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Cloud computing as a facilitator for web service composition in factory automation

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Abstract

Cloud computing is an information technology paradigm enabling companies to sell computing resources more dynamically. Software and hardware are now commodities leased on demand. Because computer systems leased from a cloud service provider, virtual machines, are typically connected to internet, they can host web services, which are frequently components of service oriented architectures (SOAs). Such architectures have recently been adopted in factory automation, as they allow systems to reach high levels of decentralization and loose-coupling. SOA-based Factory automation systems combine physical production equipment with web services that belong to the information processing (cyber) domain, and they are therefore highly cyber-physical. When some of the services are deployed on cloud resources, SOA-based factory automation systems can be classified cloud-based cyber-physical systems. Each service in such a system is typically able to perform rather simple, atomic operations, whereas achievement of complex goals requires that the services be composed to collaboratively carry out workflows. This article investigates the use of cloud resources in automatic service workflow composition. To facilitate the acquisition and utilization of cloud resources, a system of two specialized web services is proposed. The system includes a web service that dynamically deploys virtual machines to carry out planning processes, thereby exhibiting artificial intelligence. Finally, this paper demonstrates the integration of the system with a previously proposed semantic web service composition framework.

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Notes

  1. Thesis document acessible online: http://dspace.cc.tut.fi/dpub/handle/123456789/22371

  2. Available at http://escop.rd.tut.fi:3000/. Accessed March 30, 2016.

  3. Available at http://aws.amazon.com/ec2/. Accessed March 30, 2016.

  4. Available at https://azure.microsoft.com/en-us/. Accessed March 30, 2016.

  5. Available at https://cloud.google.com/compute/. Accessed March 30, 2016.

  6. Available at http://www.rackspace.com/cloud/. Accessed March 30, 2016.

  7. http://docs.aws.amazon.com/AWSEC2/latest/APIReference/Welcome.html. Accessed March 30, 2016.

  8. Available at http://projects.spring.io/spring-boot/. Accessed March 30, 2016.

  9. Available at https://linuxcontainers.org/. Accessed March 30, 2016.

  10. Available at https://www.docker.com/. Accessed March 30, 2016.

  11. Available at http://tomcat.apache.org/. Accessed March 30, 2016.

References

  • Buyya, R., Yeo, C. S., Venugopal, S., Broberg, J., & Brandic, I. (2009). Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems, 25(6), 599–616. doi:10.1016/j.future.2008.12.001.

    Article  Google Scholar 

  • Cheng, J., Liu, C., Zhou, M., Zeng, Q., & Ylä-Jääski, A. (2015). Automatic composition of semantic web services based on fuzzy predicate petri nets. IEEE Transactions on Automation Science and Engineering, 12(2), 680–689. doi:10.1109/TASE.2013.2293879.

    Article  Google Scholar 

  • Givehchi, O., Trsek, H., & Jasperneite, J. (2013). Cloud computing for industrial automation systems—A comprehensive overview. In 2013 IEEE 18th Conference on Emerging Technologies Factory Automation (ETFA) pp. 1–4. doi:10.1109/ETFA.2013.6648080.

  • Grozev, N., & Buyya, R. (2015). Performance modelling and simulation of three-tier applications in cloud and multi-cloud environments. Computer Journal, 58(1), 1–22. doi:10.1093/comjnl/bxt107.

    Article  Google Scholar 

  • Guo, Z. X., Wong, W. K., & Guo, C. (2014). A cloud-based intelligent decision-making system for order tracking and allocation in apparel manufacturing. International Journal of Production Research, 52(4), 1100–1115. doi:10.1080/00207543.2013.838650.

    Article  Google Scholar 

  • Jammes, F., & Smit, H. (2005). Service-oriented paradigms in industrial automation. IEEE Transactions on Industrial Informatics, 1(1), 62–70.

    Article  Google Scholar 

  • Jammes, F., Smit, H., Lastra, J. L. M., & Delamer, I. M. (2005). Orchestration of service-oriented manufacturing processes. In 10th IEEE Conference on Emerging Technologies and Factory Automation, ETFA 2005, vol. 1 (pp. 617–624).

  • Jeong, H.-Y., Jeong, Y.-S., & Park, J. H. (2014). G-Cloud Monitor: A cloud monitoring system for factory automation for sustainable green computing. Sustainability (Switzerland), 6(12), 8510–8521. doi:10.3390/su6128510.

    Article  Google Scholar 

  • Jeong, H.-Y., Park, J. H., & Lee, J. D. (2014). The cloud storage model for manufacturing system in global factory automation. In (pp. 895–999). doi:10.1109/WAINA.2014.138.

  • Kehoe, B., Warrier, D., Patil, S., & Goldberg, K. (2015). Cloud-based grasp analysis and planning for toleranced parts using parallelized monte carlo sampling. IEEE Transactions on Automation Science and Engineering, 12(2), 455–470. doi:10.1109/TASE.2014.2356451.

    Article  Google Scholar 

  • Kushida, Kenji E., Murray, Jonathan, & Zysman, John. (2015). Cloud computing: From scarcity to abundance. Journal of Industry, Competition and Trade, 15(1), 5–19. doi:10.1007/s10842-014-0188-y.

    Article  Google Scholar 

  • Lam, M.-L., & Lam, K.-Y. (2014). Path planning as a service PPaaS: Cloud-based robotic path planning. In 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO) (pp. 1839–1844). doi:10.1109/ROBIO.2014.7090603.

