Science Explorer Interactive view Map

Distributed systems and fault tolerance

Distributed systems and fault tolerance is a research topic within Computer Networks and Communications. Science Explorer counts 44k research works in it since 1950. 21.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on research related to fault tolerance, consistency, and resilience in distributed systems. It covers topics such as Byzantine fault tolerance, transactional memory, checkpointing, replication, concurrency control, and software aging. The papers explore various techniques and algorithms to ensure the reliability and consistency of data and operations in distributed environments.

  • Fault Tolerance
  • Distributed Systems
  • Consistency
  • Transactional Memory
  • Byzantine Fault Tolerance
  • Checkpointing
  • Replication
  • Concurrency Control
  • Failure Prediction
  • Software Aging
Research works
44k
fractional, since 1950
In the world top 10%
9.5k
per year above
Top-10% rate
21.9%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-22%
the tick is no change

Which countries lead Distributed systems and fault tolerance research?

By volume, the United States and China publish the most (859 and 746 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 859 works
  2. 2 China 746 works
  3. 3 Germany 268 works
  4. 4 India 228 works
  5. 5 France 204 works
  6. 6 United Kingdom 161 works
  7. 7 Italy 147 works
  8. 8 Canada 114 works
  9. 9 Japan 111 works
  10. 10 Brazil 83 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 29.4%China: 25.6%Germany: 9.2%India: 7.8%6 others listed: 28.1%29%largest
United States859 · 29.4%China746 · 25.6%Germany268 · 9.2%India228 · 7.8%6 others listed819 · 28.1%

Shares of the rows listed above, not of the whole node.

Which institutions lead Distributed systems and fault tolerance research?

By volume in 2022–2025, Centre National de la Recherche Scientifique publishes the most Distributed systems and fault tolerance research, followed by Shanghai Jiao Tong University and Carnegie Mellon University.

Who are the leading researchers in Distributed systems and fault tolerance?

The most-cited researchers publishing on Distributed systems and fault tolerance include Ion Stoica, H. Vincent Poor and Rajkumar Buyya.

  1. 1 Ion Stoica United States 9.6k citations
  2. 2 H. Vincent Poor United States 9.5k citations
  3. 3 Rajkumar Buyya Australia 7.8k citations
  4. 4 Ronald L. Rivest United States 7.3k citations
  5. 5 Philip S. Yu United States 6.6k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Distributed systems and fault tolerance research done?

The largest centres of Distributed systems and fault tolerance research in 2022–2025 are Beijing (China), Shanghai (China), Paris (France) and Tokyo (Japan). Among places with at least 20 works in it, it is an unusually large share of all research in Saarbrücken and Waterloo.

Largest cities, 2022–2025

  1. 1 Beijing China 193 works
  2. 2 Shanghai China 80 works
  3. 3 Paris France 61 works
  4. 4 Tokyo Japan 46 works
  5. 5 Xi'an China 45 works
  6. 6 Nanjing China 43 works
  7. 7 Seoul South Korea 39 works
  8. 8 Wuhan China 37 works
  9. 9 Munich Germany 33 works
  10. 10 London United Kingdom 32 works

Where it is the local speciality

  1. SaarbrückenDE · 21.0 works16×
  2. WaterlooCA · 21.3 works8.0×
← less than its size predictsmore →

Location quotient: how much more of its research is in Distributed systems and fault tolerance than the world average.

See Distributed systems and fault tolerance on the map

Where is the best place to study Distributed systems and fault tolerance?

Among universities, judged by research, ETH Zurich, TU Wien and Carnegie Mellon University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 20.12%fractional works in this node (log) →share in the world top 10% →ETH Zurich: 20, 25.8%TU Wien: 17, 25.2%Carnegie Mellon University: 24, 12.4%Beijing University of Posts and Telecommunications: 17, 25.4%Technical University of Munich: 21, 16.8%East China Normal University: 16, 11.9%Technische Universität Darmstadt: 12, 20.2%University of Illinois Urbana-Champaign: 21, 22.5%National University of Singapore: 13, 29.2%Macau University of Science and Technology: 9, 11.8%ETH ZurichBeijing University o…TU WienCarnegie Mellon Univ…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 ETH ZurichSwitzerland 68.225.8%7.8×20 -6.0%
2 TU WienAustria 67.125.2%14.5×17 -39.7%
3 Carnegie Mellon UniversityUnited States 67.012.4%15.7×24 +88.4%
4 Beijing University of Posts and TelecommunicationsChina 57.225.4%7.3×17 -13.1%
5 Technical University of MunichGermany 56.816.8%7.0×21 +5.2%
6 East China Normal UniversityChina 56.711.9%8.6×16 +117.4%
7 Technische Universität DarmstadtGermany 56.220.2%9.6×12 +9.9%
8 University of Illinois Urbana-ChampaignUnited States 55.122.5%6.4×21 -42.0%
9 National University of SingaporeSingapore 52.929.2%3.6×13 -15.2%
10 Macau University of Science and TechnologyMacau 52.511.8%11.0×9

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Distributed systems and fault tolerance research growing?

Output in 2018–2022 was 22% lower than in 2013–2017, peaking in 2002.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.