Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

A reinforcement learning based routing protocol with QoS support for biomedical sensor networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Xuedong Liang ; Interventional Center, Rikshospitalet Univ. Hosp., Oslo ; Balasingham, I. ; Sang-Seon Byun

Biomedical sensor networks have been widely used in medical applications, where data packets usually contain vital sign information and the network used for communications should guarantee that these packets can be delivered to the medical center reliably and efficiently. In other words, a set of requirements for quality of services (QoS) must be satisfied. In this paper, RL-QRP, a reinforcement learning based routing protocol with QoS-support is proposed for biomedical sensor networks. In RL-QRP, optimal routing policies can be found through experiences and rewards without the need of maintaining precise network state information. Simulation results show that RL-QRP performs well in terms of a number of QoS metrics and energy efficiency in various medical scenarios. By investigating the impacts of network traffic load and sensor node mobility on the network performance, RL-QRP has been proved to fit well in dynamic environments.

Published in:

Applied Sciences on Biomedical and Communication Technologies, 2008. ISABEL '08. First International Symposium on

Date of Conference:

25-28 Oct. 2008