Mobile Edge Computing-Enabled Blockchain Framework—A Survey

  • Pronaya BhattacharyaEmail author
  • Sudeep Tanwar
  • Rushabh Shah
  • Akhilesh Ladha
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 597)


Mobile edge computing (MEC) enables cloud-based services to extend to edge networks consisting of mobile base systems. MEC provides software and hardware platforms to incorporate seamless and decentralized data management schemes adjacent to base systems, thus reducing the end-to-end latency of the user. It is an integral component of the fifth-generation (5G) architecture and operates by providing innovative IT-based services. MEC spans across multiple authoritative domains where trust and interoperability among nodes is a prime concern between low power-enabled sensor nodes, as in the case of Internet of things (IoT)-based environments. The requirements of trust and interoperability make a blockchain framework applicable to MEC platform. In such platforms, miners can solve computationally expensive proof-of-work (PoW) puzzles containing mobile transactions as blocks added to immutable ledger so that a substantial amount of CPU computations and energy constraints are consumed. This article presents a systematic survey of MEC architecture and introduces a mobile blockchain framework that can be incorporated with the MEC architecture to facilitate the mining scheme. Then, the article analyzes the effects of integration of blockchain with MEC platform. Finally, concluding remarks and future work are provided.


Mobile edge computing Mobile blockchain Mining 5G IoT nodes 


  1. 1.
    Borgia, E., Bruno, R., Conti, M., Mascitti, D., Passarella, A.: Mobile edge clouds for information-centric IoT services. In: Proceedings of IEEE Symposium on Computers and Communications (ISCC), Messina, Italy, June 2016, pp. 422–428. Author, F.: Article title. Journal 2(5), 99–110 (2016)Google Scholar
  2. 2.
    Marotta, M.A., et al.: Managing mobile cloud computing considering objective and subjective perspectives. Comput. Netw. 93, 531–542, Oct. [Online]. Available: (2015)
  3. 3.
    Dinh, H.T., Lee, C., Niyato, D., Wang, P.: A survey of mobile cloud computing: architecture, applications, and approaches. Wirel. Commun. Mob. Comput. 13(18), 1587–1611 (2013)CrossRefGoogle Scholar
  4. 4.
    Jararweh, Y., et al.: The future of mobile cloud computing: integrating cloudlets and mobile edge computing. In: Proceedings of 23rd International Conference on Telecommunications (ICT), pp. 1–5. Thessaloniki, Greece (2016)Google Scholar
  5. 5.
    Yi, S., Li, C., Li, Q.: A survey of fog computing: concepts, applications, and issues. In: Proceedings of Workshop Mobile Big Data (Mobidata), pp. 37–42. Hangzhou, China (2015)Google Scholar
  6. 6.
    Jararweh, Y., et al.: SDMEC: software defined system for mobile edge computing. In: Proceedings of IEEE International Conference on Cloud Engineering Workshop (IC2EW), pp. 88–93 Berlin, Germany (2016)Google Scholar
  7. 7.
    European Telecommunication Standards Institute. Mobile Edge Computing Introductory Technical. Whitepaper (2019)Google Scholar
  8. 8.
    Suikkola, V.: Open exposure of telco capabilities—identification of critical success factors for location-based services in open telco. In: 6th International Conference on Wireless and Mobile Communications, pp. 202–208. IEEE Press: Valencia, Spain (2010)Google Scholar
  9. 9.
    Moreno-Vozmediano, R., Montero, R.S., Llorente, I.M.: IaaS cloud architecture: from virtualized datacenters to federated cloud infrastructures. Computer 45(12), 6572 (2012)CrossRefGoogle Scholar
  10. 10.
    Wong, V.W., et al.: Key technologies for 5G wireless systems. Cambridge University Press (2017)Google Scholar
  11. 11.
