Paper Info
Title
An Application Framework for Loosely Coupled Networked Cyber-Physical Systems
Abstract
Networked Cyber-Physical Systems (NCPSs) present many challenges since they require a tight combination with the physical world as well as a balance between autonomous operation and coordination among heterogeneous nodes. These fundamental challenges range from how NCPSs are architected, implemented, composed, and programmed to how they can be validated. In this paper, we describe a new paradigm for programming an NCPS that enables users to specify their needs and nodes to contribute capabilities and resources. This new paradigm is based on the partially ordered knowledge-sharing model that makes explicit the abstract structure of a computation in space and time. Based on this model, we propose an application framework that provides a uniform abstraction for a wide range of NCPS applications, especially those concerned with distributed sensing, optimization, and control. The proposed framework provides a generic service to represent, manipulate, and share knowledge across the network under minimal assumptions on connectivity. Our framework is tested on a new distributed version of an evolutionary optimization algorithm that runs on a computing cluster and is also used to solve a dynamic distributed optimization problem in a simulated NCPS that uses mobile robots as controllable data mules.
Year
DOI
Venue
2010
10.1109/EUC.2010.30
EUC
Keywords
Field
DocType
networked cyber-physical systems,wide range,evolutionary computation,simulated ncps,proposed framework,partially ordered knowledge-sharing model,knowledge-sharing model,dynamic distributed optimization problem,knowledge management,distributed control,ncps application framework,ncps programming,distributed sensing,optimization problem,new paradigm,distributed optimization,application framework,loosely coupled networked system,networked cyper-physical systems,knowledge sharing,evolutionary optimization algorithm,ncps application,distributed processing,computational modeling,optimization,knowledge engineering,robot kinematics,partial order,mobile robot,cyber physical systems
Computer science,Evolutionary computation,Robot kinematics,Cyber-physical system,Knowledge engineering,Optimization problem,Mobile robot,Computer cluster,Computation,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-0-7695-4322-2
19
1.07
References 
Authors
22
4
Name
Order
Citations
PageRank
Minyoung Kim1564.14
Mark-oliver Stehr237729.62
Jinwoo Kim31918168.52
Soonhoi Ha41684174.65