Chen-Tui Hung
Skip Abstract Section
Abstract
Battery-less devices offer potential solutions for maintaining sustainable Internet of Things (IoT) networks. However, limited energy harvesting capacity can lead to power failures, limiting the system’s quality of service (QoS). To improve timely task progress, we present ETIME, a scheduling framework that enables energy-efficient communication for intermittent-powered IoT devices. To maximize energy efficiency while meeting the timely requirements of intermittent systems, we first model the relationship between insufficient harvesting energy and task behavior time. We then propose a method for predicting response times for battery-less devices. Considering both delays from multiple task interference and insufficient system energy, we introduce a dynamic wake-up strategy to improve timely task progress. Additionally, to minimize power consumption from connection components, we propose a dynamic connection interval adjustment to provide energy-efficient communication. The proposed algorithms are implemented in a lightweight operating system on real devices. Experimental results show that our approach can significantly improve progress for timely applications while maintaining task progress.
- [1] 2016. IEEE standard for information technology telecommunications and information exchange between systems local and metropolitan area networks specific requirements - Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications. IEEE Std 802.11-2016 (Revision of IEEE Std 802.11-2012) (2016), 1–3534.
DOI: Google Scholar
Cross Ref
- [2] 2020. IEEE standard for low-rate wireless networks. IEEE Std 802.15.4-2020 (Revision of IEEE Std 802.15.4-2015) (2020), 1–800.
DOI: Google ScholarCross Ref - [3] . 2014. Hibernus: Sustaining computation during intermittent supply for energy-harvesting systems. IEEE Embedded Systems Letters 7, 1 (2014), 15–18.Google ScholarDigital Library
- [4] . 2021. A theorem on power superposition in resistive networks. IEEE Transactions on Circuits and Systems II: Express Briefs 68, 7 (2021), 2362–2363.
DOI: Google ScholarCross Ref - [5] Bluetooth SIG. 2019. Bluetooth Core Specification v5.2.Google Scholar
- [6] . 2019. Multiversion concurrency control on intermittent systems. In ICCAD. 1–8.Google Scholar
- [7] . 2016. Value-based task scheduling for nonvolatile processor-based embedded devices. In 2016 IEEE Real-Time Systems Symposium (RTSS). IEEE, 247–256.Google ScholarCross Ref
- [8] . 2020. Enabling failure-resilient intermittent systems without runtime checkpointing. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2020).Google ScholarCross Ref
- [9] . 2021. Heterogeneity-aware multicore synchronization for intermittent systems. ACM Trans. Embed. Comput. Syst. 20, 5s, Article
61 (Sep. 2021), 22 pages.DOI: Google ScholarDigital Library - [10] . 2019. Scheduling and power management in energy harvesting computing systems with real-time constraints. Journal of Systems Architecture 98 (2019), 243–248.Google ScholarDigital Library
- [11] . 2020. Improving the forward progress of transient systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2020).Google Scholar
- [12] . 2022. Optimal energy-aware task scheduling for batteryless IoT devices. IEEE Transactions on Emerging Topics in Computing 10, 3 (2022), 1374–1387.
DOI: Google ScholarCross Ref - [13] . 2018. A practical study on Bluetooth low energy (BLE) throughput. In 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE, 768–771.Google ScholarCross Ref
- [14] . 2022. ETAP: Energy-aware timing analysis of intermittent programs. ACM Trans. Embed. Comput. Syst. (
Sep. 2022).DOI: Google ScholarDigital Library - [15] . 2023. Game-combined multi-agent DRL for tasks offloading in wireless powered MEC networks. IEEE Transactions on Vehicular Technology (2023), 1–14.
DOI: Google ScholarCross Ref - [16] . 2015. Bluetooth low energy for data streaming: Application-level analysis and recommendation. In 2015 6th International Workshop on Advances in Sensors and Interfaces (IWASI). IEEE, 216–221.Google ScholarCross Ref
- [17] . 2016. NVPsim: A simulator for architecture explorations of nonvolatile processors. In 2016 21st Asia and South Pacific Design Automation Conference (ASP-DAC). 147–152.