  • Lee, E. A. (2008). Cyber physical systems: Design challenges. UCB/EECS-2008-8. EECS Department, University of California, Berkeley. http://www.eecs.berkeley.edu/Pubs/TechRpts/2008/EECS-2008-8.html.

  • Lopez Orozco, O. J., Martinez Lastra, J. L., Perez Garcia, J. A., & Cavia Soto, M. A. (2008). Messaging performance of FIPA interaction protocols in networked embedded controllers. EURASIP Journal on Embedded Systems. 2008, Article ID 470856, 7 p., doi:10.1155/2008/470856.

  • Martinez Lastra, J. L., & Delamer, I. M. (2006). Semantic web services in factory automation: Fundamental insights and research roadmap. IEEE Transactions on Industrial Informatics, 2(1), 1–11.

    Article  Google Scholar 

  • McDermott, D. (1998). PDDL—The planning domain definition language Version 1.2. Technical Report. Yale Center for Computational Vision and Control.

  • Mohanarajah, G., Hunziker, D., D’Andrea, R., & Waibel, M. (2015). Rapyuta: A cloud robotics platform. IEEE Transactions on Automation Science and Engineering, 12(2), 481–493. doi:10.1109/TASE.2014.2329556.

    Article  Google Scholar 

  • Puttonen, J., Lobov, A., & Martinez Lastra, J. L. (2013). Semantics-based composition of factory automation processes encapsulated by web services. IEEE Transactions on Industrial Informatics, 9(4), 2349–2359.

    Article  Google Scholar 

  • Puttonen, J. (2014). A semantically enhanced approach for orchestration of web services in factory automation systems. Dr. Tech. thesis, Tampere, Finland: Tampere University of Technology. http://dspace.cc.tut.fi/dpub/handle/123456789/22371.

  • Puttonen, J., Lobov, A., Soto, M. A. C., & Lastra, J. L. M. (2015). Planning-based semantic web service composition in factory automation. Advanced Engineering Informatics, Collective Intelligence Modeling, Analysis, and Synthesis for Innovative Engineering Decision MakingSpecial Issue of the 1st International Conference on Civil and Building Engineering Informatics, 29 (4): 1041–1054. doi:10.1016/j.aei.2015.08.002.

  • Puttonen, Juha, Lobov, Andrei, & Lastra, José L. Martinez. (2014). On the updating of domain OWL models at runtime in factory automation systems. International Journal of Web Services Research, 11(2), 46–66. doi:10.4018/ijwsr.2014040103.

    Article  Google Scholar 

  • Puttonen, J., Lobov, A., & Lastra, J. L. M. (2011). An approach to service deployment to the service cloud. In ICONS 2011: The Sixth International Conference on Systems (pp. 122–127). The Netherlands Antilles: St. Maarten.

  • Reddy, Y. B. (2014). Cloud-based cyber physical systems: Design challenges and security needs. In 2014 10th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN) (pp. 315–322). doi:10.1109/MSN.2014.50.

  • Wang, L., Törngren, M., & Onori, M. (2015). Current status and advancement of cyber-physical systems in manufacturing. Journal of Manufacturing Systems, 37(Part 2), 517–527. doi:10.1016/j.jmsy.2015.04.008.

    Article  Google Scholar 

  • Ward, Jonathan, & Barker, Adam. (2014). Observing the clouds: A survey and taxonomy of cloud monitoring. Journal of Cloud Computing, 3(1), 1–30.

    Article  Google Scholar 

  • Wu, Dazhong, Rosen, David W., & Schaefer, Dirk. (2015). Scalability planning for cloud-based manufacturing systems. Journal of Manufacturing Science and Engineering, 137(4), 040911–040911. doi:10.1115/1.4030266.

    Article  Google Scholar 

  • Wu, D., Terpenny, J., Zhang, L., Gao, R., & Kurfess, T. (2016). Fog-enabled architecture for data-driven cyber-manufacturing systems. InProceedings of the ASME 2016 International Manufacturing Science and Engineering Conference (MSEC2016). Paper Number: MSEC2016-8559, Blacksburg, Virginia.

  • Yang, Xiaoying, Shi, Guohong, & Zhang, Zhiwen. (2014). Collaboration of large equipment complete service under cloud manufacturing mode. International Journal of Production Research, 52(2), 326–336. doi:10.1080/00207543.2013.825383.

    Article  Google Scholar 

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Authors and Affiliations

  1. Factory Automation Systems and Technologies: FAST-Lab., Tampere University of Technology, Tampere, Finland

    Juha Puttonen, Andrei Lobov & José L. Martinez Lastra

  2. Department of Electrical and Energy Engineering, Universidad de Cantabria, Santander, Spain

    Maria A. Cavia Soto

Authors
  1. Juha Puttonen
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  2. Andrei Lobov
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  3. Maria A. Cavia Soto
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  4. José L. Martinez Lastra
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Corresponding author

Correspondence to Andrei Lobov.

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Puttonen, J., Lobov, A., Soto, M.A.C. et al. Cloud computing as a facilitator for web service composition in factory automation. J Intell Manuf 30, 687–700 (2019). https://doi.org/10.1007/s10845-016-1277-z

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  • DOI: https://doi.org/10.1007/s10845-016-1277-z

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