Energy Prediction Based MAC Layer Optimization for Harvesting Enabled WSNs in Smart Cities

MAC layer adaptation is very crucial for supporting dense and diverse data requirements of sensor networks in smart cities, powered by energy harvesting. In this paper, we perform MAC layer optimization for maximizing throughput subject to application-specific needs and energy availability in Solar...

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Bibliographic Details
Published in2018 IEEE 87th Vehicular Technology Conference (VTC Spring) pp. 1 - 6
Main Authors Amjad, Madiha, Qureshi, Hassaan Khaliq, Lestas, Marios, Mumtaz, Shahid, Rodrigues, Joel J. P. C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2018
Subjects
Analytical models
Energy consumption
Energy harvesting
Mathematical model
Optimization
Reliability
Throughput
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ISSN2577-2465
DOI10.1109/VTCSpring.2018.8417855

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Summary:MAC layer adaptation is very crucial for supporting dense and diverse data requirements of sensor networks in smart cities, powered by energy harvesting. In this paper, we perform MAC layer optimization for maximizing throughput subject to application-specific needs and energy availability in Solar Energy Harvesting Wireless Sensor Networks (EH-WSNs). In contrast to previous schemes that limit energy consumption based on current availability only, we propose Energy Prediction based Energy Management algorithm (EPEM). This algorithm exploits energy prediction and sets threshold rate of energy consumption to ensure accumulation of sufficient energy for non- energy harvesting period. Our analysis shows that MAC optimization (MO) along with EPEM algorithm not only improves performance by 72% but also avoids energy scarcity during non-energy harvesting period.
ISSN:2577-2465
DOI:10.1109/VTCSpring.2018.8417855