What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- Programming language
Karl-Erik Årzén focuses on Control system, Control engineering, Distributed computing, Dynamic priority scheduling and Scheduling.
His studies in Control system integrate themes in fields like Embedded system and Kernel.
His Control engineering study incorporates themes from Control, Expert system and Macro.
As a part of the same scientific study, Karl-Erik Årzén usually deals with the Distributed computing, concentrating on Rate-monotonic scheduling and frequently concerns with Round-robin scheduling and Two-level scheduling.
The concepts of his Dynamic priority scheduling study are interwoven with issues in Wireless sensor network and Fair-share scheduling.
The various areas that Karl-Erik Årzén examines in his Scheduling study include Real-time Control System, Real-time computing and Control theory.
His most cited work include:
- Piecewise quadratic stability of fuzzy systems (694 citations)
- Real Time Scheduling Theory: A Historical Perspective (515 citations)
- How does control timing affect performance? Analysis and simulation of timing using Jitterbug and TrueTime (492 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Control engineering, Control system, Control, Distributed computing and Control theory.
The study incorporates disciplines such as Process control and Petri net in addition to Control engineering.
His Control system research is multidisciplinary, incorporating perspectives in Systems engineering, Software, Software engineering and Automatic control.
His work carried out in the field of Distributed computing brings together such families of science as Wireless, Communications system, Scheduling, Cloud computing and Robustness.
Karl-Erik Årzén is interested in Dynamic priority scheduling, which is a field of Scheduling.
His work deals with themes such as MATLAB and Real-time computing, which intersect with Real-time Control System.
He most often published in these fields:
- Control engineering (22.71%)
- Control system (20.09%)
- Control (17.03%)
What were the highlights of his more recent work (between 2012-2021)?
- Cloud computing (10.48%)
- Distributed computing (17.03%)
- Control (17.03%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Cloud computing, Distributed computing, Control, Mathematical optimization and Real-time computing.
His Cloud computing study combines topics from a wide range of disciplines, such as Fault tolerance, User experience design, Load balancing and Automatic control.
His Distributed computing study combines topics in areas such as Software, Robustness and Communications system.
His Control research is multidisciplinary, incorporating elements of Information and Computer Science, Cloud data center, Computational science and Operations research.
His Real-time Control System study in the realm of Control system connects with subjects such as Co-design.
Karl-Erik Årzén combines subjects such as Software engineering and Cyber-physical system with his study of Control engineering.
Between 2012 and 2021, his most popular works were:
- Brownout: building more robust cloud applications (106 citations)
- PEAS: A Performance Evaluation Framework for Auto-Scaling Strategies in Cloud Applications (39 citations)
- Improving Cloud Service Resilience Using Brownout-Aware Load-Balancing (30 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Programming language
Karl-Erik Årzén mostly deals with Cloud computing, Distributed computing, Control, Load balancing and User experience design.
His research in Cloud computing intersects with topics in Computer security, Automatic control and Artificial intelligence.
The Distributed computing study combines topics in areas such as Time complexity, Software quality and SCHED_DEADLINE.
His Control research incorporates themes from Deep learning, Intelligent control, Variety, Data science and Cloud resources.
His Load balancing research includes themes of Redundancy, Crowds and Unexpected events.
His User experience design study integrates concerns from other disciplines, such as Queue, Computer network and Transient.
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