Skip to main content

A Reputation Model for Third-Party Service Providers in Fog as a Service

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11337))

Abstract

Fog computing, as a mode of distributing computing resources, can process data directly at the network edge so becomes a promising solution towards the Internet of Things (IoT). To support various IoT services, many third-party fog resources providers participate in the service provisioning process, which accelerates the development of Fog as a Service (FaaS). Current solutions assume the existence of a reliable entity to maintain run-time information about such third-party fog resources providers, which is not feasible because of resource constraints at the network edge. To be aware of the dynamic availability of the fog resources, this paper proposes a graph-based decentralized reputation model for service provisioning in fog computing environment. This mechanism includes a verification model between fog nodes and a consensus mechanism for composite transactions in FaaS. This paper evaluates the proposed solution and proves its feasibility through the experimental result.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Pirbhulal, S., Zhang, H., Me, A.E.: A novel secure IoT-based smart home automation system using a wireless sensor network. Sensors 17(1), 69 (2017)

    Google Scholar 

  2. Ming, L. (1999). http://www.dvbcn.com/2018/04/12-161148.html. Accessed 19 April 2018

  3. Zheng, Z., Wang, P., Liu, J.: Real-time big data processing framework: challenges and solutions. Appl. Math. Inf. Sci. 9(6), 3169–3190 (2015)

    Google Scholar 

  4. Bonomi, F., Milito, R., Natarajan, P., Zhu, J.: Fog computing: a platform for internet of things and analytics. In: Bessis, N., Dobre, C. (eds.) Big Data and Internet of Things: A Roadmap for Smart Environments. SCI, vol. 546, pp. 169–186. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-05029-4_7

    Chapter  Google Scholar 

  5. Skarlat, O., Nardelli, M., Schulte, S.: Resource provisioning for IoT services in the fog. Serv. Oriented Comput. Appl. 11(4), 427–443 (2016)

    Article  Google Scholar 

  6. Chaudhary, R., Kumar, N., Zeadally, S.: Network service chaining in fog and cloud computing for the 5G environment: data management and security challenges. IEEE Commun. Mag. 55(11), 114–122 (2017)

    Article  Google Scholar 

  7. Ashrafi, T.H., Hossain, M.A., Arefin, S.E., Das, K.D.J., Chakrabarty, A.: Service based FOG computing model for IoT. In: IEEE International Conference on Collaboration and Internet Computing, pp. 163–172. IEEE Computer Society (2017)

    Google Scholar 

  8. Minh, Q.T., Nguyen, D.T., An, V.L., Hai, D.N., Truong, A.: Toward service placement on Fog computing landscape. In: Nafosted Conference on Information and Computer Science, pp. 291–296 (2017)

    Google Scholar 

  9. Santoro, D., Zozin, D., Pizzolli, D., Pellegrini, F.D., Cretti, S.: Foggy: a platform for workload orchestration in a fog computing environment. IEEE International Conference on Cloud Computing Technology and Science, pp. 231–234. IEEE (2017)

    Google Scholar 

  10. Yang, Y.: FA2ST: Fog as a Service Technology. In: IEEE Computer Software and Applications Conference, p. 708. IEEE Computer Society (2017)

    Google Scholar 

  11. Chen, N., Clarke, S.: A dynamic service composition model for adaptive systems in mobile computing environments. In: Franch, X., Ghose, Aditya K., Lewis, Grace A., Bhiri, S. (eds.) ICSOC 2014. LNCS, vol. 8831, pp. 93–107. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45391-9_7

    Chapter  Google Scholar 

  12. Divya, M., Biradar, N.B.: IOTA-next generation block chain. Int. J. Eng. Comput. Sci. 7, 23823–23826 (2018)

    Article  Google Scholar 

  13. Serguei, P.: Tangle. IOTA (2017)

    Google Scholar 

  14. Kalasapur, S., Kumar, M., Shirazi, B.A.: Dynamic service composition in pervasive computing. IEEE Trans. Parallel Distrib. Syst. 18, 907–918 (2007)

    Article  Google Scholar 

  15. Tschorsch, F., Scheuermann, B.: Bitcoin and beyond: a technical survey on decentralized digital currencies. IEEE Commun. Surv. Tutor. 18(3), 2084–2123 (2016)

    Article  Google Scholar 

  16. Cao, Z., Zhang, X., Zhang, W.: A context-aware adaptive web service composition framework. In: IEEE International Conference on Computational Intelligence & Communication Technology, pp. 62–66. IEEE (2015)

    Google Scholar 

  17. Madkour, M., Ghanami, D.E., Maach, A.: Context-aware service adaptation: an approach based on fuzzy sets and service composition. J. Inf. Sci. Eng. 29(1), 1–16 (2013)

    Google Scholar 

  18. Lin, C., Kavi, K.: A QoS-aware BPEL framework for service selection and composition using QoS properties. Int. J. Adv. Softw. 6(1 and 2), 56–68 (2014)

    Google Scholar 

  19. Rajeswari, M., Sambasivam, G., Balaji, N.: Original article: appraisal and analysis on various web service composition approaches based on QoS factors. J. King Saud Univ.-Comput. Inf. Sci. 26(1), 143–152 (2014)

    Google Scholar 

  20. Wang, Z., Xu, T., Qian, Z.: A parameter-based scheme for service composition in pervasive computing environment. In: Complex, Intelligent and Software Intensive Systems, CISIS 2009 (2009)

    Google Scholar 

  21. Chen, N., Yang, Y., Li, J., Zhang, T.: A fog-based service enablement architecture for cross-domain IoT applications. IEEE Fog World Congress (2017)

    Google Scholar 

  22. Jamali, M., Ester, M.: A matrix factorization technique with trust propagation for recommendation in social networks. In: ACM Conference on Recommender Systems, pp. 135–142 ACM (2010)

    Google Scholar 

  23. Liu, G., Wang, Y., Orgun, M.A., et al.: Finding the optimal social trust path for the selection of trustworthy service providers in complex social networks. IEEE Trans. Serv. Comput. 6(2), 152–167 (2013)

    Article  Google Scholar 

  24. Ziegler, C.N., Lausen, G.: Spreading activation models for trust propagation. In: IEEE International Conference on e-Technology, e-Commerce and e-Service, pp. 83–97. IEEE (2004)

    Google Scholar 

  25. Yang, Y., Wu, Y., Chen, N., et al.: LOCASS: local optimal caching algorithm with social selfishness for mixed cooperative and selfish devices. IEEE Access PP(99), 1 (2018)

    Google Scholar 

Download references

Acknowledgement

This work is supported by the Key Program of the Chinese Academy of Sciences (Grant No. QYZDY-SSW-JSC034) and the Key Project of Science and Technology of Shanghai (Grant No. 16JC1420503).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nanxi Chen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chen, N., Xu, X., Miao, X. (2018). A Reputation Model for Third-Party Service Providers in Fog as a Service. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11337. Springer, Cham. https://doi.org/10.1007/978-3-030-05063-4_45

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-05063-4_45

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05062-7

  • Online ISBN: 978-3-030-05063-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics