Analytical modeling of multi-type failures in wireless body area networks

Author

Wang, Song ; Nah, Jae-Wook ; Seak, Ki-Jung ; Park, Jong-Tae

Author_Institution

Sch. of Electr. Eng. & Comput. Sci., Kyungpook Nat. Univ., Daegu, South Korea

fYear

2009

fDate

18-20 Oct. 2009

Firstpage

242

Lastpage

246

Abstract

Wireless body area network is one of the most suitable technologies for building patient monitoring systems in hospitals, residential and work environment. The reliability of wireless body area networks is an important research issue since it may jeopardize the vital human life, unless managed properly. In this paper, a new modeling and analysis of in multi-type failures in a wireless body area networks is presented. First, the nodes are classified into types in accordance with their functions. Then, the node behavior has been modeled using a novel semi-Markov process. Simulation has finally been performed to evaluate the performance of the proposed model.

Keywords

Markov processes; body area networks; health care; patient monitoring; telecommunication network reliability; telecommunication security; telemedicine; ubiquitous computing; U-healthcare service; WBAN; analytical multitype failure modeling; hospital environment; network security; node behavior classification model; patient monitoring system; performance modeling; residential environment; semiMarkov process; ubiquitous-healthcare service; wireless body area network reliability; work environment; Analytical models; Biological system modeling; Biosensors; Body sensor networks; Failure analysis; Humans; Intelligent sensors; Routing; Spread spectrum communication; Wireless sensor networks; Analysis of multi-type failures; Network security; Performance modeling; WBAN;

fLanguage

English

Publisher

ieee

Conference_Titel

Broadband Network & Multimedia Technology, 2009. IC-BNMT '09. 2nd IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-4590-5

Electronic_ISBN

978-1-4244-4591-2

Type

conf

DOI

10.1109/ICBNMT.2009.5348487

Filename

5348487