorithms. Revista Mexicana de Física. 63(2). 111–116. 3 indexed citations
17.
Moltó, Germán, Miguel Caballer, & Carlos Alfonso. (2015). Automatic memory-based vertical elasticity and oversubscription on cloud platforms. Future Generation Computer Systems. 56. 1–10. 27 indexed citations
18.
Caballer, Miguel, et al.. (2014). CodeCloud: A platform to enable execution of programming models on the Clouds. Journal of Systems and Software. 93. 187–198. 10 indexed citations
19.
Caballer, Miguel, Carlos Alfonso, Fernando Alvarruiz, & Germán Moltó. (2013). EC3: Elastic Cloud Computing Cluster. Journal of Computer and System Sciences. 79(8). 1341–1351. 33 indexed citations
20.
Romero, Lucía, Beatriz Trénor, J.M. Ferrero, et al.. (2006). Safety factor in simulated 2D cardiac tissue. influence of altered membrane excitability. Computing in Cardiology Conference. 217–220. 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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