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dc.contributor.authorJunichi Suzukien_US
dc.contributor.authorPruet Boonmaen_US
dc.contributor.authorDung H. Phanen_US
dc.date.accessioned2018-09-04T09:48:57Z-
dc.date.available2018-09-04T09:48:57Z-
dc.date.issued2014-01-01en_US
dc.identifier.other2-s2.0-84902590976en_US
dc.identifier.other10.1109/DICTAP.2014.6821659en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84902590976&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/53420-
dc.description.abstractThis paper considers natural neurons as a physical communication medium and defines a Time Division Multiple Access (TDMA) communication protocol on top of the physical layer to construct intrabody nanonetworks, each of which networks nanoscale nodes to perform sensing and actuation tasks in the body for biomedical and prosthetic purposes. The proposed protocol, called Neuronal TDMA, leverages a novel evolutionary multiobjective optimization algorithm (EMOA) to seek the optimal signaling schedule for individual nodes in the network with respect to conflicting optimization objectives such as signaling delay and fairness while avoiding signal interference. Simulation results show that the proposed EMOA efficiently obtains quality TDMA signaling schedules and outperforms existing EMOAs. © 2014 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleNeuronal signaling optimization for intrabody nanonetworksen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2014 4th International Conference on Digital Information and Communication Technology and Its Applications, DICTAP 2014en_US
article.stream.affiliationsUniversity of Massachusetts Bostonen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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