Blocking Delay Effects on Microcontroller Speed and Responsiveness in Industrial IoT Devices: A Systematic Review
DOI:
https://doi.org/10.37802/joti.v8i1.1347Keywords:
Blocking Delay, Microcontroller Speed, Microcontroller Responsiveness, IoT Devices, Industrial AutomationAbstract
This review synthesizes research on the impact of blocking delay on microcontroller speed and responsiveness in IoT devices for industrial automation. It evaluates blocking delay effects on microcontroller performance. The review benchmarks scheduling and edge computing techniques, identifies mitigation strategies, compares case study outcomes, and analyzes architectural and software factors influencing blocking delay. A systematic analysis of experimental, simulation, and co-design studies was conducted. The analysis focused on real-time scheduling, interrupt handling, network-induced latency, and edge computing integration. Key findings reveal that advanced scheduling algorithms and interrupt nesting significantly reduce blocking delays and improve task responsiveness. Edge computing and hardware optimizations also minimize network-induced latency and enhance local processing capabilities. Multiple sources of blocking delay, including resource contention and network overload, are mitigated through adaptive scheduling and hardware-assisted mechanisms. Real-world case studies confirm substantial latency reductions and improved control performance in industrial IoT contexts. These findings underscore the interplay of software and hardware factors in shaping microcontroller responsiveness. The review highlights the necessity for scalable, integrated solutions that address dynamic industrial environments. It informs the design of more responsive and efficient microcontroller-based IoT systems for industrial automation.
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R. Danicki, M. Haug, I. Behnke, L. Mädje, and L. Thamsen, “Detecting and Mitigating Network Packet Overloads on Real-Time Devices in IoT Systems,” in EdgeSys 2021 - Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking, Part of EuroSys 2021, in EdgeSys ’21. New York, NY, USA: Association for Computing Machinery, 2021, pp. 25–30. doi: 10.1145/3434770.3459733.
J. F. Wan, D. Li, Y. Q. Tu, and C. H. Zhang, “Performance analysis model for real-time Ethernet-based computer numerical control system,” J. Cent. South Univ. Technol. (English Ed., vol. 18, no. 5, pp. 1545–1553, 2011, doi: 10.1007/s11771-011-0871-7.
K. K. P. Brahmaji, “Edge Computing and Analytics for IoT Devices: Enhancing Real-Time Decision Making in Smart Environments,” Int. J. Multidiscip. Res., vol. 6, no. 5, 2024, doi: 10.36948/ijfmr.2024.v06i05.29826.
K. Röbert, H. Bornholdt, M. Fischer, and J. Edinger, “Latency-Aware Scheduling for Real-Time Application Support in Edge Computing,” in EdgeSys 2023 - Proceedings of the 6th International Workshop on Edge Systems, Analytics and Networking, Part of EuroSys 2023, in EdgeSys ’23. New York, NY, USA: Association for Computing Machinery, 2023, pp. 13–18. doi: 10.1145/3578354.3592866.
D. Oliveira, W. Chen, S. Pinto, and R. Mancuso, “Shared Resource Contention in MCUs: A Reality Check and the Quest for Timeliness,” in Leibniz International Proceedings in Informatics, LIPIcs, R. Pellizzoni, Ed., in Leibniz International Proceedings in Informatics (LIPIcs), vol. 298. Dagstuhl, Germany: Schloss Dagstuhl -- Leibniz-Zentrum für Informatik, 2024, pp. 5:1--5:25. doi: 10.4230/LIPIcs.ECRTS.2024.5.
M. Kim and D. Park, “Implementation of an SMP-based RTOS for Optimized Multicore Utilization on TriCore Architecture,” in 2025 International Technical Conference on Circuits/Systems, Computers, and Communications, ITC-CSCC 2025, 2025, pp. 1–6. doi: 10.1109/ITC-CSCC66376.2025.11137733.
P. Lindgren, P. Dzialo, H. Lunnikivi, and J. Ericsson, “ENEST - Efficient Interrupt Nesting for RISC-V based CPUs,” in 2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference, ONCON 2023, 2023, pp. 1–7. doi: 10.1109/ONCON60463.2023.10431132.
