@article{
 title = {Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks},
 type = {article},
 year = {2016},
 identifiers = {[object Object]},
 volume = {11},
 id = {02b6bb51-8b09-3606-a977-8df8706708f8},
 created = {2017-02-09T03:48:45.000Z},
 file_attached = {false},
 profile_id = {99d2800d-478b-301c-a879-4ec8c5b094e5},
 last_modified = {2017-03-25T00:40:59.198Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Fang2016},
 abstract = {© 2016 Fang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.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 ë. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter á 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.},
 bibtype = {article},
 author = {Fang, G. and Orgun, M.A. and Shankaran, R. and Dutkiewicz, E. and Zheng, G.},
 journal = {PLoS ONE},
 number = {2}
}

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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 ë. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter á 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.","bibtype":"article","author":"Fang, G. and Orgun, M.A. and Shankaran, R. and Dutkiewicz, E. and Zheng, G.","journal":"PLoS ONE","number":"2","bibtex":"@article{\n title = {Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks},\n type = {article},\n year = {2016},\n identifiers = {[object Object]},\n volume = {11},\n id = {02b6bb51-8b09-3606-a977-8df8706708f8},\n created = {2017-02-09T03:48:45.000Z},\n file_attached = {false},\n profile_id = {99d2800d-478b-301c-a879-4ec8c5b094e5},\n last_modified = {2017-03-25T00:40:59.198Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n citation_key = {Fang2016},\n abstract = {© 2016 Fang et al. 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