UbiCap: A Capability-based Run-time Model for Heterogeneous Sensors Management in Ubiquitous Operating System
Pages 134 - 143
Abstract
The Ubiquitous Operating System(UOS) is a new type of operating system in response to the new patterns and scenarios of future human-cyber-physical ternary ubiquitous computing. Compared with traditional operating systems, one of the fundamental requirements of UOS is to adaptively manage numerous heterogeneous sensors according to dynamic environments and diverse tasks. However, traditional management focuses on the sensors’ parameters and interfaces without highlighting the perception effect that is users’ concern and dynamic changing. It also lacks a unified management approach for heterogeneous sensors. To overcome the limitations, we propose a novel heterogeneous sensors dynamic management model UbiCap, i.e., Ubiquitous Capability, which is based on the capability abstraction and adaptive run-time capability management mechanism. The capability provides a unified abstract for heterogeneous sensors. The adaptive run-time capability management mechanism transfers the management object from low-level hardware sensors to high-level sensing capability. The capability required and the available capability are matched to support run-time adaptive sensors selection. We implement a software prototype iS2ROS(intelligent Sensor Selection Robot Operating System) based on the UbiCap model. We then simulate a forest fire spot monitoring scenario where iS2ROS selects the optimal image sensor during the identification task execution while light or weather condition changes. Experiment results show that the iS2ROS achieves comparative sensing effectiveness through UbiCap with 50% power consumption lower compared to the traditional both-sensors approach.
References
[1]
Gordon Blair, Nelly Bencomo, and Robert B. France. 2009. Models@ run.time. Computer 42, 10 (2009), 22–27. https://doi.org/10.1109/MC.2009.326
[2]
L Castañeda Bueno. 2017. Runtime modelling for user-centric smart cyber-physical-human applications. Doctoral Dissertation,University of Victoria,Canada (2017).
[3]
Marton Bur, Gabor Szilagyi, Andras Voros, and Daniel Varro. 2020. Distributed graph queries over [email protected] for runtime monitoring of cyber-physical systems. International Journal on Software Tools for Technology Transfer 22, 1 (2020), 79–102.
[4]
Donggang Cao, Dongliang Xue, Zhiyi Ma, and Hong Mei. 2021. XiUOS:an open-source ubiquitous operating system for industrial Internet of Things. Science China Information Sciences 65, 1 (2021).
[5]
Xing Chen, Zhiming Huang, Xinshu Ye, Yun Ma, Yiyan Chen, and Wenzhong Guo. 2019. Approach to Modeling and Executing Context-aware Services of Smart Home at Runtime. Journal of software11 (2019), 3297–3312.
[6]
Xing Chen, Wei Zhang, Gang Huang, Aipeng Li, Wenzhong Guo, and Guolong Chen. 2014. Wireless sensor network management method based on runtime model. Journal of software 25, 8 (2014), 17.
[7]
Lenin Erazo-Garzón, Ariana Román, José Moyano-Dután, and Priscila Cedillo. 2021. Models@runtime and Internet of Things: A Systematic Literature Review. In 2021 Second International Conference on Information Systems and Software Technologies (ICI2ST). 128–134. https://doi.org/10.1109/ICI2ST51859.2021.00026
[8]
Johannes Erbel, Thomas Brand, Holger Giese, and Jens Grabowski. 2019. OCCI-Compliant, Fully Causal-Connected Architecture Runtime Models Supporting Sensor Management. In 2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). 188–194. https://doi.org/10.1109/SEAMS.2019.00032
[9]
Huang Gang, Song Hui, and Mei Hong. 2009. SM@RT: towards architecture-based runtime management of Internetware systems. Proceedings of the 1st Asia-Pacific Symposium on Internetware, Internetware 2009 (10 2009). https://doi.org/10.1145/1640206.1640215
[10]
Mei Hong. 2021. The 20-year Periodic Law of Operating System Transition and Ubiquitous Computing. China Industry & Information Technology 000, 001 (2021), P.54–57.
[11]
Mei Hong, Cao DongGang, and Xie Tao. 2022. Ubiquitous Operating System: Toward the Blue Ocean of Human-cyber-physical Ternary Ubiquitous Computing. Bulletin of Chinese Academy of Sciences 37, 1 (2022), 8.
