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Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
ISBN: 978-0-7695-3507-4
pp: 529-533
In this paper, the application of individual scenario-based traffic models in identifying the traffic carrying needs of networks in patient monitoring environments is presented. Since the total number of traffic sources is small for a central limit theorem-like approximation, a simple traffic matrix for each scenario can be used to identify the capacity needed for carrying data. The data traffic is classified into three categories; constant bit rate (CBR), On-Off, and Impulsive. In digital communications, the Impulsive traffic is considered a limiting case of the On-Off traffic. Lack of standard mechanisms for digitization of the patient monitoring data offers a unique challenge for traffic modeling. Sample traffic characteristics in a certain scenario are used to demonstrate that the network does not have to be designed for a very high bit rate even if some sources occasionally generate high data rates. This is due to the fact that a source generating high data rate could do so only for a small fraction of time, which results in smoothing out the data over longer periods of time.
Traffic Modeling, Patient Monitoring
Matthew Scott Alley, W. Jason Naramore, Nee-Yin Chou, Aftab Ahmad, Anton Riedl, "Scenario-Based Traffic Modeling for Data Emanating from Medical Instruments in Clinical Environment", Computer Science and Information Engineering, World Congress on, vol. 01, no. , pp. 529-533, 2009, doi:10.1109/CSIE.2009.969
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