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Fog Computing in the Internet of Things pp 123–144Cite as

Control-as-a-Service in Cyber-Physical Energy Systems over Fog Computing

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Abstract

Cyber-Physical Energy Systems (CPES) are introduced for different levels (e.g., microgrid and home) of residential, commercial, and industrial domains. Different management methodologies are implemented using Internet-of-Things (IoT) to address their challenges. IoT has enabled the required interconnectivity for the devices in these systems. However, the management methodologies require multitude of different types of sensing and actuating devices which generate and process large sensed data. Hence, the complexity, scalability, heterogeneity, and performance of the methodologies become challenging with the growing number of these various devices. Implementing the control and management, e.g., energy management-as-a-service for these systems has been seen as a solution providing the required scalability, interactivity, and customizability of architecture. On the other hand, fog computing brings the computation (intelligence) close to the networking platform (edge) benefiting us to address interactivity, scalability, complexity, and inherent heterogeneity challenges. Proximity of the computation to the devices may improve the performance and dependability for delay-sensitive devices. Hence, fog computing has been seen as a promising platform for implementing control-as-a-service (CaaS) in the IoT and CPES. Herein, as an example, we illustrate an energy management-as-a-service implemented on a fog computing platform for a residential CPES.

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References

  1. Berkeley, Microgrids at Berkeley lab (2015) [Online]. Available: der.lbl.gov

  2. M.A. Al Faruque, RAMP: impact of rule based aggregator business model for residential microgrid of prosumers including distributed energy resources, in IEEE PES Innovative Smart Grid Technologies Conference (ISGT), pp. 1–6, 2014

    Google Scholar 

  3. K. Vatanparvar, M.A. Al Faruque, Design space exploration for the profitability of a rule-based aggregator business model within a residential microgrid. IEEE Trans. Smart Grid (TSG) 6 (3), 1167–1175 (2015)

    Google Scholar 

  4. S. Shao, M. Pipattanasomporn, S. Rahman, Challenges of PHEV penetration to the residential distribution network. IEEE Power and Energy Society General Meeting, 2009

    Book  Google Scholar 

  5. S. Shao, T. Zhang, M. Pipattanasomporn, S. Rahman, Impact of TOU rates on distribution load shapes in a smart grid with PHEV penetration, in IEEE PES Transmission and Distribution Conference and Exposition: Smart Solutions for a Changing World, 2010

    Google Scholar 

  6. M. Jafari, Optimal energy management in community micro-grids, in IEEE PES Innovative Smart Grid Technologies (ISGT), pp. 1–6, 2012

    Google Scholar 

  7. Department of Energy (DOE), Buildings energy data book (2014) buildingsdatabook.eren.doe.gov/TableView.aspx?table=1.1.3

  8. U.S. Department of Energy Information Administration, Washington, DC. Electric power monthly. http://www.eia.gov/electricity/monthly/current_year/april2014.pdf. April, 2014. [June, 2014]

  9. B. Bolin, B. Doos, R. Warrick, J. Jaeger, The Greenhouse Effect, Climatic Change, and Ecosystems, 29 (Wiley and Sons (SCOPE), New York, 1986)

    Google Scholar 

  10. M.A. Al Faruque, K. Vatanparvar, Energy management-as-a-service over fog computing platform. IEEE Internet Things J. 3 (2), 161–169 (2016)

    Article  Google Scholar 

  11. United States Environmental Protection Agency, Integrated energy policy report update (2004). Internet: http://www.energy.ca.gov/reports/CEC-100-2004-006/CEC-100-2004-006CMF.PDF [June, 2014]

  12. United States Environmental Protection Agency. Clean power plan. Internet: http://www2.epa.gov/sites/production/files/2014-06/documents/20140602ria-clean-power-plan.pdf. June, 2014, [June, 2014]

  13. California Energy Emission, Building energy efficiency program. www.energy.ca.gov/title24, 2014

  14. Department of Energy, US Department of energy strategic plan. energy.gov/sites/prod/files/2011_DOE_Strategic_Plan_.pdf, 2014

