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2019 | OriginalPaper | Buchkapitel

A Critical Review of Edge and Fog Computing for Smart Grid Applications

verfasst von : Gilbert M. Gilbert, Shililiandumi Naiman, Honest Kimaro, Burchard Bagile

Erschienen in: Information and Communication Technologies for Development. Strengthening Southern-Driven Cooperation as a Catalyst for ICT4D

Verlag: Springer International Publishing

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Abstract

Smart grid and cloud computing architectures have been perfectly suiting each other naturally. As a result, over the years cloud computing architectures have dominated the implementations of smart grid applications to address computing needs. However, due to continuing additions of heterogeneous (sensing and actuating) devices, emergence of Internet of Things (IoT), and massive amount of data collected across the grids for analytics, have contributed to the complexity of smart grids, making cloud computing architectures no longer suitable to provide smart grid services effectively. Edge and Fog computing approaches have relieved the cloud computing architectures of problems related to network congestion, latency and locality by shift of control, intelligence and trust to the edge of the network. In this paper, a systematic literature review is used to explore the research trend of the actual implementations of edge and fog computing for smart grid applications. A total of 70 papers were reviewed from the popular digital repositories. The study has revealed that, there is significant increase in the number of smart grid applications that have exploited the use edge and fog computing approaches. The study also shows that, considerable number of the smart grid applications are related to energy optimizations and intelligent coordination of smart grid resources. There are also challenges and issues that hinder smooth adoption of edge and fog computing for smart grid applications, which include security, interoperability and programming models.

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Vorheriges Kapitel Exploring the Impacts of Intrinsic Variables on Security Compliance Efficiency Using DEA and MARS

Nächstes Kapitel Information Security Culture Assessment of Small and Medium-Sized Enterprises in Tanzania

Ekanayake, J., Liyanage, K., Wu, J., Yokoyama, A., Jenkins, N.: Smart Grid: Technology and Applications. Wiley, Hoboken (2012)CrossRef

DECC Department of Energy and Climate Change: Smarter Grids: The Opportunity. 30 (2009)

Green, R.C., Wang, L., Alam, M.: Applications and trends of high performance computing for electric power systems: Focusing on smart grid. IEEE Trans. Smart Grid. 4, 922–931 (2013)CrossRef

Naveen, P., Ing, W.K., Danquah, M.K., Sidhu, A.S., Abu-Siada, A.: Cloud computing for energy management in smart grid - an application survey. In: IOP Conference Series: Materials Science and Engineering, p. 121 (2016)

Birman, K., Ganesh, L., van Rennessee, R.: Running smart grid control software on cloud computing architectures. In: Computational Needs for the Next Generation Electric Grid, pp. 1–33 (2011)

Boccadoro, P.: Smart Grids empowerment with Edge Computing: An Overview (2018)

Garcia Lopez, P., et al.: Edge-centric computing. ACM SIGCOMM Comput. Commun. Rev. 45, 37–42 (2015)CrossRef

Chiang, M., Ha, S., Chih-Lin, I., Risso, F., Zhang, T.: Clarifying fog computing and networking: 10 questions and answers. IEEE Commun. Mag. 55, 18–20 (2017)CrossRef

Klonoff, D.C.: Fog computing and edge computing architectures for processing data from diabetes devices connected to the medical internet of things. J. Diabetes Sci. Technol. 11, 647–652 (2017)CrossRef

10.

Thien, A.T., Colomo-Placios, R.: A systematic literature review of fog computing. Nokobit 2016(24), 28–30 (2016)

11.

Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R.H., Morrow, M.J., Polakos, P.A.: A comprehensive survey on fog computing: state-of-the-art and research challenges. IEEE Commun. Surv. Tutor. 20, 416–464 (2018)CrossRef

12.

Abbas, N., Zhang, Y., Taherkordi, A., Skeie, T.: Mobile edge computing: a survey. IEEE Internet Things J. 5, 450–465 (2018)CrossRef

13.

Yu, W.: A survey on the edge computing for the internet of things. IEEE Access. 6, 6900–6919 (2017)CrossRef

14.

