LAPSE:2019.1561
Published Article
LAPSE:2019.1561
On Hybrid Energy Utilization in Wireless Sensor Networks
Mohammad Tala’t, Chih-Min Yu, Meng-Lin Ku, Kai-Ten Feng
December 10, 2019
In a wireless sensor network (WSN), many applications have limited energy resources for data transmission. In order to accomplish a better green communication for WSN, a hybrid energy scheme can supply a more reliable energy source. In this article, hybrid energy utilization—which consists of constant energy source and solar harvested energy—is considered for WSN. To minimize constant energy usage from the hybrid source, a Markov decision process (MDP) is designed to find the optimal transmission policy. With a finite packet buffer and a finite battery size, an MDP model is presented to define the states, actions, state transition probabilities, and the cost function including the cost values for all actions. A weighted sum of constant energy source consumption and a packet dropping probability (PDP) are adopted as the cost value, enabling us to find the optimal solution for balancing the minimization of the constant energy source utilization and the PDP using a value iteration algorithm. As shown in the simulation results, the performance of optimal solution using MDP achieves a significant improvement compared to solution without its use.
Keywords
hybrid energy source, Markov decision process, wireless sensor network
Suggested Citation
Tala’t M, Yu CM, Ku ML, Feng KT. On Hybrid Energy Utilization in Wireless Sensor Networks. (2019). LAPSE:2019.1561
Author Affiliations
Tala’t M: Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu 30012, Taiwan
Yu CM: Department of Electronics Engineering, Chung Hua University, Hsinchu 30012, Taiwan [ORCID]
Ku ML: Department of Communication Engineering, National Central University, Taoyuan 32001, Taiwan [ORCID]
Feng KT: Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu 30012, Taiwan
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Journal Name
Energies
Volume
10
Issue
12
Article Number
E1940
Year
2017
Publication Date
2017-11-23
Published Version
ISSN
1996-1073
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Original Submission
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PII: en10121940, Publication Type: Journal Article
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LAPSE:2019.1561
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doi:10.3390/en10121940
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Dec 10, 2019
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CC BY 4.0
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[v1] (Original Submission)
Dec 10, 2019
 
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Original Submitter
Calvin Tsay
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