Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery Energy
Applications in wireless sensor networks (WSNs) are rapidly spreading out over the world. The one critical point of WSNs is energy consumption, where the transmitted data is limited by battery energy. Solar energy is used to handle the depletion of the battery energy via photo voltaic (PV) panels. A...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9447792/ |
| _version_ | 1819104663254859776 |
|---|---|
| author | Kanok Charoenchaiprakit Wekin Piyarat Kampol Woradit |
| author_facet | Kanok Charoenchaiprakit Wekin Piyarat Kampol Woradit |
| author_sort | Kanok Charoenchaiprakit |
| collection | DOAJ |
| description | Applications in wireless sensor networks (WSNs) are rapidly spreading out over the world. The one critical point of WSNs is energy consumption, where the transmitted data is limited by battery energy. Solar energy is used to handle the depletion of the battery energy via photo voltaic (PV) panels. A solar energy harvesting WSN (SEH-WSN) node utilizes exponential decision-dynamic duty cycle scheduling based on prospective increase in energy (ED-DSP) to save battery energy by adjusting the duty cycle from an exponential curve and future solar energy. To estimate the prospective solar energy, a prediction technique is applied, but does not guarantee 100% accuracy. Hence, this paper proposes a Markov Decision Process (MDP) to schedule a duty cycle of an SEH-WSN node instead of the ED-DSP depending on the predicted energy. We evaluate its performance via MATLAB simulations with simple irradiance models and real annual irradiance data. The results show that the MDP policy outperforms the ED-DSP. |
| first_indexed | 2024-12-22T02:09:56Z |
| format | Article |
| id | doaj.art-37a96cd67d254564926c4eeabd4a71cf |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T02:09:56Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-37a96cd67d254564926c4eeabd4a71cf2022-12-21T18:42:26ZengIEEEIEEE Access2169-35362021-01-019829478296510.1109/ACCESS.2021.30868839447792Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery EnergyKanok Charoenchaiprakit0https://orcid.org/0000-0003-0744-773XWekin Piyarat1https://orcid.org/0000-0003-4363-2967Kampol Woradit2https://orcid.org/0000-0001-7383-0361Department of Electrical Engineering, Srinakharinwirot University, Ongkharak Campus, Bangkok, ThailandDepartment of Electrical Engineering, Srinakharinwirot University, Ongkharak Campus, Bangkok, ThailandDepartment of Computer Engineering, OASYS Laboratory, Chiang Mai University, Chiang Mai, ThailandApplications in wireless sensor networks (WSNs) are rapidly spreading out over the world. The one critical point of WSNs is energy consumption, where the transmitted data is limited by battery energy. Solar energy is used to handle the depletion of the battery energy via photo voltaic (PV) panels. A solar energy harvesting WSN (SEH-WSN) node utilizes exponential decision-dynamic duty cycle scheduling based on prospective increase in energy (ED-DSP) to save battery energy by adjusting the duty cycle from an exponential curve and future solar energy. To estimate the prospective solar energy, a prediction technique is applied, but does not guarantee 100% accuracy. Hence, this paper proposes a Markov Decision Process (MDP) to schedule a duty cycle of an SEH-WSN node instead of the ED-DSP depending on the predicted energy. We evaluate its performance via MATLAB simulations with simple irradiance models and real annual irradiance data. The results show that the MDP policy outperforms the ED-DSP.https://ieeexplore.ieee.org/document/9447792/Solar energy harvestingMarkov decision processwireless sensor network |
| spellingShingle | Kanok Charoenchaiprakit Wekin Piyarat Kampol Woradit Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery Energy IEEE Access Solar energy harvesting Markov decision process wireless sensor network |
| title | Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery Energy |
| title_full | Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery Energy |
| title_fullStr | Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery Energy |
| title_full_unstemmed | Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery Energy |
| title_short | Optimal Data Transfer of SEH-WSN Node via MDP Based on Duty Cycle and Battery Energy |
| title_sort | optimal data transfer of seh wsn node via mdp based on duty cycle and battery energy |
| topic | Solar energy harvesting Markov decision process wireless sensor network |
| url | https://ieeexplore.ieee.org/document/9447792/ |
| work_keys_str_mv | AT kanokcharoenchaiprakit optimaldatatransferofsehwsnnodeviamdpbasedondutycycleandbatteryenergy AT wekinpiyarat optimaldatatransferofsehwsnnodeviamdpbasedondutycycleandbatteryenergy AT kampolworadit optimaldatatransferofsehwsnnodeviamdpbasedondutycycleandbatteryenergy |