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Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks.
Fang, Gengfa; Orgun, Mehmet A; Shankaran, Rajan; Dutkiewicz, Eryk; Zheng, Guanglou.
Affiliation
  • Fang G; Department of Engineering, Macquarie University, Sydney, NSW 2109, Australia.
  • Orgun MA; Department of Computing, Macquarie University, Sydney, NSW 2109, Australia.
  • Shankaran R; Department of Computing, Macquarie University, Sydney, NSW 2109, Australia.
  • Dutkiewicz E; School of Computing and Communications, University of Technology, Sydney, Broadway, NSW 2007, Australia.
  • Zheng G; Department of Engineering, Macquarie University, Sydney, NSW 2109, Australia.
PLoS One ; 11(2): e0148376, 2016.
Article in En | MEDLINE | ID: mdl-26844888
ABSTRACT
As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner's bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Monitoring, Ambulatory / Wireless Technology / Models, Theoretical Type of study: Prognostic_studies Limits: Humans Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2016 Document type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Monitoring, Ambulatory / Wireless Technology / Models, Theoretical Type of study: Prognostic_studies Limits: Humans Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2016 Document type: Article Affiliation country: Australia