There has been significant works on developing energy harvesting sensor network such as Heliomote[1][3] and Prometheus[2]. Those two prototypes make the sensor nodes could work for seven to ten days by using the solar energy. Besides solar power sensor nodes [4][5][6][7], recent works have explored scenarios that a solar power embedded system that consists of sensor nodes, rechargeable battery and solar panels[8][9][10][11][12]. Such embedded system can be deployed at the remote places like forest or mountain without electrical power line.
There are also growing number of energy harvesting model related works to make the power consumption of sensor nodes or system more efficiency [5~14]. Energy harvesting model is a prediction model that system can follow the result of the model and work perpetually. Energy model is usually developed by the collected real environment solar radiation. Energy harvesting model research can be divided into two parts: Energy model only and Energy model driven.
Energy model only means that the objective is to make the nodes or systems operate perpetually. The work [6][10] focus on the model for determining the battery or capacitor size. The work [11][12] aims to achieve the best performance based on the proposed energy model.
Energy model driven means the objective is not only to operate perpetually but also to make other processes successfully based on energy model. Other services are like to optimize the data rate or energy allocation for all network nodes [5][7][9][13][14].
There is also an effective storage replication service is proposed according to the energy model [8].
Our work is similar to the work [13], we deployed the system over two years and collected real and long-term data including the solar radiance and system power characteristics. The difference to the work [13] is we are going to propose an effective energy model and aim to adjust the duty cycle that makes our system operate perpetually.
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[6] J. Taneja, J. Jeong, and D. Culler, "Design, modeling, and capacity planning for micro-solar power sensor networks," in IPSN, 2008.
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[8] Y. Yang, L. Wang, D. K. Doh, H. Le, and T. Abdelzaher, "Solarstore: Enhancing data reliability in solar-powered storage-centric sensor networks," in Mobisys, 2009
[9]D. K. Noh, L. Wang, Y. Yang, H. K. Le, and T. Abdelzaher, "Minimum variance energy allocation for a solar-powered sensor system," in DCOSS, 2009.
[10] Jeremy Gummeson , Shane S. Clark , Kevin Fu , Deepak Ganesan, “On the limits of effective hybrid micro-energy harvesting on mobile CRFID sensors,”
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[11] Zhaoting Jiang; Xinyu Jin; Yu Zhang, ”A Weather-Condition Prediction Algorithm for Solar-Powered Wireless Sensor Nodes,” in 6th International Conference
Wireless Communications Networking and Mobile Computing (WiCOM), 2010
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SECON'10, June 2010.
[14] M. Gorlatova, A. Wallwater, and G. Zussman, "Networking low-power energy harvesting devices: Measurements and algorithms," in Proc. IEEE INFOCOM'11,
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