DeepSleep: IEEE 802.11 Enhancement for Energy-Harvesting Machine-to-Machine Communications
Date Issued
2012
Date
2012
Author(s)
Lin, Hsiang-Ho
Abstract
As future Machine-to-Machine (M2M) communications aiming at supporting wireless networks with large coverage and device number, energy-efficient M2M communication design becomes important. To deploy an M2M network which can operate permanently, a large number of M2M devices will be powered by energy harvesting module, which is an emerging technology by which M2M devices can harvest energy from external sources, instead of being powered by batteries. Our research focuses on enhancing WiFi-based communications with energy-harvesting power source, as IEEE 802.11ah sub 1 GHz operation is promising for M2M services. In this paper, we propose DeepSleep, which is designed to support the network in which energy-harvesting devices are widely deployed. The objective of DeepSleep is to reduce the overall outage probability, packet loss rate, delay time and amend energy-efficiency. In this proposed scheme, a low-power device, which has been stayed in sleep mode for a long time, will have higher channel access priority when it wakes up. These devices will have less energy wastage on idle listening and overhearing and go back to sleep mode sooner. In addition, the channel access fairness is also considered. Our simulation results using NS-2 platform demonstrate the effectiveness of the proposed scheme.
Subjects
power saving mode
energy-harvesting
M2M communications
Type
thesis
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