DOI: Google ScholarDigital Library - [18] . 2015. Modular performance analysis of energy-harvesting real-time networked systems. In 2015 IEEE Real-Time Systems Symposium. IEEE, 65–74.Google ScholarDigital Library
- [19] . 2022. EASTA: Energy-aware scheduling for timely applications on intermittent systems. In Proceedings of the Conference on Research in Adaptive and Convergent Systems (RACS ’22). Association for Computing Machinery, New York, NY, USA, 9–14.
DOI: Google ScholarDigital Library - [20] . 2018. Vibration and thermal energy harvesting system for automobiles with impedance matching and wake-up. In 2018 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 1–5.Google Scholar
- [21] . 2020. Scheduling computational and energy harvesting tasks in deadline-aware intermittent systems. In 2020 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS). IEEE, 95–109.Google ScholarCross Ref
- [22] . 2015. Electric Circuits (10th ed.).Google Scholar
- [23] . 2018. HomeRun: HW/SW co-design for program atomicity on self-powered intermittent systems. In Proceedings of the International Symposium on Low Power Electronics and Design. 1–6.Google ScholarDigital Library
- [24] . 2022. More is less: Model augmentation for intermittent deep inference. ACM Trans. Embed. Comput. Syst. 21, 5, Article
49 (Oct. 2022), 26 pages.DOI: Google ScholarDigital Library - [25] . 2021. Real-time task scheduling on intermittently-powered batteryless devices. IEEE Internet of Things Journal (2021).Google ScholarCross Ref
- [26] . 2020. Energy scheduling for task execution on intermittently-powered devices. ACM SIGBED Review 17, 1 (2020), 36–41.
DOI: Google ScholarDigital Library - [27] . 2015. Adaptive online power-management for Bluetooth low energy. In 2015 IEEE Conference on Computer Communications (INFOCOM). IEEE, 2695–2703.Google ScholarCross Ref
- [28] . 2018. Sensor/antenna interface IC for implantable biomedical monitoring system. IEEE Transactions on Microwave Theory and Techniques 66, 3 (2018), 1660–1667.
DOI: Google ScholarCross Ref - [29] . 1973. Scheduling algorithms for multiprogramming in a hard-real-time environment. Journal of the ACM (JACM) 20, 1 (1973), 46–61.Google ScholarDigital Library
- [30] . 2015. Ambient energy harvesting nonvolatile processors: from circuit to system. In Proceedings of the 52nd Annual Design Automation Conference. 1–6.Google ScholarDigital Library
- [31] . 2017. Intermittent computing: Challenges and opportunities. In 2nd Summit on Advances in Programming Languages (SNAPL 2017). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.Google Scholar
- [32] . 2015. Nonvolatile processor architecture exploration for energy-harvesting applications. IEEE Micro 35, 5 (2015), 32–40.Google ScholarDigital Library
- [33] . 2016. Nonvolatile processor architectures: Efficient, reliable progress with unstable power. IEEE Micro 36, 3 (2016), 72–83.Google ScholarCross Ref
- [34] . 2015. Architecture exploration for ambient energy harvesting nonvolatile processors. In 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA). IEEE, 526–537.Google ScholarCross Ref
- [35] . 2019. Alpaca: Intermittent execution without checkpoints. arXiv preprint arXiv:1909.06951 (2019).Google Scholar
- [36] . 2018. Adaptive dynamic checkpointing for safe efficient intermittent computing. In 13th \(\lbrace\)USENIX\(\rbrace\) Symposium on Operating Systems Design and Implementation (\(\lbrace\)OSDI\(\rbrace\) 18). 129–144.Google Scholar
- [37] . 2020. Adaptive low-overhead scheduling for periodic and reactive intermittent execution. In Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2020). Association for Computing Machinery, New York, NY, USA, 1005–1021.
DOI: Google ScholarDigital Library - [38] . 2020. Dynamic task-based intermittent execution for energy-harvesting devices. ACM Transactions on Sensor Networks 16, 1 (2020).