A. Nurmi, A. Kalache, and T. D. Hamalainen, “Hardware Solutions for Eliminating Context Switching Latency in Processor-Based Hard Real-Time Systems,” in 2024 IEEE Nordic Circuits and Systems Conference, NORCAS 2024 - Proceedings, 2024, pp. 1–6. doi: 10.1109/NorCAS64408.2024.10752471.
A. Saxena, R. Khalid, K. A. Jabbar, and L. H. A. Fezaa, “Enhancing Efficiency and Performance of Microcontrollers Through Advanced Optimization Techniques,” in Proceedings - International Conference on Technological Advancements in Computational Sciences, ICTACS 2023, 2023, pp. 1188–1192. doi: 10.1109/ICTACS59847.2023.10390521.
C. Li, T. Li, J. Li, W. Fu, and B. Wang, “DRA: Ultra-Low Latency Network I/O for TSN Embedded End-Systems,” in IEEE International Workshop on Quality of Service, IWQoS, 2023, pp. 1–10. doi: 10.1109/IWQoS57198.2023.10188749.
T. Springer and P. Zhao, “Design and Implementation of a Real-Time Rate-Based Task Scheduler for Real-Time Operating Systems: A Case Study with VxWorks,” in CS & IT Conference Proceedings, 2024, pp. 01–20. doi: 10.5121/csit.2024.142301.
M. H. Bin Kamilin, M. A. Bin Ahmadon, and S. Yamaguchi, “Multi-task learning-based task scheduling switcher for a resource-constrained iot system†,” Inf., vol. 12, no. 4, 2021, doi: 10.3390/info12040150.
S. A. Khajeh, M. Saberikamarposhti, and A. M. Rahmani, “Real-Time Scheduling in IoT Applications: A Systematic Review,” Sensors, vol. 23, no. 1, 2023, doi: 10.3390/s23010232.
P. Balbastre, I. Ripoll, and A. Crespo, “Control tasks delay reduction under static and dynamic scheduling policies,” in Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000, 2000, pp. 522–526. doi: 10.1109/RTCSA.2000.896437.
Y. Wu, E. Bini, and G. Buttazzo, “A framework for designing embedded real-time controllers,” in Proceedings - 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2008, 2008, pp. 303–311. doi: 10.1109/RTCSA.2008.22.
S. Samii, A. Cervin, P. Eles, and Z. Peng, “Integrated scheduling and synthesis of control applications on distributed embedded systems,” in Proceedings -Design, Automation and Test in Europe, DATE, 2009, pp. 57–62. doi: 10.1109/date.2009.5090633.
Y. Wang, X. Zhao, T. Chong, and X. Liu, “Embedded Microprocessor Extension Design and Optimization for Real-Time Edge Computing,” Wirel. Commun. Mob. Comput., vol. 2022, no. 1, p. 5705184, 2022, doi: 10.1155/2022/5705184.
F. Bender, J. J. Brune, N. L. Keutel, I. Behnke, and L. Thamsen, “Pieres: A playground for network interrupt experiments on real-time embedded systems in the IoT,” in ICPE 2021 - Companion of the ACM/SPEC International Conference on Performance Engineering, in ICPE ’21. New York, NY, USA: Association for Computing Machinery, 2021, pp. 81–84. doi: 10.1145/3447545.3451189.
K. Brun-Laguna, P. Minet, and Y. Tanaka, “Optimized scheduling for time-critical industrial IoT,” in Proceedings - IEEE Global Communications Conference, GLOBECOM, 2019, pp. 1–6. doi: 10.1109/GLOBECOM38437.2019.9014218.
K. Li, P. Zhu, Y. Wang, J. Wang, and X. You, “Scheduling of Time-Triggered Traffic for Deterministic URLLC in Industrial Automation,” IEEE Internet Things J., vol. 11, no. 16, pp. 26552–26567, 2024, doi: 10.1109/JIOT.2024.3422400.
Y. H. Song, Suk-Lee, H. J. Kim, and K. C. Lee, “Computational delay and real-time performance of industrial network,” in ICCAS 2015 - 2015 15th International Conference on Control, Automation and Systems, Proceedings, 2015, pp. 735–737. doi: 10.1109/ICCAS.2015.7364716.
H. Youness, M. Moness, and M. Khaled, “MPSoCs and multicore microcontrollers for embedded PID control: A detailed study,” IEEE Trans. Ind. Informatics, vol. 10, no. 4, pp. 2122–2134, 2014, doi: 10.1109/TII.2014.2355036.
