Abstract
In order to improve the control effect of industrial robots, this paper analyzes the application of the joint optimization algorithm of wireless resources and cloud resources based on cloud edge multi-cluster containers in industrial robots, and improves the robot's network resource scheduling. Moreover, this paper analyzes the difficulties and challenges faced by industrial big data analysis, and based on the characteristics of the smart factory and the requirements of modeling, analyzes and uses the related technologies of big data analysis and processing to propose an algorithm system based on the joint optimization of wireless resources and cloud resources. In addition, when modeling the system, this paper maps the software components of the system to the execution platform, adds design factors for the implementation platform, and realizes the collaborative design and collaborative analysis of computer software and hardware. Finally, this paper designs an experiment to verify the performance of the system constructed in this paper. The research results show that the joint optimization algorithm constructed in this paper has a certain effect.
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References
Abd-Elmagid MA, Pappas N, Dhillon HS (2019) On the role of age of information in the internet of things. IEEE Commun Mag 57(12):72–77
Argin OF, Bayraktaroglu ZY (2021) Consistent dynamic model identification of the Stäubli RX-160 industrial robot using convex optimization method. J Mech Sci Technol 35(5):2185–2195
Baнцoв CB, Coкoлoв BA, Xoмyтcкaя OB (2021) Comprehensive control system for industrial robots. Hayчнoe Пpибopocтpoeниe 31(1):96–106
Butun I, Österberg P, Song H (2019) Security of the internet of things: vulnerabilities, attacks, and countermeasures. IEEE Commun Surv Tutor 22(1):616–644
Jagadeeswari V, Subramaniyaswamy V, Logesh R et al (2018) A study on medical internet of things and big data in personalized healthcare system. Health Inf Sci Syst 6(1):1–20
Jeon SY, Kim ES, Park BY (2021) CNN-based hand gesture recognition method for teleoperation control of industrial robot. IEMEK J Embed Syst Appl 16(2):65–72
Ji S, Liu Z, Zhang L et al (2021) Research status and development trends of industrial robot. Int Core J Eng 7(4):373–376
La VT, Huang S, Tran TD et al (2021) Adaptive robust backstepping sliding mode control of a de-icing industrial robot manipulator using neural network with dead zone. Int J Robot Autom 36(3):154–169
Li Z, Liu Y, Liu A et al (2018) Minimizing convergecast time and energy consumption in green internet of things. IEEE Trans Emerg Top Comput 8(3):797–813
Liu H, Liu B, Lian M et al (2021) Industrial robot-based system design of thickness scanning measurement using ultrasonic. Mech Sci 12(1):479–486
Mayer M, Baeumner AJ (2019) A megatrend challenging analytical chemistry: biosensor and chemosensor concepts ready for the internet of things. Chem Rev 119(13):7996–8027
Qadri YA, Nauman A, Zikria YB et al (2020) The future of healthcare internet of things: a survey of emerging technologies. IEEE Commun Surv Tutor 22(2):1121–1167
Ray PP (2018) A survey on Internet of Things architectures. J King Saud Univ Comput Inf Sci 30(3):291–319
Rout A, Deepak B, Biswal BB et al (2021) Trajectory generation of an industrial robot with constrained kinematic and dynamic variations for improving positional accuracy. Int J Appl Metaheuristic Comput (IJAMC) 12(3):163–179
Saez M, Maturana FP, Barton K et al (2018) Real-time manufacturing machine and system performance monitoring using internet of things. IEEE Trans Autom Sci Eng 15(4):1735–1748
Siboni S, Sachidananda V, Meidan Y et al (2019) Security testbed for internet-of-things devices. IEEE Trans Reliab 68(1):23–44
Smys S, Basar A, Wang H (2020) Hybrid intrusion detection system for internet of things (IoT). J ISMAC 2(04):190–199
Wang S, Yang X, Geer J (2021) Development of EtherCAT real-time control system for robot based on simulink real-time. J Comput Methods Sci Eng 21(1):49–57
Yang Y, Zhong M, Yao H et al (2018) Internet of things for smart ports: technologies and challenges. IEEE Instrum Meas Mag 21(1):34–43
Zhang Y, Liu M (2021) Application of photoelectric sensor in control of industrial robot. J Nanoelectron Optoelectron 16(2):324–332
Zhang C, Tang Z, Li K et al (2021) A polishing robot force control system based on time series data in industrial Internet of Things. ACM Trans Internet Technol (TOIT) 21(2):1–22
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This research is funded by Guangdong Vocational College of Post and Telecom.
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Huang, Z., Wang, Q. Industrial robot control system optimized by wireless resources and cloud resources based on cloud edge multi-cluster containers. Int J Syst Assur Eng Manag 14, 538–547 (2023). https://doi.org/10.1007/s13198-021-01254-0
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DOI: https://doi.org/10.1007/s13198-021-01254-0