His scientific interests lie mostly in Distributed computing, Computer network, Mobile computing, Middleware and Wireless ad hoc network. His Distributed computing study integrates concerns from other disciplines, such as Loose coupling, Service, Event, Component and Reinforcement learning. His Mobile computing research incorporates themes from Wireless and Ubiquitous computing.
His Ubiquitous computing research is multidisciplinary, incorporating elements of World Wide Web, Mobile device, Usability, Authentication and Trust management. His study in Middleware is interdisciplinary in nature, drawing from both Wireless sensor network and Software deployment. His Wireless ad hoc network research includes themes of Mobile ad hoc network and Wireless Routing Protocol.
His primary scientific interests are in Distributed computing, Computer network, Mobile computing, Wireless ad hoc network and Ubiquitous computing. His Distributed computing study combines topics from a wide range of disciplines, such as Middleware, Event, Programming paradigm and Reinforcement learning. His research investigates the connection between Computer network and topics such as Vehicular ad hoc network that intersect with problems in Ad hoc wireless distribution service.
His research brings together the fields of Wireless and Mobile computing. In most of his Wireless ad hoc network studies, his work intersects topics such as Network topology. His study of Context-aware pervasive systems is a part of Ubiquitous computing.
His primary areas of study are Smart grid, Distributed computing, Artificial intelligence, Computer network and Simulation. His Smart grid research integrates issues from Wind power, Electricity, Demand response, Reliability engineering and Electrical grid. The various areas that he examines in his Distributed computing study include Ubiquitous computing, Key distribution in wireless sensor networks, Wireless sensor network and Data mining.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Computer vision and Traffic flow. His biological study spans a wide range of topics, including Wireless ad hoc network and Vehicular ad hoc network. His Simulation study combines topics from a wide range of disciplines, such as VisSim, Real-time computing, Mathematical optimization and Traffic simulation.
His main research concerns Simulation, Real-time computing, Smart grid, Distributed computing and Demand forecasting. He studied Simulation and Renewable energy that intersect with Electricity. His Real-time computing research integrates issues from Intelligent agent, Set, VisSim, Adaptation and Traffic congestion.
His Smart grid study integrates concerns from other disciplines, such as Reliability engineering, Computer engineering, Demand response and Optimal control. His Distributed computing research incorporates themes from Multi-task learning, Ubiquitous computing, Wireless sensor network, Node and Reinforcement learning. His Demand forecasting research includes elements of Artificial neural network, Microgrid, Moving average and Fuzzy logic.
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.
Using trust for secure collaboration in uncertain environments
V. Cahill;E. Gray;J.-M. Seigneur;C.D. Jensen.
IEEE Pervasive Computing (2003)
A framework for developing mobile, context-aware applications
G. Biegel;V. Cahill.
pervasive computing and communications (2004)
STEAM: event-based middleware for wireless ad hoc networks
R. Meier;V. Cahill.
international conference on distributed computing systems (2002)
The K-Component Architecture Meta-model for Self-Adaptive Software
Jim Dowling;Vinny Cahill.
Lecture Notes in Computer Science (2001)
Chisel: a policy-driven, context-aware, dynamic adaptation framework
J. Keeney;V. Cahill.
ieee international workshop on policies for distributed systems and networks (2003)
When TCP Breaks: Delay- and Disruption- Tolerant Networking
S. Farrell;V. Cahill;D. Geraghty;I. Humphreys.
IEEE Internet Computing (2006)
Using feedback in collaborative reinforcement learning to adaptively optimize MANET routing
J. Dowling;E. Curran;R. Cunningham;V. Cahill.
systems man and cybernetics (2005)
Supporting Unanticipated Dynamic Adaptation of Application Behaviour
Barry Redmond;Vinny Cahill.
european conference on object oriented programming (2002)
Taxonomy of Distributed Event-Based Programming Systems
René Meier;Vinny Cahill.
The Computer Journal (2005)
Language-independent aspect-oriented programming
Donal Lafferty;Vinny Cahill.
conference on object oriented programming systems languages and applications (2003)
Profile was last updated on December 6th, 2021.
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