Title
An efficient sensor network architecture using open platform in vehicle environment
Abstract
Vehicles have been developed with an objective of safety. A large number of sensors will be required in Advanced Safety Vehicles that provide intelligent and automatic services in future ITS(Intelligent Transport Systems) circumstances. Because current in-vehicle networks must be changed to add new sensors, the number of sensors that can be added is restricted in current in-vehicle networks. To manage the sensors more efficiently and to provide extensibility, we propose a SCSN (Smart Car Sensor Network), which is an in-vehicle architecture based on AMI-C and OSGi standards. In this architecture, Vehicle Interface (VI), defined in the AMI-C standard, performs as a gateway in an AMIC network. An integrated VI structure has been developed to provide a Vehicle Service (VS) on a standard platform. An interworking structure with a CAN(Controller Area Network) interface is implemented to provide an efficient VI. In current telematics architecture, time delay occurs between the CAN network start-up time and the platform booting time. Message loss occurs during this time delay. In this paper, we propose an efficient gateway architecture to minimize message loss due to this time delay. The efficiency of this platform has been verified using CANoe, which is a vehicle-network simulation tool.
Year
DOI
Venue
2006
10.1007/978-3-540-71789-8_24
ICUCT
Keywords
Field
DocType
integrated vi structure,message loss,open platform,vehicle environment,efficient vi,current telematics architecture,in-vehicle architecture,efficient sensor network architecture,standard platform,time delay,network start-up time,current in-vehicle network,efficient gateway architecture,network simulator,sensor network,telematics,controller area network
CAN bus,Open platform,Network architecture,Real-time computing,Default gateway,Intelligent transportation system,Engineering,Wireless sensor network,Telematics,Intelligent computer network,Embedded system
Conference
Volume
ISSN
Citations 
4412
0302-9743
2
PageRank 
References 
Authors
0.43
1
4
Name
Order
Citations
PageRank
Hongbin Yim1111.82
Pyungsun Park271.78
Heeseok Moon371.10
Jaeil Jung417426.82