Advertisement

An Application-Driven Heterogeneous Internet of Things Integration Architecture

  • Changhao WangEmail author
  • Shining Li
  • Yan Pan
  • Bingqi Li
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1035)

Abstract

Smart city consists of heterogenous Internet of Things (IoTs) and urban application systems. To achieve smart city integration, One critical challenge is that these heterogenous systems are implemented independently, and hard to communicate with each other. To address this issue, the authors propose an application-driven heterogeneous IoTs architecture. Under this architecture, all kinds of resources are uniformly described by extracting the common characteristics of application requirements in smart cities to form independent and complete capability components, resources are reconfigured according to application requirements to provide adaptive resources and differentiated services for urban applications. The results show that our proposed architecture can effectively solve the problem of deep integration of heterogeneous Internet of things.

Keywords

Application-driven Heterogenous architecture Internet of Things 

Notes

Acknowledgments

This work is supported by National Natural Science Foundation of China (NSFC) under Grant No. 61872434 and Key R&D Program of Shaanxi Province in 2017 (No. 2017ZDXM-GY-018).

References

  1. 1.
    Wang, J.: Research on routing in software defined internet of things. Huazhong University of Science & Technology, Wuhan, China (2016)Google Scholar
  2. 2.
    Wang, X.A., Liu, Y., Zhang, J., Yang, X., Zhang, M.: Improved group-oriented proofs of cloud storage in IoT setting. Concurr. Comput.: Pract. Exp. 30(21), e4781 (2018)CrossRefGoogle Scholar
  3. 3.
    Huo, R., et al.: Software defined networking, caching, and computing for green wireless networks. IEEE Commun. Mag. 54(11), 185–193 (2016)CrossRefGoogle Scholar
  4. 4.
    Wang, X.A., Yang, X., Li, C., Liu, Y., Ding, Y.: Improved functional proxy re-encryption schemes for secure cloud data sharing. Comput. Sci. Inf. Syst. 15(3), 585–614 (2018)CrossRefGoogle Scholar
  5. 5.
    Mckeown, N.: Software-defined networking. INFOCOM Keynote Talk 17(2), 30–32 (2009)Google Scholar
  6. 6.
    Volpato, F., Silva, M.P.D., Dantas, M.A.R.: OFQuality: a quality of service management module for software-defined networking. Int. J. Grid Util. Comput. 10(2), 187–198 (2019)CrossRefGoogle Scholar
  7. 7.
    Cheng, B., et al.: Situation-aware dynamic service coordination in an IoT environment. IEEE/ACM Trans. Netw. (TON) 25(4), 2082–2095 (2017)CrossRefGoogle Scholar
  8. 8.
    Zhang, J., Zhang, X., Wang, W.: Cache-enabled software defined heterogeneous networks for green and flexible 5G networks. IEEE Access 4, 3591–3604 (2016)Google Scholar
  9. 9.
    Qiao, X., Zhang, Y., Wu, B., et al.: Event-driven, service-oriented internet of things service delivery method. Sci. China Inf. Sci. 43(10), 1219–1243 (2013)Google Scholar
  10. 10.
    Ye, Q., et al.: End-to-end quality of service in 5G networks: examining the effectiveness of a network slicing framework. IEEE Veh. Technol. Mag. 13(2), 65–74 (2018)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Liu, J., et al.: Software-defined internet of things for smart urban sensing. IEEE Commun. Mag. 53(9), 55–63 (2015)CrossRefGoogle Scholar
  12. 12.
    Li, Z., He, T.: WEBee: Physical-layercross-technology communication via emulation. In: Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking, pp. 2–14. ACM (2017)Google Scholar
  13. 13.
    Guo, X., He, Y., Zheng, X., et al.: LEGO-Fi: transmitter-transparent CTC with cross-demapping. In: Proceedings of IEEE INFOCOM (2019)Google Scholar
  14. 14.
    Jiang, W., Yin, Z., Liu, R., et al.: BlueBee: a 10,000 x faster cross-technology communication via phy emulation. In: Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems, p. 3. ACM (2017)Google Scholar
  15. 15.
    Liu, J., Wang, S., Li, S., Cui, X., Pan, Y., Zhu, T.: MCTS: multi-channel transmission simultaneously using non-feedback fountain code. IEEE Access 6, 58373–58382 (2018)CrossRefGoogle Scholar
  16. 16.
    Wang, W., Liu, X., Yao, Y., Pan, Y., Chi, Z., Zhu, T.: CRF: coexistent routing and flooding using WiFi packets in heterogeneous IoT networks. In: IEEE IN-FOCOM 2019 - IEEE Conference on Computer Communications (INFOCOM 2019), Paris, France (2019)Google Scholar
  17. 17.
    Ling, J., Jiang, L.Y.: Semantic description of IoT services: a method of mapping WSDL to OWL-S. Comput. Sci. 4, 89–94 (2019)Google Scholar
  18. 18.
    Huang, H.: Collaborative resource allocation algorithms over hybrid networks based on primal-dual method. University of Science and Technology of China (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringNorthwestern Polytechnical UniversityXi’anPeople’s Republic of China

Personalised recommendations