What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- Software
Marco Caccamo mostly deals with Embedded system, Distributed computing, Scheduling, Cache and Operating system.
Marco Caccamo combines subjects such as Isolation and Set with his study of Embedded system.
His Distributed computing research includes elements of Key distribution in wireless sensor networks, Earliest deadline first scheduling, Rate-monotonic scheduling, Dynamic priority scheduling and Computer network.
His biological study spans a wide range of topics, including Scheduling theory, Key, Deadline-monotonic scheduling and Operations research.
His work carried out in the field of Scheduling brings together such families of science as Automatic control, Computation, Adaptive control and Workload management.
When carried out as part of a general Operating system research project, his work on Coscheduling, Executable and Shared resource is frequently linked to work in Upper and lower bounds, therefore connecting diverse disciplines of study.
His most cited work include:
- Real Time Scheduling Theory: A Historical Perspective (515 citations)
- An implicit prioritized access protocol for wireless sensor networks (273 citations)
- Elastic scheduling for flexible workload management (218 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Distributed computing, Embedded system, Scheduling, Real-time computing and Multi-core processor.
His Distributed computing research is multidisciplinary, incorporating perspectives in Earliest deadline first scheduling, Computer network, Cyber-physical system and Parallel computing.
Marco Caccamo has included themes like Software, Operating system, Task and Cache in his Embedded system study.
His Scheduling research incorporates themes from Exploit, Quality of service, Real-time Control System and Computation.
His Real-time computing study combines topics in areas such as Radar, Fixed-priority pre-emptive scheduling and Reinforcement learning.
His studies in Multi-core processor integrate themes in fields like Single-core, Shared resource and Shared memory.
He most often published in these fields:
- Distributed computing (33.53%)
- Embedded system (28.24%)
- Scheduling (25.29%)
What were the highlights of his more recent work (between 2018-2021)?
- Distributed computing (33.53%)
- Reinforcement learning (4.71%)
- Motion planning (5.29%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Distributed computing, Reinforcement learning, Motion planning, Real-time computing and Embedded system.
Marco Caccamo conducts interdisciplinary study in the fields of Distributed computing and Reaction timing through his works.
His work deals with themes such as Network architecture and Control, which intersect with Reinforcement learning.
His study in Real-time computing is interdisciplinary in nature, drawing from both Range, Mobile agent and Leverage.
His work in the fields of Embedded system, such as Real-time operating system, overlaps with other areas such as Hypervisor.
The Worst-case execution time study combines topics in areas such as Cache hierarchy, Multi-core processor, Shared memory and Cache.
Between 2018 and 2021, his most popular works were:
- Preserving Physical Safety Under Cyber Attacks (14 citations)
- Electric Propulsion System Optimization for Long-Endurance and Solar-Powered Unmanned Aircraft (9 citations)
- UAV Coverage Path Planning under Varying Power Constraints using Deep Reinforcement Learning (8 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Software
His primary areas of investigation include Motion planning, Reinforcement learning, Real-time computing, Distributed computing and Leverage.
Marco Caccamo integrates several fields in his works, including Motion planning, Network architecture, Partially observable Markov decision process and Collision avoidance.
His research links Telecommunications network with Network architecture.
With his scientific publications, his incorporates both Distributed computing and Drone.
His Leverage research includes themes of Transfer of learning and Mobile agent.
His research on Transfer of learning often connects related topics like Trajectory.
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