Muzakkir Hussain, M., Alam, M.S., Sufyan Beg, M.M.: Feasibility of fog computing in smart grid architectures. In: Krishna, C.R., Dutta, M., Kumar, R. (eds.) Proceedings of 2nd International Conference on Communication, Computing and Networking. LNNS, vol. 46, pp. 999–1010. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-1217-5_98CrossRef

15.

Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering, version 2.3 (2007)

16.

Okay, F.Y., Ozdemir, S.: A fog computing based smart grid model. In: 2016 International Symposium on Networks, Computers and Communications, ISNCC 2016, pp. 1–6 (2016)

17.

Dubey, A., Karsai, G., Pradhan, S.: Resilience at the edge in cyber-physical systems. In: 2017 2nd International Conference on Fog and Mobile Edge Computing, FMEC 2017, pp. 139–146. ACM, Austin (2017)

18.

Eisele, S., Mardari, I., Dubey, A., Karsai, G.: RIAPS: resilient information architecture platform for decentralized smart systems. In: Proceedings of 2017 IEEE 20th International Symposium on Real-Time Distributed Computing, ISORC 2017, pp. 125–132. ACM, Santa Barbara (2017)

19.

Yang, Z., Chen, N., Chen, Y., Zhou, N.: A novel PMU fog based early anomaly detection for an efficient wide area PMU network. In: 2018 IEEE 2nd International Conference on Fog and Edge Computing, ICFEC 2018 - In Conjunction with 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, IEEE/ACM CCGrid 2018, pp. 1–10. ACM, New Delhi (2018)

20.

Risteska Stojkoska, B.L., Trivodaliev, K.V.: A review of internet of things for smart home: challenges and solutions. J. Clean. Prod. 140, 1454–1464 (2017)CrossRef

21.

Jiang, R., Lu, R., Choo, K.K.R.: Achieving high performance and privacy-preserving query over encrypted multidimensional big metering data. Future Gener. Comput. Syst. 78, 392–401 (2018)CrossRef

22.

Xiao, J., Kou, P.: A hierarchical distributed fault diagnosis system for hydropower plant based on fog computing. In: Proceedings of the 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2017, pp. 1138–1142 (2018)

23.

Tehreem, K., Javaid, N., Bano, H., Ansar, K., Waheed, M., Butt, H.: A cloud-fog based environment using beam search algorithm in smart grid. Presented at the 5 September 2019

24.

Yaghmaee Moghaddam, M.H., Leon-Garcia, A.: A fog-based internet of energy architecture for transactive energy management systems. IEEE Internet Things J. 5, 1055–1069 (2018)CrossRef

25.

Al-Jaroodi, J., Mohamed, N., Jawhar, I., Mahmoud, S.: CoTWare: a cloud of things middleware. In: Proceedings of IEEE 37th International Conference on Distributed Computing Systems Workshops, ICDCSW 2017, pp. 214–219 (2017)

26.

Shahryari, K., Anvari-Moghaddam, A.: Demand side management using the internet of energy based on fog and cloud computing. In: Proceedings of 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017, pp. 931–936 (2018)

27.

Wang, P., Liu, S., Ye, F., Chen, X.: A fog-based architecture and programming model for IoT applications in the smart grid (2018)

28.

Zahoor, S., Javaid, N., Khan, A., Ruqia, B., Muhammad, F.J., Zahid, M.: A cloud-fog-based smart grid model for efficient resource utilization. In: 2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018, pp. 1154–1160 (2018)

29.

Mishra, J., Sheetlani, J., Reddy, K.H.K., Roy, D.S.: A novel edge-supported cost-efficient resource management approach for smart grid system. Adv. Intell. Syst. Comput. 710, 369–380 (2018)

30.

Ismail, M., Javaid, N., Zakria, M., Zubair, M., Saeed, F., Zaheer, M.A.: Cloud-fog based smart grid paradigm for effective resource distribution. Presented at the 5 September 2019

31.

