Abstract
Energy Harvesting Cognitive Wireless Sensor Network (EH-CRSN) is a novel network which introduces cognitive radio (CR) technology and energy harvesting (EH) technology into traditional WSN. Most of the existing works do not consider that battery capacity of the sensor is limited and will decay over time. Battery capacity degradation will reduce the lifetime of the sensor and affect the performance of the network. In this paper, in order to maximize the network utility of the energy harvesting sensor node in its life cycle, we are concerned with how to determine the optimal sampling rate of sensor node under the condition of battery capacity degradation. Therefore, we propose an optimal adaptive sampling rate control algorithm (ASRC), which can adaptively adjust the sampling rate according to the battery level and effectively manage energy use. In addition, the impact of link capacity on network utility is further investigated. The simulation results verify the effectiveness of the algorithm, which shows that the algorithm is more realistic than the existing algorithm. It can maximize the network utility and improve the overall performance of the network.
This work was supported in part by the Chongqing Basic and Cuttingedge Project under Grant cstc2018jcyjAX0507 and cstc2017jcyjBX0005, National Natural Science Foundation of China under Grant 61671096 and 61379159.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Pei, E., Liu, S., Ran, M. (2020). Energy Management Strategy Based on Battery Capacity Degradation in EH-CRSN (Workshop). In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-030-41117-6_26
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DOI: https://doi.org/10.1007/978-3-030-41117-6_26
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