  15. S. Teleke, M.E. Baran, S. Bhattacharya, A.Q. Huang, Rule-based control of battery energy storage for dispatching intermittent renewable sources. IEEE Trans. Sustainable Energy 1 (3), 117–124 (2010)

    Article  Google Scholar 

  16. P. Siano, Demand response and smart grids’ A survey. Renew. Sust. Energ. Rev. 30, 461–478 (2014)

    Article  Google Scholar 

  17. J. Aghaei, M.-I. Alizadeh, Demand response in smart electricity grids equipped with renewable energy sources: a review. Renew. Sust. Energ. Rev. 18, 64–72 (2013)

    Article  Google Scholar 

  18. M.A. Al Faruque, L. Dalloro, S. Zhou, H. Ludwig, G. Lo, Managing residential-level EV charging using network-as-automation platform (NAP) technology, pp. 1–6, 2012

    Google Scholar 

  19. M. Pipattanasomporn, M. Kuzlu, S. Rahman, An algorithm for intelligent home energy management and demand response analysis. IEEE Trans. Smart Grid 3 (4), 2166–2173 (2012)

    Article  Google Scholar 

  20. M.A. Al Faruque, F. Ahourai, A model-based design of cyber-physical energy systems, in Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 97–104, 2014

    Google Scholar 

  21. DER Group at LBNL, “WebOpt”. der.lbl.gov/News/3rd-release-distributed-energy-resources-der-web-optimization-tool-webopt, 2014

  22. T.H. Morris, A.K. Srivastava et al., Engineering future cyber-physical energy systems: challenges, research needs, and roadmap, in North American Power Symposium (NAPS), pp. 1–6, 2009

    Google Scholar 

  23. S. Karnouskos, Cyber-physical systems in the SmartGrid, in IEEE International Conference on Industrial Informatics (INDIN), pp. 20–23, 2011

    Google Scholar 

  24. K. Vatanparvar, M.A. Al Faruque, Demo abstract: energy management as a service over fog computing platform, in ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), pp. 248–249, 2015

    Google Scholar 

  25. K. Vatanparvar, Q. Chau, M.A. Al Faruque, Home energy management as a service over networking platforms, in IEEE PES Conference on Innovative Smart Grid Technologies (ISGT), 2015

    Google Scholar 

  26. U.S. Department of Energy Efficiency and Renewable Energy Golden Service Center. Financial Assistant Funding Opportunity Announcement. 28 March 2013. DE-FOA-0000822: “Turn key” open source software solutions for energy management of small to medium sized buildings (2014)

    Google Scholar 

  27. F. Jammes, H. Smit, Service-oriented paradigms in industrial automation. IEEE Trans. Ind. Inf. (2005). doi:10.1109/TII.2005.844419

    Google Scholar 

  28. P. Palensky, D. Dietrich, Demand side management: demand response, intelligent energy systems, and smart loads. IEEE Trans. Ind. Inf. 7, 381–388 (2011)

    Article  Google Scholar 

  29. D. Bian, M. Kuzlu, M. Pipattanasomporn, S. Rahman, Assessment of communication technologies for a home energy management system, in IEEE PES Innovative Smart Grid Technologies Conference (ISGT), pp. 1–5, 2014

    Google Scholar 

  30. M. Rahman, M. Kuzlu, M. Pipattanasomporn, S. Rahman, Architecture of web services interface for a home energy management system, in IEEE PES Innovative Smart Grid Technologies Conference (ISGT), pp. 1–5, 2014

    Google Scholar 

  31. D.-M. Han, J.-H. Lim, Design and implementation of smart home energy management systems based on ZigBee. IEEE Trans. Consum. Electron. 56, 1417–1425 (2010)

    Article  Google Scholar 

  32. Y.-S. Son, T. Pulkkinen, K.-D. Moon, C. Kim, Home energy management system based on power line communication. IEEE Trans. Consum. Electron. 56, 1380–1386 (2010)