DOI: Google ScholarDigital Library - [39] . 2022. Exploiting the solar energy surplus for edge computing. IEEE Transactions on Sustainable Computing 7, 1 (2022), 135–143.
DOI: Google ScholarCross Ref - [40] . 2021. Intermittent-aware neural architecture search. ACM Trans. Embed. Comput. Syst. 20, 5s, Article
64 (Sep. 2021), 27 pages.DOI: Google ScholarDigital Library - [41] . 2007. Real-time scheduling for energy harvesting sensor nodes. Real-Time Systems 37, 3 (2007), 233–260.Google ScholarDigital Library
- [42] . 2019. Modeling and optimization for self-powered non-volatile IoT edge devices with ultra-low harvesting power. ACM Transactions on Cyber-Physical Systems 3, 3 (2019), 1–26.Google ScholarDigital Library
- [43] . 2017. A lightweight progress maximization scheduler for non-volatile processor under unstable energy harvesting. SIGPLAN Not. 52, 5 (
Jun 2017), 101–110.DOI: Google ScholarDigital Library - [44] . 2015. Real-time water level monitoring using low-power wireless sensor network. In Embedded World Conference.Google Scholar
- [45] . 2011. Mementos: System support for long-running computation on RFID-scale devices. In Proceedings of the 16th International Conference on Architectural Support for Programming Languages and Operating Systems. 159–170.Google ScholarDigital Library
- [46] . 2020. Energy-aware sensing on battery-less LoRaWAN devices with energy harvesting. Electronics 9, 6 (2020), 904.Google ScholarCross Ref
- [47] TI. 2018. Developing a Bluetooth Low Energy Application, BLE5-Stack User’s Guide. (2018).Google Scholar
- [48] . 2022. Cooperative communication between two transiently powered sensor nodes by reinforcement learning. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 41, 1 (2022), 76–90.
DOI: Google ScholarDigital Library - [49] . 2022. Immortal threads: Multithreaded event-driven intermittent computing on ultra-low-power microcontrollers. In 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22). USENIX Association, Carlsbad, CA, 339–355. https://www.usenix.org/conference/osdi22/presentation/yildizGoogle Scholar
- [50] . 2018. InK: Reactive kernel for tiny batteryless sensors. SenSys 2018 - Proceedings of the 16th Conference on Embedded Networked Sensor Systems (2018), 41–53.
DOI: Google ScholarDigital Library - [51] . 2014. Intra-task scheduling for storage-less and converter-less solar-powered nonvolatile sensor nodes. In 2014 IEEE 32nd International Conference on Computer Design (ICCD). IEEE, 348–354.Google ScholarCross Ref
- [52] . 2018. Energy-delay tradeoff for dynamic offloading in mobile-edge computing system with energy harvesting devices. IEEE Transactions on Industrial Informatics 14, 10 (2018), 4642–4655.
DOI: Google ScholarCross Ref - [53] . 2020. Toward an intelligent edge: Wireless communication meets machine learning. IEEE Communications Magazine 58, 1 (2020), 19–25.
DOI: Google ScholarDigital Library
Index Terms
- Energy-Efficient Communications for Improving Timely Progress of Intermittent-Powered BLE Devices
Recommendations
EASTA: energy-aware scheduling for timely applications on intermittent systems
RACS '22: Proceedings of the Conference on Research in Adaptive and Convergent SystemsBattery-less devices offer potential solutions for maintaining sustainable IoT networks. However, limited energy harvesting capacity can result in power failures that limit system quality of service. To maximize energy efficiency while meeting the ...
Energy harvesting discontinuous reception (DRX) mechanism in wireless powered cellular networks
The energy harvesting paradigm enables the design of new wireless powered cellular networks (WPCNs) for the Internet‐of‐Things (IoT). In a WPCN, if the harvested energy is larger than the consumed energy, an IoT device may utilise the surplus harvested ...
Joint Energy Management for Distributed Energy Harvesting Systems
SenSys '21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor SystemsEmploying energy harvesting to power the Internet of Things supports their long-term, self-sustainable, and maintenance-free operation. These energy harvesting systems have an energy management subsystem to orchestrate the flow of energy and optimize ...
Comments