    Zhang, Y., et al.: Offloading in software defined network at edge with information asymmetry: a contract theoretical approach. J. Signal Process. Syst. 83(2), 241–253 (2016)CrossRefGoogle Scholar
  12. 12.
    Foroglou, G., Tsilidou, A.L.: Further applications of the blockchain (2015)Google Scholar
  13. 13.
    Peters, G.W., Panayi, E., Chapelle, A.: Trends in crypto-currencies and blockchain technologies: a monetary theory and regulation perspective (2015)Google Scholar
  14. 14.
    Christidis, K., Devetsikiotis, M.: Blockchains and smart contracts for the Internet of Things. IEEE Access 4, 2292–2303 (2016)CrossRefGoogle Scholar
  15. 15.
    Zhang, Y., Wen, J.: An IoT electric business model based on the protocol of bitcoin. In: Proceedings of 18th International Conference on Intelligence in Next Generation Networks (ICIN). pp. 184–191. Paris, France (2015)Google Scholar
  16. 16.
    Kosba, A., Miller, A., Shi, E., Wen, Z., Papamanthou, C.: Hawk: the blockchain model of cryptography and privacy-preserving smart contracts. In: Proceedings of IEEE Symposium on Security and Privacy (SP). pp. 839–858. San Jose, CA, USA (2016)Google Scholar
  17. 17.
    Peterson, K., Deeduvanu, R., Kanjamala, P., Mayo, K.B.: A blockchain-based approach to health information exchange networks (2016)Google Scholar
  18. 18.
    Vora, J., et al.: BHEEM: a blockchain-based framework for securing electronic health records, 2018 IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, United Arab Emirates, pp. 1–6 (2018)Google Scholar
  19. 19.
    Wang, L., Liu, W., Han, X.: Blockchain-based government information resource sharing. In: 2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS), pp. 804–809. Shenzhen (2017)Google Scholar
  20. 20.
    Srivastava, A., Bhattacharya, P., Singh, A., Mathur, A., Prakash, O., Pradhan, R.: A distributed credit transfer educational framework based on blockchain. In: IEEE 2018 2nd International Conference on Advances in Computing, Control and Communication Technology (IA3CT 2018), Allahabad, Uttar Pradesh, India, pp. 54–59 (2018)Google Scholar
  21. 21.
    Satria, D., Park, D., Jo, M.: Recovery for overloaded mobile edge computing. Futur. Gener. Comput. Syst. 70, 138–147 (2017)CrossRefGoogle Scholar
  22. 22.
    Patel, M., et al.: Mobile-edge computing—introductory technical white paper. In: White Paper, Mobile-Edge Computing (MEC) Industry Initiative (2014)Google Scholar
  23. 23.
    Pfaff, B., Pettit, J., Koponen, T., et al.: The design and implementation of open vSwitch. In: Networked Systems Design and Implementation (2015)Google Scholar
  24. 24.
    Beimborn, D., Miletzki, T., Wenzel, S., et al.: Platform as a Service (PaaS). Bus. Inf. Syst. Eng. 3(6), 381–384 (2011)CrossRefGoogle Scholar
  25. 25.
    Commun. (ICFCC), Kuala Lumpar, Malaysia, pp. 334–338. CommVerge. (2016). Radio Access Network (RAN) Optimization. Last Accessed on 19 Feb 2002. [Online]. Available: (2009)
  26. 26.
    Wu, Y., et al.: Joint traffic scheduling and resource allocations for traffic offloading with secrecy-provisioning. IEEE Trans. Vehic. Tech. 66(9), 8315–8332 (2017)CrossRefGoogle Scholar
  27. 27.
    Pass, R., Shi, E.: FruitChains: a fair blockchain. In: PODC‘17 Proceedings of ACM Symposium, Principles of Distributed Computing, pp. 315–24 Washington, DC (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Pronaya Bhattacharya
    • 1
    • 2
    Email author
  • Sudeep Tanwar
    • 1
  • Rushabh Shah
    • 1
  • Akhilesh Ladha
    • 1
  1. 1.Department of Computer Science and EngineeringInstitute of Technology, Nirma UniversityAhmedabadIndia
  2. 2.Department of Computer Science and EngineeringDr. A.P.J Abdul Kalam Technical UniversityLucknowIndia

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