Priority-Aware Actuation Update Scheme in Heterogeneous Industrial Networks
In heterogeneous wireless networked control systems (WNCSs), the age of information (AoI) of the actuation update and actuation update cost are important performance metrics. To reduce the monetary cost, the control system can wait for the availability of a WiFi network for the actuator and then con...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/2/357 |
| _version_ | 1797339451663319040 |
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| author | Yeunwoong Kyung Jihoon Sung Haneul Ko Taewon Song Youngjun Kim |
| author_facet | Yeunwoong Kyung Jihoon Sung Haneul Ko Taewon Song Youngjun Kim |
| author_sort | Yeunwoong Kyung |
| collection | DOAJ |
| description | In heterogeneous wireless networked control systems (WNCSs), the age of information (AoI) of the actuation update and actuation update cost are important performance metrics. To reduce the monetary cost, the control system can wait for the availability of a WiFi network for the actuator and then conduct the update using a WiFi network in an opportunistic manner, but this leads to an increased AoI of the actuation update. In addition, since there are different AoI requirements according to the control priorities (i.e., robustness of AoI of the actuation update), these need to be considered when delivering the actuation update. To jointly consider the monetary cost and AoI with priority, this paper proposes a priority-aware actuation update scheme (PAUS) where the control system decides whether to deliver or delay the actuation update to the actuator. For the optimal decision, we formulate a Markov decision process model and derive the optimal policy based on Q-learning, which aims to maximize the average reward that implies the balance between the monetary cost and AoI with priority. Simulation results demonstrate that the PAUS outperforms the comparison schemes in terms of the average reward under various settings. |
| first_indexed | 2024-03-08T09:48:20Z |
| format | Article |
| id | doaj.art-fddefe13297a46e1b92d90610dd7c5ba |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T09:48:20Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-fddefe13297a46e1b92d90610dd7c5ba2024-01-29T14:13:37ZengMDPI AGSensors1424-82202024-01-0124235710.3390/s24020357Priority-Aware Actuation Update Scheme in Heterogeneous Industrial NetworksYeunwoong Kyung0Jihoon Sung1Haneul Ko2Taewon Song3Youngjun Kim4Division of Information & Communication Engineering, Kongju National University, Cheonan-daero, Cheonan 31080, Republic of KoreaDepartment of Electrical Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of KoreaDepartment of Electronic Engineering, Kyung Hee University, Yongin-si 17104, Republic of KoreaDepartment of Internet of Things, SCH MediaLabs, Soonchunhyang University, 22 Soonchunhyang-ro, Shinchang-myeon, Asan-si 31538, Republic of KoreaSchool of Computer Science and Engineering, Kyungnam University, Changwon-si 51767, Republic of KoreaIn heterogeneous wireless networked control systems (WNCSs), the age of information (AoI) of the actuation update and actuation update cost are important performance metrics. To reduce the monetary cost, the control system can wait for the availability of a WiFi network for the actuator and then conduct the update using a WiFi network in an opportunistic manner, but this leads to an increased AoI of the actuation update. In addition, since there are different AoI requirements according to the control priorities (i.e., robustness of AoI of the actuation update), these need to be considered when delivering the actuation update. To jointly consider the monetary cost and AoI with priority, this paper proposes a priority-aware actuation update scheme (PAUS) where the control system decides whether to deliver or delay the actuation update to the actuator. For the optimal decision, we formulate a Markov decision process model and derive the optimal policy based on Q-learning, which aims to maximize the average reward that implies the balance between the monetary cost and AoI with priority. Simulation results demonstrate that the PAUS outperforms the comparison schemes in terms of the average reward under various settings.https://www.mdpi.com/1424-8220/24/2/357actuation updateage of informationindustrial networkswireless networked control systemsMarkov decision processQ-learning |
| spellingShingle | Yeunwoong Kyung Jihoon Sung Haneul Ko Taewon Song Youngjun Kim Priority-Aware Actuation Update Scheme in Heterogeneous Industrial Networks Sensors actuation update age of information industrial networks wireless networked control systems Markov decision process Q-learning |
| title | Priority-Aware Actuation Update Scheme in Heterogeneous Industrial Networks |
| title_full | Priority-Aware Actuation Update Scheme in Heterogeneous Industrial Networks |
| title_fullStr | Priority-Aware Actuation Update Scheme in Heterogeneous Industrial Networks |
| title_full_unstemmed | Priority-Aware Actuation Update Scheme in Heterogeneous Industrial Networks |
| title_short | Priority-Aware Actuation Update Scheme in Heterogeneous Industrial Networks |
| title_sort | priority aware actuation update scheme in heterogeneous industrial networks |
| topic | actuation update age of information industrial networks wireless networked control systems Markov decision process Q-learning |
| url | https://www.mdpi.com/1424-8220/24/2/357 |
| work_keys_str_mv | AT yeunwoongkyung priorityawareactuationupdateschemeinheterogeneousindustrialnetworks AT jihoonsung priorityawareactuationupdateschemeinheterogeneousindustrialnetworks AT haneulko priorityawareactuationupdateschemeinheterogeneousindustrialnetworks AT taewonsong priorityawareactuationupdateschemeinheterogeneousindustrialnetworks AT youngjunkim priorityawareactuationupdateschemeinheterogeneousindustrialnetworks |