Nazir, S., Shafiq, S., Iqbal, Z., Zeeshan, M., Tariq, S., Javaid, N.: Cuckoo optimization algorithm based job scheduling using cloud and fog computing in smart grid. Presented at the 5 September 2019

32.

Fatima, A., Javaid, N., Waheed, M., Nazar, T., Shabbir, S., Sultana, T.: Efficient resource allocation model for residential buildings in smart grid using fog and cloud computing. In: Barolli, L., Xhafa, F., Javaid, N., Enokido, T. (eds.) IMIS 2018. AISC, vol. 773, pp. 289–298. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-93554-6_26CrossRef

33.

Mehmood, M., Javaid, N., Akram, J., Abbasi, S.H., Rahman, A., Saeed, F.: Efficient resource distribution in cloud and fog computing. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds.) NBiS 2018. LNDECT, vol. 22, pp. 209–221. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98530-5_18CrossRef

34.

Ahmad, N., Javaid, N., Mehmood, M., Hayat, M., Ullah, A., Khan, H.A.: Fog-cloud based platform for utilization of resources using load balancing technique. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds.) NBiS 2018. LNDECT, vol. 22, pp. 554–567. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98530-5_48CrossRef

35.

Carvalho, O., Garcia, M., Roloff, E., Carreño, E.D., Navaux, P.O.A.: IoT workload distribution impact between edge and cloud computing in a smart grid application. Commun. Comput. Inf. Sci. 796, 203–217 (2018)

36.

Ning, S., Ge, Q., Jiang, H.: Research on distributed computing method for coordinated cooperation of distributed energy and multi-devices. In: 2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC), pp. 905–910 (2018)

37.

Alrawais, A., Alhothaily, A., Hu, C., Xing, X., Cheng, X.: An attribute-based encryption scheme to secure fog communications. IEEE Access. 5, 9131–9138 (2017)CrossRef

38.

Islam, T., Hashem, M.M.A.: A big data management system for providing real time services using fog infrastructure. In: 2018 IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2018, pp. 85–89 (2018)

39.

Beligianni, F., Alamaniotis, M., Fevgas, A., Tsompanopoulou, P., Bozanis, P., Tsoukalas, L.H.: An internet of things architecture for preserving privacy of energy consumption. In: Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MedPower 2016, p. 107 (7)–107 (7) (2016)

40.

Han, W., Xiao, Y.: Big data security analytic for smart grid with fog nodes. In: Wang, G., Ray, I., Alcaraz Calero, Jose M., Thampi, Sabu M. (eds.) SpaCCS 2016. LNCS, vol. 10066, pp. 59–69. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49148-6_6CrossRef

41.

Sani, A.S., Yuan, D., Jin, J., Gao, L., Yu, S., Dong, Z.Y.: Cyber security framework for Internet of Things-based Energy Internet. Futur. Gener. Comput. Syst. (2018)

42.

Lyu, L., Nandakumar, K., Rubinstein, B., Jin, J., Bedo, J., Palaniswami, M.: PPFA: privacy preserving fog-enabled aggregation in smart grid. IEEE Trans. Ind. Inform. 14, 3733–3744 (2018)CrossRef

43.

Qureshi, N.M.F., et al.: An aggregate MapReduce data block placement strategy for wireless IoT edge nodes in smart grid. Wirel. Pers. Commun. 1, 1–12 (2018)

44.

Barik, R.K., et al.: FogGrid : leveraging fog computing for enhanced smart grid network. In: 14TH IEEE India Council International Conference, INDICON 2017, pp. 1–6 (2017)

45.

Jaradat, M., Jarrah, M., Bousselham, A., Jararweh, Y., Al-Ayyoub, M.: The internet of energy: Smart sensor networks and big data management for smart grid. Proced. Comput. Sci. 56, 592–597 (2015)CrossRef

46.

Meloni, A., Pegoraro, P.A., Atzori, L., Benigni, A., Sulis, S.: Cloud-based IoT solution for state estimation in smart grids: exploiting virtualization and edge-intelligence technologies. Comput. Netw. 130, 156–165 (2018)CrossRef

47.