E. Marevac, E. Kadušić, N. Živić, N. Buzađija, and S. Lemeš, “Framework Design for the Dynamic Reconfiguration of IoT-Enabled Embedded Systems and ‘On-the-Fly’ Code Execution,” Futur. Internet, vol. 17, no. 1, 2025, doi: 10.3390/fi17010023.
M. Geier, T. Burghart, M. Hackl, and S. Chakraborty, “In situ latency monitoring for heterogeneous real-time systems,” in Proceedings - 32nd International Conference on VLSI Design, VLSID 2019 - Held concurrently with 18th International Conference on Embedded Systems, ES 2019, 2019, pp. 275–280. doi: 10.1109/VLSID.2019.00066.
C. A. Tanase, “Reducing Energy Consumption in Microcontroller-based Systems with Multipipeline Architecture,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 12, pp. 16–24, 2020, doi: 10.14569/IJACSA.2020.0111203.
Q. Yang, “Embedded System Based on Task Interval Data Interaction Model,” Int. J. High Speed Electron. Syst., vol. 34, no. 2, 2025, doi: 10.1142/S0129156424400895.
P. Vasu, H. Chouhan, and N. Naik, “Design and implementation of optimal soft-programmable logic controller on multicore processor,” in 2017 International Conference on Microelectronic Devices, Circuits and Systems, ICMDCS 2017, 2017, pp. 1–4. doi: 10.1109/ICMDCS.2017.8211691.
Y. Hu et al., “Deterministic Scheduling and Network Structure Optimization for Time-Critical Computing Tasks in Industrial IoT,” 2025. doi: 10.1109/ton.2025.3587916.
S. Malik, S. Ahmad, I. Ullah, D. H. Park, and D. H. Kim, “An adaptive emergency first intelligent scheduling algorithm for effcient task management and scheduling in hybrid of hard real-time and soft real-time embedded IoT systems,” Sustain., vol. 11, no. 8, 2019, doi: 10.3390/su11082192.
H. Choi, H. Kim, and Q. Zhu, “Toward Practical Weakly Hard Real-Time Systems: A Job-Class-Level Scheduling Approach,” IEEE Internet Things J., vol. 8, no. 8, pp. 6692–6708, 2021, doi: 10.1109/JIOT.2021.3058215.
B. Ness and G. Karsai, “High precision automatic scheduling of periodic task sets for microcontrollers,” in Proceedings of the 46th Annual Southeast Regional Conference on XX, ACM-SE 46, in ACMSE ’08. New York, NY, USA: Association for Computing Machinery, 2008, pp. 1–6. doi: 10.1145/1593105.1593107.
C. Lozoya, M. Velasco, and P. Martí, “The one-shot task model for robust real-time embedded control systems,” IEEE Trans. Ind. Informatics, vol. 4, no. 3, pp. 164–174, 2008, doi: 10.1109/TII.2008.2002702.
P. Fara, G. Serra, and F. Aromolo, “Bounded transmission latency in real-time edge computing: a scheduling analysis,” in Proceedings - 2023 26th Euromicro Conference on Digital System Design, DSD 2023, 2023, pp. 618–625. doi: 10.1109/DSD60849.2023.00090.
D. Ko, J. Jeon, and S. Kang, “A Research on Low Latency Motion Control System using Real-time Scheduling in Edge Server,” in International Conference on Information Networking, 2023, pp. 537–540. doi: 10.1109/ICOIN56518.2023.10048964.
F. C. Braescu, L. Ferariu, and C. Lazar, “OSEK-based multiple controllers with schedule feasibility self-testing,” in SPEEDAM 2010 - International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 2010, pp. 1237–1242. doi: 10.1109/SPEEDAM.2010.5542060.
L. Yang, X. Wang, Z. Liu, Y. Liu, and L. Fan, “Real-time processing and optimization strategies for IoT data streams,” Appl. Math. Nonlinear Sci., vol. 9, no. 1, 2024, doi: 10.2478/amns-2024-2978.
Z. Zhang, W. Sun, and Y. Yu, “Research on Intelligent Scheduling Mechanism in Edge Network for Industrial Internet of Things,” Secur. Commun. Networks, vol. 2022, no. 1, p. 5358873, 2022, doi: 10.1155/2022/5358873.
