What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- Programming language
Luca Abeni mainly focuses on Distributed computing, Quality of service, Scheduling, Real-time computing and Reservation.
Luca Abeni has included themes like Resource allocation, Elastic scheduling, Workload management, Resource and Computation in his Distributed computing study.
His Scheduling study combines topics from a wide range of disciplines, such as Control system and Adaptive control.
His studies in Adaptive control integrate themes in fields like Automatic control, Data acquisition, Data compression, Digital control and Adaptive system.
The concepts of his Real-time computing study are interwoven with issues in Probabilistic logic, POSIX, Multimedia and Fixed-priority pre-emptive scheduling.
His research investigates the link between Reservation and topics such as Linux kernel that cross with problems in Latency and Linux os.
His most cited work include:
- Integrating multimedia applications in hard real-time systems (632 citations)
- Elastic task model for adaptive rate control (248 citations)
- Elastic scheduling for flexible workload management (218 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Distributed computing, Scheduling, Real-time computing, Quality of service and Linux kernel.
His work carried out in the field of Distributed computing brings together such families of science as Computer network, Resource allocation, Reservation, Resource and Task.
His biological study spans a wide range of topics, including Virtual machine, Virtualization and Embedded system.
His Real-time computing research is multidisciplinary, incorporating elements of Control system, Temporal isolation and Computation.
His studies deal with areas such as Processor scheduling, Legacy system, Application software, Control and Server as well as Quality of service.
His biological study deals with issues like Central processing unit, which deal with fields such as Deadline scheduler.
He most often published in these fields:
- Distributed computing (49.19%)
- Scheduling (45.97%)
- Real-time computing (26.61%)
What were the highlights of his more recent work (between 2018-2021)?
- Scheduling (45.97%)
- Distributed computing (49.19%)
- Virtualization (8.06%)
In recent papers he was focusing on the following fields of study:
Scheduling, Distributed computing, Virtualization, Operating system and Cloud computing are his primary areas of study.
His research in Scheduling intersects with topics in Real-time operating system and Parallel computing.
His Distributed computing research integrates issues from Temporal isolation, Kernel and Linux kernel.
His work deals with themes such as Bridging, Latency and Edge computing, which intersect with Kernel.
His study in Linux kernel is interdisciplinary in nature, drawing from both Partition and Greedy algorithm.
Luca Abeni combines subjects such as Container, Kernel and Computational science with his study of Cloud computing.
Between 2018 and 2021, his most popular works were:
- Container-based real-time scheduling in the Linux kernel (10 citations)
- Reducing Temporal Interference in Private Clouds through Real-Time Containers (4 citations)
- Real-time and energy efficiency in Linux: theory and practice (4 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Programming language
His primary areas of investigation include Virtualization, Scheduling, Operating system, Linux kernel and Temporal isolation.
His Scheduling research includes elements of Virtual machine and Hypervisor.
His Virtual machine study combines topics in areas such as Software, Custom software and Thread.
His Linux kernel research is multidisciplinary, incorporating perspectives in Set, Central processing unit, Software development and Deadline scheduler.
His Temporal isolation research incorporates themes from Edge computing, Cloud computing, Distributed computing and Kernel.
His Distributed computing study frequently links to adjacent areas such as Latency.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
