Efficiency improvement of using unmanned aerial vehicles by distribution of tasks between the cores of the computing processor

Authors

DOI:

https://doi.org/10.15587/2312-8372.2017.117889

Keywords:

computing systems of unmanned aerial vehicles (UAV), 4-core processor, simulation modeling

Abstract

The object of research is the computer system of unmanned aerial vehicles (UAVs). Most modern UAVs are based on 2- or 4-core single-chip processors, between which between which the OS automated scheduler tries to evenly distribute computational tasks. One of the most problematic places in the described process is that the first core can instantly become extremely congested in the event of an urgent task from the UAV control system. Therefore, the subject of research is complex indicators of the state of the processor cores for various algorithms of task distribution proposed between the cores of a multicore single-chip processor.

In the course of the research, methods for simulating the dispatching of tasks processed by the UAV computer system based on a quad-core single-chip processor are used. The expediency of using the energy of the measuring signal from piezoelectric sensors for partial compensation of the consumed energy by the UAV computer system is investigated and justified. To evaluate the effectiveness of measures taken to increase the efficiency of the use of computer system components, the HWMonitor utility is used.

According to the research results from the developed certain optimal algorithm, which differs from the others by reserving the resources of the 1st core of a multi-core single-chip computing processor for calculations of primary importance. The use of such calculation algorithm provides an increase in flight time by 3.1 minutes and increases the range of professional tasks by 1.3 min (for UAV DJI Phantom 4).

In comparison with similar known solutions, the proposed algorithm improves the UAV stable behavior in critical applications (loss of ground control, the occurrence of obstacles, the impossibility of obtaining GPS coordinates in the areas of radio electronic warfare, etc.).

Author Biographies

Iryna Zhuravska, Petro Mohyla Black Sea National University, 10, 68 Desantnykiv str., Mykolaiv, Ukraine, 54003

PhD, Associate Professor

Department of Computer Engineering

Svitlana Borovlyova, Petro Mohyla Black Sea National University, 10, 68 Desantnykiv str., Mykolaiv, Ukraine, 54003

Senior Lecturer

Department of Software Engineering

Mykhailo Kostyria, Petro Mohyla Black Sea National University, 10, 68 Desantnykiv str., Mykolaiv, Ukraine, 54003

Department of Intelligent Information Systems

Oleksandra Koretska, Petro Mohyla Black Sea National University, 10, 68 Desantnykiv str., Mykolaiv, Ukraine, 54003

Postgraduate Student

Department of Computer Engineering

References

  1. Tencent and ZEROTECH Unveil Commercial Drone Based on Qualcomm Snapdragon Flight Platform. (2016, January 5). Qualcomm Technologies, Inc. Available at: https://www.qualcomm.com/news/releases/2016/01/05/tencent-and-zerotech-unveil-commercial-drone-based-qualcomm-snapdragon
  2. Cortex™-A9. Revision: r4p1. Technical Reference Manual. (2012). ARM. Available at: http://infocenter.arm.com/help/topic/com.arm.doc.ddi0388i/DDI0388I_cortex_a9_r4p1_trm.pdf
  3. Development of multi-threaded applications using optimization method for platforms. (2011, February 3). Intel Software Developer Zone. Available at: https://software.intel.com/ru-ru/articles/61695
  4. Task Scheduler How To... Microsoft TechNet. Available at: https://technet.microsoft.com/en-gb/library/cc766428(v=ws.11).aspx
  5. Prostaia model' planirovshchika OS. (2012, October 12). Habrahabr. Available at: https://habrahabr.ru/post/154609/
  6. Troubleshooting Task Scheduler. Microsoft TechNet. Available at: https://technet.microsoft.com/en-gb/library/cc721846(v=ws.11).aspx
  7. Tanenbaum, A. S., Bos, H. (2015). Modern Operating Systems. Ed. 4. Amsterdam, The Netherlands: Pearson Prentice-Hall, 1072.
  8. Arhitektura: gibkaia, effektivnaia. (2013). CHIP, 9, 52–53.
  9. Krainyk, Y., Perov, V., Musiyenko, M., Davydenko, Y. (2017). Hardware-oriented turbo-product codes decoder architecture. Proceedings of the 2017 IEEE 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS 2017), Bucharest, Romania, September 21–23, 2017, 1, 151–154. doi:10.1109/idaacs.2017.8095067
  10. Burlachenko, I., Zhuravska, I., Musiyenko, M. (2017). Devising a method for the active coordination of video cameras in optical navigation based on the multi-agent approach. Eastern-European Journal of Enterprise Technologies, 1 (9 (85)), 17–25. doi:10.15587/1729-4061.2017.90863
  11. Nikiforov, V. V. (2014). Basic Requirements to the SPIIRAS Transactions Paper Format Feasibility of Real-Time Applications on Multicore Processors. SPIIRAS Proceedings, 8, 255–284. doi:10.15622/sp.8.12
  12. Zhuravska, I. M., Koretska, O. O., Musiyenko, M. P., Surtel, W., Assembay, A., Kovalev, V., Tleshova, A. (2017, August 7). Self-powered information measuring wireless networks using the distribution of tasks within multicore processors. Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments, Wilga, Poland, 2017, 1–13. doi:10.1117/12.2280965
  13. Sharapov, V., Sarwar, I., Chudaeva, I., Musienko, M. (1998). The electromechanical feed-back in piezoceramic sensors and transducers. Proceedings of the IEEE Ultrasonics Symposium, Sendai, Japan, October 5–8, 1998, 1, 543–544. doi:10.1109/ultsym.1998.762208
  14. Trasvina-Moreno, C., Blasco, R., Marco, A., Casas, R., Trasvina-Castro, A. (2017). Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring. Sensors, 17 (3), 460. doi:10.3390/s17030460
  15. CPU Stability Test. (2017). BenchmarkHQ. Available at: http://www.benchmarkhq.ru/russian.html?/b.html
  16. Chakos, B. (2013). Here’s how. PCWorld, 89.
  17. Property Process.ProcessorAffinity. (2016, October). Microsoft Developer Network. Available at: https://msdn.microsoft.com/ru-ru/library/system.diagnostics.process.processoraffinity(v=vs.110).aspx
  18. Intel® Math Kernel Library – Documentation. (2017, September 13). Intel Software Developer Zone. Available at: https://software.intel.com/en-us/articles/intel-math-kernel-library-documentation
  19. Grama, А., Karypis, G., Kumar, V., Gupta, A. (2003). Introduction to Parallel Computing. Ed. 2. Boston, MA, US: Addison-Wesley, 656.
  20. Richter, J. (2012). CLR via C#. Ed. 4. Redmond, WA, US: Microsoft prePress, 813.
  21. Phantom 4 Pro: specifications. (2017). DJI. Available at: https://www.dji.com/ru/phantom-4-pro/info

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Published

2017-11-30

How to Cite

Zhuravska, I., Borovlyova, S., Kostyria, M., & Koretska, O. (2017). Efficiency improvement of using unmanned aerial vehicles by distribution of tasks between the cores of the computing processor. Technology Audit and Production Reserves, 6(2(38), 4–13. https://doi.org/10.15587/2312-8372.2017.117889

Issue

Vol. 6 No. 2(38) (2017): Information and Control Systems

Section

Information Technologies: Original Research

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Copyright (c) 2017 Iryna Zhuravska, Svitlana Borovlyova, Mykhailo Kostyria, Oleksandra Koretska

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