[12]
Mei Hong and Guo Yao. 2018. Toward Ubiquitous Operating Systems: A Software-Defined Perspective. Computer 51, 1 (2018), 50–56. https://doi.org/10.1109/MC.2018.1151018
[13]
Igor Khokhlov, Akshay Pudage, and Reznik Leon. 2019. Sensor Selection Optimization with Genetic Algorithms. In 2019 IEEE SENSORS. 1–4. https://doi.org/10.1109/SENSORS43011.2019.8956579
[14]
Ege Korkan, Miguel Romero Karam, Sebastian Kaebisch, and Sebastian Steinhorst. 2021. Runtime Deployment, Management and Monitoring of Web of Things Systems. In 2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS). 1–6. https://doi.org/10.1109/COINS51742.2021.9524213
[15]
A. Miele, H. Zarate, L. Cassano, C. Bolchini, and J. E. Ortiz. 2022. A Runtime Resource Management and Provisioning Middleware for Fog Computing Infrastructures. ACM Transactions on Internet of Things3 (2022), 3.
[16]
Naser Hossein Motlagh, Miloud Bagaa, and Tarik Taleb. 2016. UAV Selection for a UAV-Based Integrative IoT Platform. In 2016 IEEE Global Communications Conference (GLOBECOM). 1–6. https://doi.org/10.1109/GLOCOM.2016.7842359
[17]
Henry Muccini, Mohammad Sharaf, and Danny Weyns. 2016. Self-Adaptation for Cyber-Physical Systems: A Systematic Literature Review. In 2016 IEEE/ACM 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). 75–81. https://doi.org/10.1145/2897053.2897069
[18]
Haoyu Ren, Darko Anicic, and Thomas A. Runkler. 2022. Towards Semantic Management of On-Device Applications in Industrial IoT. ACM Trans. Internet Technol. 22, 4, Article 102 (nov 2022), 30 pages. https://doi.org/10.1145/3510820
[19]
Denis Smirnov and Stutz Peter. 2017. Use case driven approach for ontology-based modeling of reconnaissance resources on-board UAVs using OWL. In 2017 IEEE Aerospace Conference. 1–17. https://doi.org/10.1109/AERO.2017.7943606
[20]
Ghimire Sudeep, Sarraipa João, Agostinho Carlos, and Jardim-Gonçalves Ricardo. 2017. Fault tolerant sensing model for cyber-physical systems. In Proceedings of the Symposium on Model-driven Approaches for Simulation Engineering, Mod4Sim 2017, Virginia Beach, VA, USA, April 23 - 26, 2017, D’Ambrogio Andrea, Durak Umut, and Deniz Çetinkaya (Eds.). ACM, 10:1–10:9. http://dl.acm.org/citation.cfm?id=3108254
[21]
Sirine Taleb, HajjHazem, and Dawy Zaher. 2019. EGO: Optimized Sensor Selection for Multi-Context Aware Applications with an Ontology for Recognition Models. IEEE Transactions on Mobile Computing 18, 11 (2019), 2518–2535. https://doi.org/10.1109/TMC.2018.2879864
[22]
Marcello Thiry and Roger Schmidt. 2017. Self-adaptive Systems Driven by Runtime Models. Proceedings of the International Conference on Software Engineering, 248–253. https://doi.org/10.1829/32017-168
[23]
Ranran Wang, Wenling Wei, Mingchao Yang, and Wei Liu. 2020. Task allocation of multiple UAVs considering cooperative route planning. Acta Aeronautica ET Astronautica Sinica 41, S2, Article 724234 (2020), 0 pages. https://doi.org/10.7527/S1000-6893.2020.24234
[24]
Jiuqiang Xu, Xuejing Guo, Jinfa Wang, Hequn Li, and Zhao Hai. 2018. Research on CPS resource service model and resource scheduling. Chinese Journal of Computers. Chinese Journal of Computers 41, 10 (2018), 14.
[25]
Xiaojun Yang and Ruixin Niu. 2018. Adaptive Sensor Selection for Nonlinear Tracking via Sparsity-Promoting Approaches. IEEE Trans. Aerospace Electron. Systems 54, 4 (2018), 1966–1982. https://doi.org/10.1109/TAES.2018.2805258
[26]
Mingyue Zhang, Zhi Jin, Haiyan Zhao, and Yixing Luo. 2020. Survey of machine learning enabled software self-adaptation. Journal of Software 31, 8 (8 2020), 2404–2431.
[27]
P. Zhang and J. Wang. 2015. Management of Intelligent Campus Wireless Sensor Networks Based on Runtime Model. Journal of Computer & Communications 03, 7 (2015), 22–31.
[28]
Tianqi Zhao, Haiyan Zhao, Wei Zhang, and Zhi Jin. 2018. Overview of model-based adaptive methods. Journal of Software 29, 1 (1 2018), 23–41.
Index Terms
- UbiCap: A Capability-based Run-time Model for Heterogeneous Sensors Management in Ubiquitous Operating System
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Published In
August 2023
332 pages
ISBN:9798400708947
DOI:10.1145/3609437
- Editors:
- Hong Mei,
- Jian Lv,
- Zhi Jin,
- Xuandong Li,
- Xiaohu Yang,
- Xin Xia
Copyright © 2023 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 05 October 2023
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