Juan Cáceres

3.5k citations
9 papers · 2.2k indexed · 2 hit papers · h-index 5

Juan Cáceres

7 papers receiving 1.9k citations

Hit Papers

The Reservoir model and architecture for open federated c...499200820262014202050010001.5k

Peers

Juan Cáceres
Comparison fields: 5 of 86
  • Information Systems 1.8k
  • Computer Networks and Communications 1.4k
  • Information Systems and Management 212
  • Management Information Systems 192
  • Artificial Intelligence 333
Replace Maik Lindner with:
Maik Lindner United Kingdom
Marcos Dias de Assunção Brazil
Stefan Tai Germany
Luis Rodero‐Merino Spain
Anna Liu Australia
Nirmal Mukhi United States
Yuri Demchenko Netherlands
Wolfgang Emmerich United Kingdom
Paola Grosso Netherlands
Paolo Trunfio Italy
Juan Cáceres relative to Maik Lindner United Kingdom Maik Lindner's profile →
Citations per field
00.5×1.5×
Maik Lindner · 1×
Citations per year

Countries citing papers authored by Juan Cáceres

Since Specialization
Citations

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

Fields of papers citing papers by Juan Cáceres

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Juan Cáceres, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Juan Cáceres Line = papers co-authored together Juan Cáceres links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 20250
2 20240
3 20186
4 20141
5 20116
6 201022
7
The Reservoir model and architecture for open federated cloud computingbreakdown →
2009499
8
A break in the cloudsbreakdown →
20081644
9 20023

About Juan Cáceres

Juan Cáceres is a scholar working on Information Systems, Computer Networks and Communications and Oncology, having authored 9 papers that have together received 2.2k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (4 papers), Distributed systems and fault tolerance (2 papers), Distributed and Parallel Computing Systems (2 papers), Pancreatic and Hepatic Oncology Research (1 paper), Peer-to-Peer Network Technologies (1 paper), Diabetes and associated disorders (1 paper), Advanced Numerical Methods in Computational Mathematics (1 paper) and Hyperglycemia and glycemic control in critically ill and hospitalized patients (1 paper). The work is most often cited by research in Information Systems (1.8k citations), Computer Networks and Communications (1.4k citations) and Information Systems and Management (212 citations). Juan Cáceres has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include Luis M. Vaquero, Maik Lindner, Luis Rodero‐Merino, Francisco José Galán Morillo, Kenneth Nagin, W. Emmerich, Alex Galis, Erik Elmroth, Rubén Montero and Ignacio M. Llórente.

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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