    Article  Google Scholar 

  33. S. Katipamula, R.M. Underhill, J.K. Goddard, D. Taasevigen, M. Piette, J. Granderson, R.E. Brown, S.M. Lanzisera, T. Kuruganti, Small-and medium-sized commercial building monitoring and controls needs: a scoping study. Technical Report, Pacific Northwest National Laboratory (PNNL), Richland, WA (2012)

    Book  Google Scholar 

  34. X. Ye, J. Huang, A framework for cloud-based smart home, in Proceedings of International Conference on Computer Science and Network Technology (ICCSNT), vol. 2, pp. 894–897, 2011

    Google Scholar 

  35. J. LaMarche, K. Cheney, S. Christian, K. Roth, Home energy management products & trends. Fraunhofer Center for Sustainable Energy Systems (2011)

    Google Scholar 

  36. C. Angulo, R. Téllez, Distributed intelligence for smart home appliances. Tendencias de la minería de datos en España. Red Española de Minería de Datos (2004)

    Google Scholar 

  37. M. Skubic, G. Alexander, M. Popescu, M. Rantz, J. Keller, A smart home application to eldercare: current status and lessons learned. Technol. Health Care 17 (3), 183–201 (2009)

    Google Scholar 

  38. S.Y. Chen, C.F. Lai, Y.M. Huang, Y.L. Jeng, Intelligent home-appliance recognition over IoT cloud network, in 9th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 639–643, 2013

    Google Scholar 

  39. F. Bonomi, R. Milito, J. Zhu, S. Addepalli, Fog computing and its role in the internet of things, in Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, pp. 13–16, 2012

    Google Scholar 

  40. A.-M. Rahmani, N.K. Thanigaivelan, T.N. Gia, J. Granados, B. Negash, P. Liljeberg, H. Tenhunen, Smart e-health gateway: bringing intelligence to internet-of-things based ubiquitous healthcare systems, in IEEE Consumer Communications and Networking Conference (CCNC), pp. 826–834, 2015

    Google Scholar 

  41. Z. Sheng, S. Yang, Y. Yu, A. Vasilakos, J. McCann, K. Leung, A survey on the IETF protocol suite for the internet of things: standards, challenges, and opportunities. IEEE Wirel. Commun. 20, 91–98 (2013)

    Article  Google Scholar 

  42. Z. Yan, P. Zhang, A.V. Vasilakos, A survey on trust management for Internet of Things. J. Netw. Comput. Appl. 42, 120–134 (2014)

    Article  Google Scholar 

  43. Q. Jing, A.V. Vasilakos, J. Wan, J. Lu, D. Qiu, Security of the Internet of Things: perspectives and challenges. Wirel. Netw. 20, 2481–2501 (2014)

    Article  Google Scholar 

  44. A. Zaslavsky, C. Perera, D. Georgakopoulos, Sensing as a service and big data, arXiv preprint arXiv:1301.0159 (2013)

    Google Scholar 

  45. L. Wang, F. Zhang, J. A. Aroca, A. V. Vasilakos, K. Zheng, C. Hou, D. Li, Z. Liu, GreenDCN: a general framework for achieving energy efficiency in data center networks. IEEE J. Sel. Areas Commun. 32, 4–15 (2014)

    Article  Google Scholar 

  46. S. Patidar, D. Rane, P. Jain, A survey paper on cloud computing, in Proceedings of 2nd International Conference on Advanced Computing and Communication Technologies (ACCT), pp. 394–398, 2011

    Google Scholar 

  47. Q. Duan, Y. Yan, A.V. Vasilakos, A survey on service-oriented network virtualization toward convergence of networking and cloud computing. IEEE Trans. Netw. Serv. Manage. 9, 373–392 (2012)

    Article  Google Scholar 

  48. M.R. Rahimi, N. Venkatasubramanian, A.V. Vasilakos, MuSIC: mobility-aware optimal service allocation in mobile cloud computing, in IEEE International Conference on Cloud Computing, CLOUD, pp. 75–82, 2013