Zhang, Y., Liang, K., Zhang, S., He, Y.: Applications of edge computing in PIoT. In: Proceedings of 2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017, pp. 1–4 (2018)

48.

Chen, Y.D., Azhari, M.Z., Leu, J.S.: Design and implementation of a power consumption management system for smart home over fog-cloud computing. In: 2018 International Conference on Intelligent Green Building and Smart Grid, IGBSG 2018, pp. 1–5 (2018)

49.

Hussain, M., Alam, M.S., Beg, M.M.S.: Fog assisted cloud models for smart grid architectures - comparison study and optimal deployment, pp. 1–27 (2018)

50.

Kumar, S., Agarwal, S., Krishnamoorthy, A., Vijayarajan, V., Kannadasan, R.: Improving the response time in smart grid using fog computing. In: Kulkarni, A.J., Satapathy, S.C., Kang, T., Kashan, A.H. (eds.) Proceedings of the 2nd International Conference on Data Engineering and Communication Technology. AISC, vol. 828, pp. 563–571. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-1610-4_57CrossRef

51.

Minh, Q.T., Nguyen, D.T., Van Le, A., Nguyen, H.D., Truong, A.: Toward service placement on fog computing landscape. In: Proceedings of 2017 4th NAFOSTED Conference on Information and Computer Science, NICS 2017, pp. 291–296 (2017)

52.

Yan, Y., Su, W.: A fog computing solution for advanced metering infrastructure. In: Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, pp. 1–4 (2016)

53.

Rabie, A.H., Ali, S.H., Ali, H.A., Saleh, A.I.: A fog based load forecasting strategy for smart grids using big electrical data (2018). http://dx.doi.org/10.1007/s10586-018-2848-x

54.

Jiang, Z., Shah, H., Rojas-Cessa, R., Grebel, H., Mohamed, A.: Experimental evaluation of power distribution to reactive loads in a network-controlled delivery grid. In: 2018 3rd International Conference on Fog and Mobile Edge Computing, FMEC 2018, pp. 199–204 (2018)

55.

Cao, H., Liu, S., Wu, L., Guan, Z., Du, X.: Achieving differential privacy against non-intrusive load monitoring in smart grid: a fog computing approach. Concurr. Comput. Pract. Exp., p. e4528 (2018)

56.

Mousavi, M.J., Stoupis, J., Saarinen, K.: Event zone identification in electric utility systems using statistical machine learning. In: 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), pp. 1–9 (2018)

57.

Khan, S., Paul, D., Momtahan, P., Aloqaily, M.: Artificial intelligence framework for smart city microgrids: state of the art, challenges, and opportunities. In: 2018 3rd International Conference on Fog and Mobile Edge Computing, FMEC 2018, pp. 283–288 (2018)

58.

Tom, R.J., Sankaranarayanan, S.: IoT based SCADA integrated with fog for power distribution automation. In: Iberian Conference on Information Systems and Technologies, CISTI, pp. 1–4. ACM, Santa Clara (2017)

59.

Kumar, N., Zeadally, S., Rodrigues, J.J.P.C.: Vehicular delay-tolerant networks for smart grid data management using mobile edge computing. IEEE Commun. Mag. 54, 60–66 (2016)CrossRef

60.

Naeem, M., Javaid, N., Zahid, M., Abbas, A., Rasheed, S., Rehman, S.: Cloud and fog based smart grid environment for efficient energy management. In: Xhafa, F., Barolli, L., Greguš, M. (eds.) INCoS 2018. LNDECT, vol. 23, pp. 514–525. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98557-2_48CrossRef

61.

KaleemUllah Khan, M., Javaid, N., Murtaza, S., Zahid, M., Ali Gilani, W., Junaid Ali, M.: Efficient energy management using fog computing. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds.) NBiS 2018. LNDECT, vol. 22, pp. 286–299. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98530-5_24CrossRef

62.

Naqvi, S.A.A., Javaid, N., Butt, H., Kamal, M.B., Hamza, A., Kashif, M.: Metaheuristic optimization technique for load balancing in cloud-fog environment integrated with smart grid. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds.) NBiS 2018. LNDECT, vol. 22, pp. 700–711. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98530-5_61CrossRef

63.

