Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Design of a distributed offloading and real-time data unified access platform for IoT within command and control communication networks

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

With the rapid convergence of the Internet of Things (IoT) and command and control communication networks, there is a swift surge in computation-intensive applications and heterogenous devices. Building an edge computing network near the protocol gateway not only facilitates network protocol conversion, but also alleviates computational load on the gateway. Nevertheless, traditional protocol gateways necessitate the inclusion of conversion methods for all communication protocols in the network for data interoperability with other devices. Consequently, constructing low-complexity protocol conversion programs, and the more efficient and equitable allocation of edge server resources, are critical challenges that need to be addressed. This paper investigates the joint problem of task offloading and heterogeneous protocol device access in command and control communication networks, deriving the benefit parameters of task offloading. We propose a real-time data unified access platform, which, by distributing configuration files, enables the IoT gateway to generate protocol conversion programs, thereby transforming all device protocols into a unified common protocol. Furthermore, to enhance the efficiency of heterogeneous device access to the network, we design a data parsing/encapsulation algorithm based on the real-time data unified access platform, supporting bidirectional mapping of two types of data. Experimental validation confirms the reasonability and effectiveness of the proposed scheme.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

Enquiries about data availability should be directed to the authors.

References

  1. Park, H.D., et al.: Scalable architecture for an automated surveillance system using edge computing. J. Supercomput. (2017). https://doi.org/10.1007/s11227-016-1750-7

    Article  Google Scholar 

  2. Romano, P., Quaglia, F.: Design and evaluation of a parallel invocation protocol for transactional applications over the web. IEEE Trans. Comput. 63(2), 317–334 (2014)

    Article  MathSciNet  Google Scholar 

  3. Wang, J.Y., Yen, L.H., Liman, J.: Incentive-stable matching protocol for service chain placement in multi-operator edge system. IEICE Trans. Commun. E105.B, 1353–1360 (2022)

    Article  Google Scholar 

  4. Satyanarayanan, M., Bahl, P., Caceres, R., et al.: The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput. 8(4), 14–23 (2009)

    Article  Google Scholar 

  5. Chun, B.G., Maniatis, P.: Augmented smartphone applications through clone cloud execution. In: Conference on hot topics in operating systems. USENIX Association (2009)

  6. Zhang, X., Kunjithapatham, A., Jeong, S., et al.: Towards an elastic application model for augmenting the computing capabilities of mobile devices with cloud computing. Mob. Netw. Appl. 16(3), 270–284 (2011)

    Article  Google Scholar 

  7. Chun, B.G., Ihm, S., Maniatis, P., et al.: CloneCloud: elastic execution between mobile device and cloud. In: Conference on computer systems. ACM (2011)

  8. He, Y., Ren, J., Yu, G., et al.: D2D communications meet mobile edge computing for enhanced computation capacity in cellular networks. IEEE Trans. Wirel. Commun. (2019). https://doi.org/10.1109/TWC.2019.2896999

    Article  Google Scholar 

  9. Zhang, W., Wen, Y., Guan, K., et al.: Energy-optimal mobile cloud computing under stochastic wireless channel. IEEE Trans. Wirel. Commun. 12(9), 4569–4581 (2013)

    Article  Google Scholar 

  10. Liu, B., Liu, C., Peng, M.: Resource allocation for energy-efficient MEC in NOMA-enabled massive IoT networks. IEEE J. Sel. Areas Commun. (2020). https://doi.org/10.1109/JSAC.2020.3018809

    Article  Google Scholar 

  11. You, C., Huang, K., Chae, H., et al.: Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Trans. Wirel. Commun. 16(3), 1397–1411 (2017)

    Article  Google Scholar 

  12. You, C., Huang, K., Chae, H.: Energy efficient mobile cloud computing powered by wireless energy transfer. IEEE J. Sel. Areas Commun. 34(5), 1757–1771 (2016)

    Article  Google Scholar 

  13. Wang, Y., Min, S., Wang, X., et al.: Mobile-edge computing: partial computation offloading using dynamic voltage scaling. IEEE Trans. Commun. 64(10), 4268–4282 (2016)

