The scientist’s investigation covers issues in Distributed computing, Network on a chip, Computer network, Real-time computing and Embedded system. His Distributed computing research also works with subjects such as
His research ties Mesh networking and Computer network together. Juha Plosila has researched Real-time computing in several fields, including Energy consumption, Stochastic hill climbing, Algorithm design and Cloud computing. The concepts of his Embedded system study are interwoven with issues in Frequency scaling, Power management, Dark silicon and Error detection and correction.
His main research concerns Embedded system, Distributed computing, Network on a chip, Computer network and Asynchronous communication. As part of the same scientific family, he usually focuses on Embedded system, concentrating on Fault tolerance and intersecting with Reliability. His work carried out in the field of Distributed computing brings together such families of science as Static routing, Geographic routing, Routing protocol and Control reconfiguration.
His Network on a chip research incorporates elements of Routing, Energy consumption, Algorithm design, Parallel computing and Network interface. The study incorporates disciplines such as Real-time computing and Cloud computing in addition to Energy consumption. His work deals with themes such as Computer architecture, Very-large-scale integration, Formal methods and Modular design, which intersect with Asynchronous communication.
His primary areas of study are Artificial intelligence, Swarm behaviour, Computer vision, Event and Distributed computing. His work on Feature selection as part of general Artificial intelligence study is frequently linked to Consciousness, therefore connecting diverse disciplines of science. His research on Swarm behaviour also deals with topics like
His Energy consumption research is multidisciplinary, relying on both Computer hardware, Service-level agreement, Resource, Heuristic and PlanetLab. His study in Event is interdisciplinary in nature, drawing from both Pixel, High dynamic range and Asynchronous communication. Juha Plosila has included themes like Scalability, Dependability, Reliability and Cloud computing in his Distributed computing study.
Juha Plosila spends much of his time researching Swarm behaviour, Drone, Collision avoidance, Artificial intelligence and Distributed computing. In his study, Morphing and Efficient energy use is strongly linked to Control theory, which falls under the umbrella field of Swarm behaviour. His Collision avoidance research includes elements of Node, Robotics and Systems engineering.
The Artificial intelligence study combines topics in areas such as Frame and Computer vision. His Distributed computing study deals with Cloud computing intersecting with Container. His biological study spans a wide range of topics, including Energy consumption, Service-level agreement, Resource and Heuristic.
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.
Timepix3: a 65K channel hybrid pixel readout chip with simultaneous ToA/ToT and sparse readout
T Poikela;J Plosila;T Westerlund;M Campbell.
Journal of Instrumentation (2014)
Using Ant Colony System to Consolidate VMs for Green Cloud Computing
Fahimeh Farahnakian;Adnan Ashraf;Tapio Pahikkala;Pasi Liljeberg.
IEEE Transactions on Services Computing (2015)
Network on Chip Routing Algorithms
Ville Rantala;Teijo Lehtonen;Juha Plosila.
LiRCUP: Linear Regression Based CPU Usage Prediction Algorithm for Live Migration of Virtual Machines in Data Centers
Fahimeh Farahnakian;Pasi Liljeberg;Juha Plosila.
software engineering and advanced applications (2013)
Online Reconfigurable Self-Timed Links for Fault Tolerant NoC
Teijo Lehtonen;Pasi Liljeberg;Juha Plosila.
Vlsi Design (2007)
Energy-Efficient Virtual Machines Consolidation in Cloud Data Centers Using Reinforcement Learning
Fahimeh Farahnakian;Pasi Liljeberg;Juha Plosila.
parallel, distributed and network-based processing (2014)
Smart hill climbing for agile dynamic mapping in many-core systems
Mohammad Fattah;Masoud Daneshtalab;Pasi Liljeberg;Juha Plosila.
design automation conference (2013)
Self-Adaptive System for Addressing Permanent Errors in On-Chip Interconnects
T. Lehtonen;D. Wolpert;P. Liljeberg;J. Plosila.
IEEE Transactions on Very Large Scale Integration Systems (2010)
Energy-Aware VM Consolidation in Cloud Data Centers Using Utilization Prediction Model
Fahimeh Farahnakian;Tapio Pahikkala;Pasi Liljeberg;Juha Plosila.
IEEE Transactions on Cloud Computing (2019)
Congestion aware, fault tolerant, and thermally efficient inter-layer communication scheme for hybrid NoC-bus 3D architectures
Amir-Mohammad Rahmani;Khalid Latif;Kameswar Rao Vaddina;Pasi Liljeberg.
networks on chips (2011)
Profile was last updated on December 6th, 2021.
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