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|Title:||Cognitive energy efficient for closed-proximity devices: An empirical study and standardization issues||Authors:||Hashim, W.
|Issue Date:||2015||Journal:||Cognitive energy efficient for closed-proximity devices: An empirical study and standardization issues. ARPN Journal of Engineering and Applied Sciences, 10(3), 987-992||Abstract:||We 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).||URI:||https://pure.uniten.edu.my/en/publications/cognitive-energy-efficient-for-closed-proximity-devices-an-empiri|
|Appears in Collections:||CCI Scholarly Publication|
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