K. Takado, T. Yokoyama, and M. Yoo, “A Real-Time Operating System for Physical and Logical Time-Triggered Distributed Computing,” in ACM International Conference Proceeding Series, in APIT ’24. New York, NY, USA: Association for Computing Machinery, 2024, pp. 78–85. doi: 10.1145/3651623.3651635.
J. Wang and D. Huang, “Effective Task Scheduling for Intelligent Manufacturing With Fog Computing,” in IET Conference Proceedings, 2024, pp. 118–126. doi: 10.1049/icp.2024.2720.
P. Ntumba, N. Georgantas, and V. Christophides, “Scheduling Continuous Operators for IoT edge Analytics with Time Constraints,” in Proceedings - 2022 IEEE International Conference on Smart Computing, SMARTCOMP 2022, 2022, pp. 78–85. doi: 10.1109/SMARTCOMP55677.2022.00026.
F. Liang, W. Yu, X. Liu, D. Griffith, and N. Golmie, “Toward Computing Resource Reservation Scheduling in Industrial Internet of Things,” IEEE Internet Things J., vol. 8, no. 10, pp. 8210–8222, 2021, doi: 10.1109/JIOT.2020.3044057.
P. Lindgren, J. Eriksson, M. Lindner, A. Lindner, D. Pereira, and L. M. Pinho, “Response time for IEC 61499 over Ethernet,” in Proceeding - 2015 IEEE International Conference on Industrial Informatics, INDIN 2015, IEEE, Jul. 2015, pp. 1206–1212. doi: 10.1109/INDIN.2015.7281907.
L. Orciari, D. Raggini, and A. Tilli, “Taming Edge Computing for Hard Real-Time Advanced Control of Mechatronic Systems,” IEEE Trans. Ind. Informatics, vol. 20, no. 8, pp. 9898–9906, 2024, doi: 10.1109/TII.2024.3390608.
K. G. Sundararaj and G. C. Megharaj, “IoT Enabled Smart Sensing Systems Using RISC V Based Microcontrollers and Embedded AI,” in Smart Microcontrollers and FPGA Based Architectures for Advanced Computing and Signal Processing, RADemics Research Institute, 2025, pp. 131–158. doi: 10.71443/9789349552425-05.
M. V. Manjula, “Optimizing Edge Computing for Real-Time Data Processing in IoT Networks: A Comparative Study of Lightweight Algorithms,” Int. J. Res. Appl. Sci. Eng. Technol., vol. 13, no. 8, pp. 895–899, Aug. 2025, doi: 10.22214/ijraset.2025.73662.
C. H. Chen, M. Y. Lin, and C. C. Liu, “Edge Computing Gateway of the Industrial Internet of Things Using Multiple Collaborative Microcontrollers,” IEEE Netw., vol. 32, no. 1, pp. 24–32, Jan. 2018, doi: 10.1109/MNET.2018.1700146.
P. Muralidhara and V. Janardhan, “Edge and cloud integration: Optimizing Latency and Resource Allocation for IoT Applications,” Int. J. Eng. Comput. Sci., vol. 5, no. 7, pp. 17388–17406, Jul. 2016, doi: 10.18535/ijecs/v5i7.33.
S. B. Kamatchi, V. N. Agme, S. Premkumar, K. Prasad, D. G. V, and I. Gugan, “Enhancing Microcomputer Edge Computing for Autonomous IoT Motion Control,” Int. J. Recent Innov. Trends Comput. Commun., vol. 11, no. 3, pp. 58–67, Apr. 2023, doi: 10.17762/ijritcc.v11i3.6202.
V. S. Anooja, M. Krishnakumar, S. B. Sangeetha, and W. Rajaian, “Enhancing Intelligent Connectivity Through Embedded Iot Systems for Real-Time Applications,” ICTACT J. Microelectron., vol. 11, no. 1, pp. 2058–2063, Apr. 2025, doi: 10.21917/ijme.2025.0348.
M. Walker, S. Wörtz, M. Neubauer, A. Lechler, and A. Verl, “Scheduling for the Orchestration of Distributed Real-Time Applications,” in 2025 IEEE 8th International Conference on Industrial Cyber-Physical Systems (ICPS), IEEE, May 2025, pp. 01–08. doi: 10.1109/icps65515.2025.11087855.
