, Volume 99, Issue 11, pp 1081–1104 | Cite as

OaaS: offload as a service in fog networks

  • Dai H. Tran
  • Nguyen H. Tran
  • Chuan PhamEmail author
  • S. M. Ahsan Kazmi
  • Eui-Nam Huh
  • Choong Seon Hong


Cloud computing is a mature technology that provides a huge leap in elastic computation, and new development trends are shaped to compliment the cloud computing paradigm. Cisco recently introduced the concept of Fog Computing to enable applications on billions of devices that are already connected and form the Internet of Things at the edge of the network. With the view point that the fog computing paradigm will be the future of computing technology, we look at its strong characteristics and propose a novel approach to enable a new kind of service called Offload As A Service (OaaS). Offload computation has been an active research area for many years and provides the capability to extend mobile resources limitations in terms of CPU, GPU, memory, storage and battery energy. Fog computing paradigm is a good synergy for offload computation technology with its low delay and close proximity features. To realize the enabling of OaaS in a fog computing environment, we propose a novel framework for communication and an offloading mechanism between different layers of the fog infrastructure, using matching algorithm to handle the fair mapping between users and service providers. Simulation results are provided to validate the effectiveness of our proposal. Simulation results of our work have shown great potential and value based on the prototype implementation, especially in the running time of tasks, which was reduced significantly with improvements of up to 37 and \(12\%\) observed for photos offloaded to “PC” and “Odroid”, respectively, compared to the local running time on the user device.


Fog computing Offloading services Cloud computing 

Mathematics Subject Classification

68R05 62P20 



This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (B0190-16-2017, Resilient/Fault-Tolerant Autonomic Networking Based on Physicality, Relationship and Service Semantic of IoT Devices).


  1. 1.
    Rimal BP, Choi Eunmi, Lumb I (2009) A taxonomy and survey of cloud computing systems. INC, IMS and IDC, 2009. NCM ’09. In: Fifth international joint conference on, vol., no., pp 44,51, 25–27Google Scholar
  2. 2.
    Gubbi J et al (2013) Internet of things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660CrossRefGoogle Scholar
  3. 3.
    Bonomi F (2011) Connected vehicles, the Internet of things, and fog computing. The Eighth ACM Int. Workshop on Vehicular Inter Networking VANET, Las Vegas, USAGoogle Scholar
  4. 4.
    Bahtovski A, Marjan G (2014) Cloudlet challenges. Proced Eng 69:704–711CrossRefGoogle Scholar
  5. 5.
    Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things. In: 1st ACM MCC Workshop on Mobile Cloud Computing, 13–16Google Scholar
  6. 6.
  7. 7.
    Cuervo E, Balasubramanian A, Cho D, Wolman A, Saroiu S, Chandra R, Bahl P (2010) MAUI: making smartphones last longer with code offload. In: International conferenceGoogle Scholar
  8. 8.
    Chun B-G, Ihm S, Maniatis P, Naik M, Patti A (2011) CloneCloud: elastic execution between mobile device and cloud. In: Proceedings of the sixth conference on Computer systems (EuroSys ’11). ACM, New York, NY, USA, 301–314Google Scholar
  9. 9.
    Kumar K, Liu J, Lu Y-H, Bhargava B (2013) A survey of computation offloading for mobile systems. Mob. Netw. Appl. 18(1):129–140CrossRefGoogle Scholar
  10. 10.
    Bertino E et al (2001) Author-: a java-based system for XML data protection. Data and application security. Springer, New York, pp 15–26zbMATHGoogle Scholar
  11. 11.
    oseph AD, de Lespinasse AF, Tauber JA, Gifford DK, Kaashoek MF (1995) Rover: a toolkit for mobile information access. In: ACM symposium on operating systems principles, pp 156–171Google Scholar
  12. 12.
    Adams K, Agesen O (2006) A comparison of software and hardware techniques for x86 virtualization. In: International conference on architectural support for programming languages and operating systems, pp 2–13Google Scholar
  13. 13.
    Barham P, Dragovic B, Fraser K, Hand S, Harris T, Ho A, Neugebauer R, Pratt I, Warfield A (2003) Xen and the art of virtualization. In: ACM symposium on operating systems principles, pp 164–177Google Scholar
  14. 14.
    Rosenblum M, Garfinkel T (2005) Virtual machine monitors: current technology and future trends. IEEE Comput 38(5):39–47CrossRefGoogle Scholar
  15. 15.
  16. 16.
    Flores H, Hui Pan, Tarkoma S, Yong Li, Srirama S, Buyya R (2015) Mobile code offloading: from concept to practice and beyond. Commun Mag IEEE 53(3):80–88CrossRefGoogle Scholar
  17. 17.
    Gandhewar N, Sheikh R (2010) Google android: an emerging software platform for mobile devices. Int J Comput Sci Eng 1(1):12–17Google Scholar
  18. 18.
    Asadi A, Mancuso V (2013) Wifi direct and lte d2d in action. Wireless Days (WD), 2013 IFIP. IEEEGoogle Scholar
  19. 19.
  20. 20.
    Roth AE (2008) Deferred acceptance algorithms: history, theory, practice, and open questions. Int J Game Theory 36(3–4):537–569MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Roth Alvin E (1985) The college admissions problem is not equivalent to the marriage problem. J Econ Theory 36(2):277–288, ISSN 0022-0531Google Scholar
  22. 22.
    Gusfield D, Irving RW (1989) The stable marriage problem: structure and algorithms. MIT Press, BostonzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Wien 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringKyung Hee UniversityYongin-siKorea

Personalised recommendations