    Google Scholar 

  49. G. Fortino, G. Di Fatta, M. Pathan, A.V. Vasilakos, Cloud-assisted body area networks: state-of-the-art and future challenges. Wirel. Netw. 20, 1925–1938 (2014)

    Article  Google Scholar 

  50. L. Wei, H. Zhu, Z. Cao, X. Dong, W. Jia, Y. Chen, A.V. Vasilakos, Security and privacy for storage and computation in cloud computing. Inf. Sci. 258, 371–386 (2014)

    Article  Google Scholar 

  51. Q.Z. Sheng, X. Qiao, A.V. Vasilakos, C. Szabo, S. Bourne, X. Xu, Web services composition: a decade’s overview. Inf. Sci. 280, 218–238 (2014)

    Article  Google Scholar 

  52. A. Copie, T.-F. Fortis, V.I. Munteanu, Benchmarking cloud databases for the requirements of the internet of things, in Information Technology Interfaces (ITI), pp. 77–82, 2013

    Google Scholar 

  53. F. Xu, F. Liu, H. Jin, A.V. Vasilakos, Managing performance overhead of virtual machines in cloud computing: a survey, state of the art, and future directions. Proc. IEEE 102, 11–31 (2014)

    Article  Google Scholar 

  54. L. Wang, F. Zhang, A.V. Vasilakos, C. Hou, Z. Liu, Joint virtual machine assignment and traffic engineering for green data center networks. ACM SIGMETRICS Perform. Eval. Rev. 41, 107–112 (2014)

    Article  Google Scholar 

  55. M.A. Al Faruque, L. Dalloro, S. Zhou, H. Ludwig, G. Lo, Managing residential-level EV charging using network-as-automation platform (NAP) technology, in IEEE International Electric Vehicle Conference (IEVC), 2012

    Google Scholar 

  56. M.A. Al Faruque, A. Canedo, Intelligent and collaborative embedded computing in automation engineering, in Proceedings of the Conference on Design, Automation and Test in Europe, pp. 344–345, 2012

    Google Scholar 

  57. P. Baronti, P. Pillai, V.W. Chook, S. Chessa, A. Gotta, Y.F. Hu, Wireless sensor networks: a survey on the state of the art and the 802.15.4 and ZigBee standards. Comput. Commun. 30, 1655–1695 (2007)

    Google Scholar 

  58. DD-WRT. Open source firmware for routers (2014). dd-wrt.com/site/index

  59. P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, D. Culler, TinyOS: an operating system for sensor networks, in Ambient Intelligence (Springer, Berlin, 2005), pp. 115–148

    Google Scholar 

  60. TinyOS Open source operating system for low-power wireless devices. github.com/tinyos. 2014

  61. Web services for devices “(WS4D)”. ws4d.e-technik.uni-rostock.de. 2014

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of California, Irvine, CA, 92697, USA

    Korosh Vatanparvar & Mohammad Abdullah Al Faruque

Authors
  1. Korosh Vatanparvar
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  2. Mohammad Abdullah Al Faruque
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Correspondence to Korosh Vatanparvar .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of California, Irvine, California, USA

    Amir M. Rahmani

  2. Department of Future Technologies, University of Turku, Turku, Finland

    Pasi Liljeberg

  3. Thinnect, Inc., Sunnyvale, California, USA

    Jürgo-Sören Preden

  4. Institute of Computer Technology, TU Wien, Vienna, Austria

    Axel Jantsch

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Vatanparvar, K., Al Faruque, M.A. (2018). Control-as-a-Service in Cyber-Physical Energy Systems over Fog Computing. In: Rahmani, A., Liljeberg, P., Preden, JS., Jantsch, A. (eds) Fog Computing in the Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-319-57639-8_7

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  • DOI: https://doi.org/10.1007/978-3-319-57639-8_7

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