    Google Scholar 

  14. Sardellitti, S., Scutari, G., Barbarossa, S.: Joint optimization of radio and computational resources for multicell mobile-edge computing. IEEE Trans. Signal Inf. Process. Over Netw. 1(2), 89–103 (2015)

    Article  MathSciNet  Google Scholar 

  15. Dai, S., Liwang, M., Gao, Z., Huang, F.L., Du, X., Guizani, M.: An adaptive computation offloading mechanism for mobile helth applications. IEEE Trans. Veh. Technol. 69(1), 998–1007 (2020)

    Article  Google Scholar 

  16. Liu, J., Mao, Y., Zhang, J., et al.: Delay-optimal computation task scheduling for mobile-edge computing systems. IEEE (2016). https://doi.org/10.1109/ISIT.2016.7541539

    Article  Google Scholar 

  17. Molina, M., Muñoz, O., Pascual-Iserte, A., et al.: Joint scheduling of communication and computation resources in multiuser wireless application offloading. In: IEEE international symposium on personal. IEEE (2015)

  18. Kao, Y.H., Krishnamachari, B., Ra, M.R., et al.: Hermes: latency optimal task assignment for resource-constrained mobile computing. In: 2015 IEEE conference on computer communications (INFOCOM). IEEE (2015)

  19. Ren, J., Yu, G., Cai, Y., et al.: Latency optimization for resource allocation in mobile-edge computation offloading. IEEE Trans. Wirel. Commun. 17(8), 5506–5519 (2018)

    Article  Google Scholar 

  20. Deng, R., Lu, R., Lai, C., et al.: Optimal workload allocation in fog-cloud computing toward balanced delay and power consumption. IEEE Internet Things J. 3(6), 1171–1181 (2017)

    Google Scholar 

  21. Mao, Y., Zhang, J., Song, S.H., et al.: Power-delay tradeoff in multi-user mobile-edge computing systems. In: IEEE. IEEE (2016)

  22. Uddin, M., Mukherjee, S., Chang, H., et al.: SDN-based multi-protocol edge switching for IoT service automation. IEEE J. Sel. Areas Commun. (2018). https://doi.org/10.1109/JSAC.2018.2871325

    Article  Google Scholar 

  23. Mcgrath, W., Etemadi, M., Roy, S., et al.: Fabryq: using phones as gateways to prototype internet of things applications using web scripting. In: ACM (2015)

  24. Hassanalieragh, M., Page, A., Soyata, T., et al.: Health monitoring and management using internet-of-things (IoT) sensing with cloud-based processing: opportunities and challenges. In: IEEE international conference on services computing. In: IEEE (2015)

  25. Lea, R., Blackstock, M.: City hub: a cloud-based IoT platform for smart cities. In: Proc. IEEE CloudCom (2014)

  26. Pereira, P.P., Eliasson, J., Kyusakov, R., et al.: Enabling cloud connectivity for mobile internet of things applications. In: 2013 IEEE seventh international symposium on service-oriented system engineering. IEEE (2013)

  27. Han, S., Kim, H.: On AUTOSAR TCP/IP performance in in-vehicle network environments. IEEE Commun. Mag. 54(12), 168–173 (2016)

    Article  Google Scholar 

  28. Botta, A., Pescapé, A., Ventre, G.: Quality of service statistics over heterogeneous networks: analysis and applications. Eur. J. Oper. Res. 191(3), 1075–1088 (2008)

    Article  Google Scholar 

Download references

Funding

This article did not receive funding.

Author information

Authors and Affiliations

Authors

Contributions

YY and HZ derive the main algorithm in the manuscript. YY and TC completed the software implementation in the manuscript. YY and ML complete the main content and picture preparation in the manuscript.

Corresponding author

Correspondence to YiZhuo Yang.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, Y., Zeng, H., Chen, T. et al. Design of a distributed offloading and real-time data unified access platform for IoT within command and control communication networks. Cluster Comput 27, 2313–2327 (2024). https://doi.org/10.1007/s10586-023-04081-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-023-04081-z

Keywords

Navigation