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Topic · Hardware and Architecture

Real-Time Systems Scheduling

Real-Time Systems Scheduling is a research topic within Hardware and Architecture. Science Explorer counts 24k research works in it since 1953. 15.4% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on real-time scheduling algorithms, timing analysis, and resource allocation in the context of embedded systems. It covers topics such as scheduling algorithms for hard real-time systems, WCET analysis, multiprocessor scheduling, and the integration of multimedia applications in real-time systems.

  • Scheduling Algorithms
  • Hard Real-Time Systems
  • Multiprocessor Scheduling
  • WCET Analysis
  • Embedded Systems
  • Timing Analysis
  • Resource Allocation
  • Mixed-Criticality Systems
  • Feedback Control
  • RTOS
Research works
24k
fractional, since 1953
In the world top 10%
3.7k
per year above
Top-10% rate
15.4%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-26%
the tick is no change

Which countries lead Real-Time Systems Scheduling research?

By volume, China and the United States publish the most (453 and 342 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 453 works
  2. 2 United States 342 works
  3. 3 Germany 241 works
  4. 4 India 178 works
  5. 5 France 108 works
  6. 6 Italy 100 works
  7. 7 South Korea 69 works
  8. 8 United Kingdom 65 works
  9. 9 Japan 64 works
  10. 10 Spain 53 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.

China: 27.1%United States: 20.4%Germany: 14.4%India: 10.6%6 others listed: 27.5%27%largest
China453 · 27.1%United States342 · 20.4%Germany241 · 14.4%India178 · 10.6%6 others listed460 · 27.5%

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

Which institutions lead Real-Time Systems Scheduling research?

By volume in 2022–2025, Technical University of Munich publishes the most Real-Time Systems Scheduling research, followed by Eindhoven University of Technology and Scuola Superiore Sant'Anna.

By volume, 2022–2025

  1. 1 Technical University of MunichGermany 20 works
  2. 2 Eindhoven University of TechnologyNetherlands 16 works
  3. 3 Scuola Superiore Sant'AnnaItaly 15 works
  4. 4 University of StuttgartGermany 15 works
  5. 5 Sungkyunkwan UniversitySouth Korea 13 works
  6. 6 Shanghai Jiao Tong UniversityChina 12 works
  7. 7 Centre National de la Recherche ScientifiqueFrance 12 works
  8. 8 Beihang UniversityChina 12 works
  9. 9 KTH Royal Institute of TechnologySweden 11 works
  10. 10 Karlsruhe Institute of TechnologyGermany 11 works

Who are the leading researchers in Real-Time Systems Scheduling?

The most-cited researchers publishing on Real-Time Systems Scheduling include Luca Benini and MengChu Zhou.

  1. 1 Luca Benini Italy 4.6k citations
  2. 2 MengChu Zhou United States 4.4k citations

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

Where is Real-Time Systems Scheduling research done?

The largest centres of Real-Time Systems Scheduling research in 2022–2025 are Beijing (China), Shanghai (China), Seoul (South Korea) and Munich (Germany). Among places with at least 20 works in it, it is an unusually large share of all research in Stuttgart and Pisa.

Largest cities, 2022–2025

  1. 1 Beijing China 107 works
  2. 2 Shanghai China 50 works
  3. 3 Seoul South Korea 43 works
  4. 4 Munich Germany 37 works
  5. 5 Xi'an China 37 works
  6. 6 Stuttgart Germany 26 works
  7. 7 Tokyo Japan 26 works
  8. 8 Paris France 25 works
  9. 9 Nanjing China 24 works
  10. 10 Pisa Italy 23 works

Where it is the local speciality

  1. StuttgartDE · 26.1 works14×
  2. PisaIT · 23.4 works13×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Real-Time Systems Scheduling than the world average.

See Real-Time Systems Scheduling on the map

Where is the best place to study Real-Time Systems Scheduling?

Among universities, judged by research, Technical University of Munich, University of Stuttgart and Scuola Superiore Sant'Anna 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%10%20%mean 10.68%fractional works in this node (log) →share in the world top 10% →Technical University of Munich: 20, 16.4%University of Stuttgart: 15, 12.1%Scuola Superiore Sant'Anna: 15, 13.3%Eindhoven University of Technology: 16, 6.5%TU Dortmund University: 9, 20.6%KTH Royal Institute of Technology: 12, 6.3%University of York: 9, 12.4%Mälardalen University: 10, 10.9%Sungkyunkwan University: 14, 0.8%Karlsruhe Institute of Technology: 11, 7.5%Technical University…Scuola Superiore San…University of Stuttg…Eindhoven University…
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 Technical University of MunichGermany 70.916.4%11.7×20 -10.3%
2 University of StuttgartGermany 68.012.1%19.4×15 +181.7%
3 Scuola Superiore Sant'AnnaItaly 58.613.3%72.9×15 -24.4%
4 Eindhoven University of TechnologyNetherlands 54.66.5%20.1×16 -13.1%
5 TU Dortmund UniversityGermany 52.320.6%15.6×9 -2.6%
6 KTH Royal Institute of TechnologySweden 48.76.3%14.2×12 -13.8%
7 University of YorkUnited Kingdom 44.912.4%13.1×9 -29.4%
8 Mälardalen UniversitySweden 44.610.9%86.7×10 -48.7%
9 Sungkyunkwan UniversitySouth Korea 42.70.8%11.2×14 +1.5%
10 Karlsruhe Institute of TechnologyGermany 42.47.5%9.6×11 -41.9%

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 Real-Time Systems Scheduling research growing?

Output in 2018–2022 was 26% 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.