Matta, N., Rahim-Amoud, R., Merghem-Boulahia, L., Jrad, A.: Putting sensor data to the service of the smart grid: from the substation to the AMI. J. Netw. Syst. Manage. 26, 108–126 (2018)CrossRef

64.

Rasheed, S., Javaid, N., Rehman, S., Hassan, K., Zafar, F., Naeem, M.: A cloud-fog based smart grid model using max-min scheduling algorithm for efficient resource allocation. In: Barolli, L., Kryvinska, N., Enokido, T., Takizawa, M. (eds.) NBiS 2018. LNDECT, vol. 22, pp. 273–285. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-98530-5_23CrossRef

65.

Okay, F.Y., Ozdemir, S.: A secure data aggregation protocol for fog computing based smart grids. In: Proceedings of 2018 IEEE 12th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2018, pp. 1–6 (2018)

66.

Aujla, G.S., Chaudhary, R., Kumar, N., Kumar, R., Rodrigues, J.J.P.C.: An ensembled scheme for QoS-aware traffic flow management in software defined networks. In: IEEE International Conference on Communications, pp. 1–7 (2018)

67.

El-Sayed, H., et al.: Edge of things: the big picture on the integration of edge, IoT and the cloud in a distributed computing environment. IEEE Access. 6, 1706–1717 (2017)CrossRef

68.

Bakken, D., et al.: Towards enhanced power grid management via more dynamic and flexible edge computations. In: 2017 IEEE Fog World Congress, FWC 2017, pp. 1–8 (2018)

69.

Akram, W., Niazi, M.A.: A formal specification framework for smart grid components. Complex Adapt. Syst. Model. 6, 5 (2018)CrossRef

70.

Hussain, M.M., Alam, M.S., Beg, M.M.S.: Fog computing in IoT aided smart grid transition- requirements, prospects, status quos and challenges (2018)

71.

Aujla, G.S., Kumar, N.: MEnSuS: An efficient scheme for energy management with sustainability of cloud data centers in edge–cloud environment. Futur. Gener. Comput. Syst. 86, 1279–1300 (2018)CrossRef

72.

Fatima, I., Javaid, N., Iqbal, M.N., Shafi, I., Anjum, A., Ullah Memon, U.: Integration of cloud and fog based environment for effective resource distribution in smart buildings. In: 2018 14th International Wireless Communications and Mobile Computing Conference, IWCMC 2018, pp. 60–64 (2018)

73.

Nazmudeen, M.S.H., Wan, A.T., Buhari, S.M.: Improved throughput for power line communication (PLC) for smart meters using fog computing based data aggregation approach. In: Proceedings of IEEE 2nd International Smart Cities Conference: Improving the Citizens Quality of Life, ISC2 2016, pp. 1–4 (2016)

74.

Hackenberg, G., Irlbeck, M., Koutsoumpas, V., Bytschkow, D.: Applying formal software engineering techniques to smart grids. In: Proceedings of 2012 1st International Workshop on Software Engineering Challenges for the Smart Grid, SE-SmartGrids 2012, pp. 50–56 (2012)

75.

Rohjans, S., Lehnhoff, S., Schütte, S., Andrén, F., Strasser, T.: Requirements for smart grid simulation tools. In: IEEE International Symposium on Industrial Electronics, pp. 1730–1736 (2014)

76.

Young, J.: Smart grid technology in the developing world. Honors Projects (2017)

Titel: A Critical Review of Edge and Fog Computing for Smart Grid Applications
verfasst von: Gilbert M. Gilbert
Shililiandumi Naiman
Honest Kimaro
Burchard Bagile
Verlag: Springer International Publishing
Buch: Information and Communication Technologies for Development. Strengthening Southern-Driven Cooperation as a Catalyst for ICT4D
Print ISBN: 978-3-030-18399-8

Electronic ISBN: 978-3-030-18400-1

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-18400-1_62

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