MWC: an efficient and secure multi-cloud storage approach to leverage augmentation of multi-cloud storage services on mobile devices using fog computing

  • Rajeev Kumar Bedi
  • Jaswinder Singh
  • Sunil Kumar Gupta


To store the sensitive and large amount of information on mobile devices is not recommended as it can be lost or stolen and the storage capacity is limited. Even the services of the single-cloud storage provider are not preferred due to issues like limited free storage, vendor lock-in and data loss. To deal with these issues, multi-cloud storage services are preferred which provide a single platform for multiple cloud storage services. From recent studies, it has been observed that the use of existing multi-cloud storage systems is uncommon by mobile users because they have lots of issues when accessed through resource-constrained mobile devices as they are consuming a lot of resources like CPU, battery and data (Internet usage) of mobile devices. So, in this paper, an efficient and secure multi-cloud storage approach is developed using the concept of fog computing to leverage augmentation of multi-cloud storage services on resource-constrained mobile devices.


Fog computing Multi-cloud storage CPU usage Data usage Battery consumption Data security 


  1. 1.
    Mell P, Grance T (2011) The NIST definition of cloud computingGoogle Scholar
  2. 2.
  3. 3.
    Josyula V, Orr M, Page G (2011) Cloud computing: automating the virtualized data center. Cisco Press, IndianapolisGoogle Scholar
  4. 4.
    Furht B (2010) Cloud computing fundamentals. Handbook of cloud computing. Springer, Berlin, pp 3–19CrossRefzbMATHGoogle Scholar
  5. 5.
    Alan H. Five best cloud storage providers.
  6. 6.
    Gartner, Gartner says that consumers will store more than a third of their digital content in the cloud by 2016.
  7. 7.
    King NJ, Raja V (2012) Protecting the privacy and security of sensitive customer data in the cloud. Comput Law Secur Rev 28:308–319CrossRefGoogle Scholar
  8. 8.
    Jansen W, Grance T (2011) Guidelines on security and privacy in public cloud computing. NIST Spec Publ 800:10–11Google Scholar
  9. 9.
    Gangula A, Ansari S, Gondhalekar M (2013) Survey on mobile computing security. In: Modelling Symposium (EMS), 2013 European, pp 536–542Google Scholar
  10. 10.
    Stefanov E, Shi E (2013) Multi-cloud oblivious storage. In: Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security, CCS 13, p 247258, New York, NY, USA, ACMGoogle Scholar
  11. 11.
    Yang K, Jia X (2013) An efficient and secure dynamic auditing protocol for data storage in cloud computing. IEEE Trans Parallel Distrib Syst 24(9):1717–1726CrossRefGoogle Scholar
  12. 12.
    Dobre D, Viotti P, Vukolic M (2014) Hybris robust hybrid cloud storage. In: Proceedings of the ACM Symposium on Cloud Computing, SOCC 14, pp 12:1–12:14, New York, 2014. ACMGoogle Scholar
  13. 13.
    Singh Y, Kandah F, Weiyi Z (2011) A secured cost effective multi-cloud storage in cloud computing. In: 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp 619–624Google Scholar
  14. 14.
    Go W, Kwak J (2014) Dual server-based secure data-storage system for cloud storage. Int J Eng Syst Model Simul 6:86–90Google Scholar
  15. 15.
    AlZain MA, Pardede E, Soh B, Thorn JA (2012) Cloud computing security: from single to multi-clouds. In: 2012 45th Hawaii International Conference on System Science (HICSS), pp 5490–5499Google Scholar
  16. 16.
    Hogan M, Liu F, Sokol A, Tong J (2011) Nist cloud computing standards roadmap, vol 35. NIST Special Publication, GaithersburgCrossRefGoogle Scholar
  17. 17.
    Alizadeh M, Hassan WH (2013) Challenges and opportunities of mobile cloud computing. In: Wireless Communications and Mobile Computing Conference (IWCMC), 2013 9th International, pp 660–666Google Scholar
  18. 18.
