Marco A. S. Netto

2.9k citations
41 papers · 1.4k indexed · 1 hit paper · h-index 15

Marco A. S. Netto

39 papers receiving 1.3k citations

Hit Papers

Big Data computing and clouds: Trends and future directions4942014202620182022100200300400

Peers

Marco A. S. Netto
Comparison fields: 5 of 96
  • Information Systems 984
  • Computer Networks and Communications 920
  • Management Information Systems 224
  • Information Systems and Management 161
  • Hardware and Architecture 85
Replace Marcos Dias de Assunção with:
Marcos Dias de Assunção Brazil
Beniamino Di Martino Italy
Paola Grosso Netherlands
M. Kunze Germany
Paolo Trunfio Italy
Anna Liu Australia
R. G. G. Cattell United States
Michael L. Brodie United States
Peter Mell United States
Karthik Kambatla United States
Marco A. S. Netto relative to Marcos Dias de Assunção Brazil Marcos Dias de Assunção's profile →
Citations per field
00.5×1.5×
Marcos Dias de Assunção · 1×
Citations per year

Countries citing papers authored by Marco A. S. Netto

Since Specialization
Citations

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

Fields of papers citing papers by Marco A. S. Netto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco A. S. Netto. 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 Marco A. S. Netto. The network helps show where Marco A. S. Netto may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Marco A. S. Netto, 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 Marco A. S. Netto Line = papers co-authored together Marco A. S. Netto links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202127
2 20202
3 20160
4 20157
5 20144
6 20146
7 20141
8 201456
9
Big Data computing and clouds: Trends and future directionsbreakdown →
2014494
10 20133
11 20121
12 20123
13 201114
14 20119
15 201110
16 20100
17 200814
18 20072
19 20069
20 20037

About Marco A. S. Netto

Marco A. S. Netto is a scholar working on Information Systems and Management, Computer Networks and Communications and Information Systems, having authored 41 papers that have together received 1.4k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (27 papers), Distributed and Parallel Computing Systems (23 papers), IoT and Edge/Fog Computing (10 papers), Scientific Computing and Data Management (10 papers), Software System Performance and Reliability (6 papers), Parallel Computing and Optimization Techniques (6 papers), Distributed systems and fault tolerance (4 papers) and Advanced Data Storage Technologies (4 papers). The work is most often cited by research in Information Systems (984 citations), Computer Networks and Communications (920 citations) and Management Information Systems (224 citations). Marco A. S. Netto has collaborated with scholars based in Brazil, United States and Australia. Frequent co-authors include Rodrigo N. Calheiros, Rajkumar Buyya, Marcos Dias de Assunção, Silvia Bianchi, César A. F. De Rose, Tiago Ferreto, Renato L. F. Cunha, Carlos Cardonha, Ivona Brandić and Vincent C. Emeakaroha. Their work appears in journals such as ACM Computing Surveys, Computer and Future Generation Computer Systems.

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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