What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- The Internet
His primary areas of study are Distributed computing, Real-time computing, Virtual machine, Operating system and Host.
His work on Virtual network as part of general Distributed computing research is frequently linked to Term, thereby connecting diverse disciplines of science.
His Real-time computing research integrates issues from Sonar, The Internet and Time series.
His Virtual machine research incorporates elements of Reliability, Supercomputer and Virtualization, Full virtualization.
The Host study combines topics in areas such as Range, Linear model and Set.
His work in Range addresses issues such as CPU time, which are connected to fields such as Autoregressive integrated moving average and Simulation.
His most cited work include:
- A case for grid computing on virtual machines (408 citations)
- Demo: indoor localization without infrastructure using the acoustic background spectrum (228 citations)
- Host load prediction using linear models (223 citations)
What are the main themes of his work throughout his whole career to date?
Peter A. Dinda spends much of his time researching Distributed computing, Operating system, Virtual machine, Real-time computing and Embedded system.
In his work, Peter A. Dinda performs multidisciplinary research in Distributed computing and Grid computing.
He interconnects Leverage and Runtime system in the investigation of issues within Operating system.
Many of his studies on Virtual machine apply to Virtual network as well.
His research in Real-time computing intersects with topics in Time series, Microprocessor, Linear model, Power management and Simulation.
In his research, Frequency scaling is intimately related to CPU time, which falls under the overarching field of Embedded system.
He most often published in these fields:
- Distributed computing (27.68%)
- Operating system (27.12%)
- Virtual machine (16.38%)
What were the highlights of his more recent work (between 2012-2020)?
- Operating system (27.12%)
- Compiler (6.78%)
- Parallel computing (6.78%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Operating system, Compiler, Parallel computing, Virtualization and Software.
His Operating system research is mostly focused on the topic Hypervisor.
His biological study spans a wide range of topics, including Scheduling and Nondeterministic algorithm.
He combines subjects such as Virtual machine, Supercomputer, Database and Extreme scale with his study of Virtualization.
The concepts of his Virtual machine study are interwoven with issues in Process and Subroutine.
The study incorporates disciplines such as Xeon Phi, Computer hardware, Latency and Embedded system in addition to Software.
Between 2012 and 2020, his most popular works were:
- Panappticon: event-based tracing to measure mobile application and platform performance (42 citations)
- HAPPE: Human and Application-Driven Frequency Scaling for Processor Power Efficiency (28 citations)
- UStress: Understanding college student subjective stress using wrist-based passive sensing (21 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Programming language
His scientific interests lie mostly in Operating system, Android, Compiler, Embedded system and Parallel computing.
His work carried out in the field of Operating system brings together such families of science as Leverage and Runtime system.
His studies deal with areas such as Floating point and IEEE floating point as well as Compiler.
His Embedded system study combines topics in areas such as Interactive programming, Mobile computing, Adaptation and Electrical efficiency.
His study in Parallel computing is interdisciplinary in nature, drawing from both Semantics, Nondeterministic algorithm and Kernel.
His Software study frequently links to related topics such as Virtual machine.
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