    Cox PA (2011) Mobile cloud computing. IBM Developerworks, pp 1–10Google Scholar
  19. 19.
  20. 20.
    Duro F, Blas J (2015) CoSMIC: a hierarchical cloudlet based storage architecture for mobile clouds. Simul Model Pract Theory 50:3–19CrossRefGoogle Scholar
  21. 21.
  22. 22.
    Alqahtani H, Mostefaoui G (2014) Multi-clouds Mobile Computing for the Secure Storage of Data. In: IEEE/ACM 7th International Conference on Utility and Cloud Computing, London, pp 495–496Google Scholar
  23. 23.
    Wang S, Liang K, Liu JK, Chen J, Yu J, Xie W (2016a) Attribute-based data sharing scheme revisited in cloud computing. IEEE Trans Inf Forensics Secur 11(8):1661–1673. CrossRefGoogle Scholar
  24. 24.
    Pasupuleti S, Ramalingam S (2016) An efficient and secure privacy-preserving approach for outsourced data of resource-constrained mobile devices in cloud computing. J Netw Comput Appl 64:12–22CrossRefGoogle Scholar
  25. 25.
    Kavitha GM, Kumar V (2013) Secure cloud storage with multi-cloud architecture. Int J Innov Technol Explor Eng 3:45–49Google Scholar
  26. 26.
    Bedi RK, Singh J et al (2016) Current Trends in Cloud Storage for Resource Constrained Mobile Devices. In: IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2016), pp 1187–1192Google Scholar
  27. 27.
    Bedi RK et al (2016) Analysis of Multi Cloud Storage applications for resource constrained mobile devices. J Perspect Sci 8:279–282CrossRefGoogle Scholar
  28. 28.
    Bedi RK, Singh J, Gupta SK (2017) Design and implementation of an efficient multi cloud storage approach for resource constrained mobile devices. Cluster Comput. Google Scholar
  29. 29.
    Luan T, Gao L (2016) Fog computing: focusing on mobile users at the edge, pp 10–11. arxiv:1502.01815
  30. 30.
    Slamanig D, Hanser C (2012) On Cloud Storage and Cloud of Clouds Approach. In: IEEE 7th International Conference on Internet Technology and Secure Transactions, London, December 10–12, pp 649–655Google Scholar
  31. 31.
    Wang S, Zhou J, Liu JK, Chen J, Yu J, Xie W (2016b) An efficient file hierarchy attribute-based encryption scheme in cloud computing. IEEE Trans Inf Forens Secur 11(6):1265–1277. CrossRefGoogle Scholar
  32. 32.
    Lounis A, Hadjidj A, Bouabdallah A, Challal Y (2016) Healing on the cloud: secure cloud architecture for medical wireless sensor networks. Future Gen Comput Syst 55:266–277. CrossRefGoogle Scholar
  33. 33.
  34. 34.
    Bedi RK et al (2016) Comparison of multi cloud storage systems for mobile devices. Int J Control Theory Appl 9(40):389–396Google Scholar
  35. 35.
    Chang R, Gao J (2013) Mobile Cloud Computing Research: Issues, Challenges, and Needs. In: IEEE 7th International Symposium on Service-Oriented System Engineering, Redwood City, pp 442–453Google Scholar
  36. 36.
    Wu L, Zhang Y, Li L, Shen J (2016) Efficient and anonymous authentication scheme for wireless body area networks. J Med Syst 40:134. CrossRefGoogle Scholar
  37. 37.
  38. 38.
  39. 39.
    MarketsandMarkets (2014) Mobile cloud market by application (gaming, entertainment, utilities, education, productivity, business and finance, social networking, healthcare, travel and navigation), and by user (enterprise user, consumer)—worldwide market forecast and analysis (2014–2019). http://goo.gI/ZF3aVE. Accessed August 2017
  40. 40.
    Rice A, Hay S (2010) Measuring mobile phone energy consumption for 802.11 wireless networking. Pervasive Mob Comput.
  41. 41.
    Rodrigo M, Ruben S, Foutse K, Francisco C, Giuliano A (2016) Anti-patterns and the energy efficiency of Android applicationsGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Rajeev Kumar Bedi
    • 1
    • 2
  • Jaswinder Singh
    • 1
  • Sunil Kumar Gupta
    • 2
  1. 1.Department of Computer EngineeringPunjabi UniversityPatialaIndia
  2. 2.Department of Computer Science and EngineeringBCETGurdaspurIndia

Personalised recommendations