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Cognitive energy efficient for closed-proximity devices: An empirical study and standardization issues

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dc.contributor.authorHashim W.en_US
dc.contributor.authorIsmail A.F.en_US
dc.contributor.authorKamrul M.H.en_US
dc.contributor.authorBadron K.en_US
dc.contributor.authorRaj R.M.en_US
dc.contributor.authorNasir H.A.en_US
dc.contributor.authorid11440260100en_US
dc.contributor.authorid36602773900en_US
dc.contributor.authorid56532507700en_US
dc.contributor.authorid35387519800en_US
dc.contributor.authorid56996859800en_US
dc.contributor.authorid56532389900en_US
dc.date.accessioned2023-05-29T06:02:04Z
dc.date.available2023-05-29T06:02:04Z
dc.date.issued2015
dc.description.abstractWe describe empirical study findings on the impact of throughput performance when transmission power is adjusted among access points in closed-proximity network devices. The experiment was conducted in an office environment to emulate such wireless LAN network. We introduce a potential energy efficient mechanism based on cognitively learning one of the attributes which then triggers the power selection. We show that similar throughput performance at the client can be obtained at reduced transmission power thus prevent an access point from maximizing power unnecessarily. We have also evaluated the impact of increasing and reducing power to other neighbouring access points. It was found that the improvement of throughput is increased to 44% maximum. Throughput performance alert is introduced in the mechanism to be aware of sudden throughput changes in the system. � 2006-2015 Asian Research Publishing Network (ARPN).en_US
dc.description.natureFinalen_US
dc.identifier.epage992
dc.identifier.issue3
dc.identifier.scopus2-s2.0-84923851986
dc.identifier.spage987
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84923851986&partnerID=40&md5=3abf01288cf39781075147e65e78ac7f
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22564
dc.identifier.volume10
dc.publisherAsian Research Publishing Networken_US
dc.sourceScopus
dc.sourcetitleARPN Journal of Engineering and Applied Sciences
dc.titleCognitive energy efficient for closed-proximity devices: An empirical study and standardization issuesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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