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An Emergency Adaptive Communication Protocol for Driver Health Monitoring in WSN Based Vehicular Environments

Title
An Emergency Adaptive Communication Protocol for Driver Health Monitoring in WSN Based Vehicular Environments
Authors
Kim, Young-DukKwon, SoonJung, Woo YoungKim, Dongkyun
DGIST Authors
Kim, Young-DukKwon, SoonJung, Woo Young
Issue Date
2015
Citation
International Journal of Distributed Sensor Networks
Type
Article
Article Type
Article
Keywords
Activity MonitoringAdaptive CommunicationsBetter PerformanceChannel ContentionPacket Delivery RatioPeriodic CalculationsQueue Management SchemeSensor NetworksVehicular EnvironmentsWireless Sensor Networks (WSNs)
ISSN
1550-1329
Abstract
Driver health and activity monitoring is one of the principal design issues for the safety provision in vehicular environments. Recently, the wireless sensor network technology is widely used to address the concerns in such applications. However, only few conventional protocols have dealt with reliable and prompt delivery of emergency packets considering the vehicular specifications. In this paper, we propose an emergency adaptive communication protocol, which treats the data packet in a discriminatory manner by investigating whether it is emergency or not. Hence, the proposed protocol defines an emergency factor for each data packet and exploits it for both route establishment and channel access procedures. In route establishment, the proposed protocol chooses a route with low delay and high reliability among the candidates by periodic calculation of emergency factor. Then, it dynamically adjusts back-off parameters before participating in the channel contention among the neighbors. In addition, an emergency aware queue management scheme and packet drop policy are proposed to improve the reliability of emergency data traffic during transmission. Our simulation results show that the proposed protocol provides a better performance compared with the existing protocol in terms of packet delivery ratio, end-to-end packet delay, and number of dropped packets. © 2015 Young-Duk Kim et al.
URI
http://hdl.handle.net/20.500.11750/5222
DOI
10.1155/2015/704253
Publisher
Hindawi Publishing Corporation
Related Researcher
  • Author Jung, Woo Young  
  • Research Interests Artificial Intelligence, Machine Learning, Autonomous Driving
Files:
There are no files associated with this item.
Collection:
Convergence Research Center for Future Automotive Technology1. Journal Articles


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