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An evolutionary game approach to IoT task offloading in fog-cloud computing

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Abstract

Developing the edge and fog computing has been the result of the fast growth of cloud-based IoT applications. These new paradigms define new resource management problems such as IoT task offloading challenge. Despite the many conducted effort in the IoT task offloading, this issue remains a research gap partly because this problem is NP-hard inherently, and also because many proposed solutions are based on unrealistic assumptions. Indeed, many proposed solutions suffer from the lack of a real set of tasks for a comprehensive evaluation. Thus, we prepare a collection of Python tasks to provide a realistic context for the assessment of the proposed task offloading methods. Also, this paper proposes a four-tier architecture to determine the specific decision-maker for the task offloading. Then, we formulate this problem as a population (evolutionary) game that is solved by Maynard replicator dynamics. The time and energy consumption are the main optimization objectives in this work. Finally, we simulate the proposed scheme in MATLAB by emphasizing the use of realistic values and parameters. The experimental results indicate that our scheme is a practical approach partly because it contributes to the core traffic decreases and because its convergence time is less than 6 s to solve the problem with 100 tasks.

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References

  1. 40 Internet of Things statistics from 2019 to justify the rise of IoT. https://techjury.net/stats-about/internet-of-things-statistics/. Accessed 06/17/2019

  2. What’s new with the internet of things? | mckinsey. https://www.mckinsey.com/industries/semiconductors/our-insights/whats-new-with-the-internet-of-things. Accessed 06/17/2019

  3. Zhang H, Xiao Y, Bu S, Niyato D, Yu FR, Han Z (2017) Computing resource allocation in three-tier IoT fog networks: a joint optimization approach combining Stackelberg game and matching. IEEE Internet Things J 4(5):1204

    Article  Google Scholar 

  4. Muñoz R, Vilalta R, Yoshikane N, Casellas R, Martínez R, Tsuritani T, Morita I (2018) Integration of IoT, transport SDN, and edge/cloud computing for dynamic distribution of IoT analytics and efficient use of network resources. J Lightwave Technol 36(7):1420

    Article  Google Scholar 

  5. Dastjerdi AV, Buyya R (2016) Fog computing: helping the internet of things realize its potential. Computer 49(8):112

    Article  Google Scholar 

  6. Schulz P, Matthe M, Klessig H, Simsek M, Fettweis G, Ansari J, Ashraf SA, Almeroth B, Voigt J, Riedel I et al (2017) Latency critical IoT applications in 5G: perspective on the design of radio interface and network architecture. IEEE Commun Mag 55(2):70

    Article  Google Scholar 

  7. Edge computing vs. fog computing: Definitions and enterprise uses—CISCO. https://www.cisco.com/c/en/us/solutions/enterprise-networks/edge-computing.html. Accessed 06/17/2019

  8. Adhinugraha K, Rahayu W, Hara T, Taniar D (2020) On internet-of-things (IoT) gateway coverage expansion. Future Gen Comput Syst 107:578

    Article  Google Scholar 

  9. Myerson R (2013) Game theory. Harvard University Press, Cambridge. https://books.google.com/books?id=oGUET9JBytEC

  10. Misra S, Saha N (2019) Detour: dynamic task offloading in software-defined fog for IoT applications. IEEE J Sel Areas Commun 37(5):1159

    Article  Google Scholar 

  11. Chen M, Hao Y (2018) Task offloading for mobile edge computing in software defined ultra-dense network. IEEE J Sel Areas Commun 36(3):587

    Article  Google Scholar 

  12. Chamola V, Tham CK, Chalapathi GS (2017) In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (IEEE 2017), pp 587–592

  13. Xu J, Ren S (2016) In: 2016 IEEE Global Communications Conference (GLOBECOM) (IEEE, 2016), pp 1–6

  14. Zhao X, Zhao L, Liang K (2016) In: International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness. Springer, Berlin, pp 293–301

  15. Ye D, Wu M, Tang S, Yu R (2016) In: 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud) (IEEE, 2016), pp 247–251

  16. Alam MGR, Tun YK, Hong CS (2016) In: 2016 International Conference on Information Networking (ICOIN) (IEEE, 2016), pp 285–290

  17. Liang K, Zhao L, Zhao X, Wang Y, Ou S (2016) Joint resource allocation and coordinated computation offloading for fog radio access networks. China Commun 13(Supplement2):131

    Article  Google Scholar 

  18. Tran DH, Tran NH, Pham C, Kazmi SA, Huh EN, Hong CS (2017) OaaS: offload as a service in fog networks. Computing 99(11):1081

    Article  MathSciNet  Google Scholar 

  19. Chiti F, Fantacci R, Picano B (2018) A matching theory framework for tasks offloading in fog computing for IoT systems. IEEE Internet Things J 5(6):5089

    Article  Google Scholar 

  20. Liu L, Chang Z, Guo X, Mao S, Ristaniemi T (2017) Multiobjective optimization for computation offloading in fog computing. IEEE Internet Things J 5(1):283

    Article  Google Scholar 

  21. Meng X, Wang W, Zhang Z (2017) Delay-constrained hybrid computation offloading with cloud and fog computing. IEEE Access 5:21355

    Article  Google Scholar 

  22. Khan JA, Westphal C, Ghamri-Doudane Y (2017) In: 2017 29th International Teletraffic Congress (ITC 29). IEEE, vol 1, pp 223–231

  23. Ahn S, Gorlatova M, Chiang M (2017) In: 2017 IEEE MIT Undergraduate Research Technology Conference (URTC). IEEE, pp 1–4

  24. Newton R, Toledo S, Girod L, Balakrishnan H, Madden S (2009) In: NSDI, vol 9, pp 395–408

  25. Bozorgchenani A, Tarchi D, Corazza GE (2017) In: 2017 International Symposium on Wireless Communication Systems (ISWCS). IEEE, pp 390–395

  26. Bozorgchenani A, Tarchi D, Corazza GE (2017) In: GLOBECOM 2017–2017 IEEE Global Communications Conference. IEEE, pp 1–6

  27. Zhu Q, Si B, Yang F, Ma Y (2017) Task offloading decision in fog computing system. China Commun 14(11):59

    Article  Google Scholar 

  28. Chang Z, Zhou Z, Ristaniemi T, Niu Z (2017) In: GLOBECOM 2017–2017 IEEE Global Communications Conference. IEEE, pp 1–6

  29. Bao W, Li W, Delicato FC, Pires PF, Yuan D, Zhou BB, Zomaya AY (2017) In: Proceedings of the 20th ACM International Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems. ACM, pp 99–108

  30. Mukherjee A, Deb P, De D, Buyya R (2018) C2OF2N: a low power cooperative code offloading method for femtolet-based fog network. J Supercomput 74(6):2412

    Article  Google Scholar 

  31. Wang X, Ning Z, Wang L (2018) Offloading in internet of vehicles: a fog-enabled real-time traffic management system. IEEE Trans Ind Inf 14(10):4568

    Article  Google Scholar 

  32. Liu L, Chang Z, Guo X (2018) Socially aware dynamic computation offloading scheme for fog computing system with energy harvesting devices. IEEE Internet Things J 5(3):1869

    Article  Google Scholar 

  33. Shah-Mansouri H, Wong VW (2018) Hierarchical fog-cloud computing for IoT systems: a computation offloading game. IEEE Internet Things J 5(4):3246

    Article  Google Scholar 

  34. Narahari Y (2014) Game theory and mechanism design, vol 4. World Scientific, Singapore

    Book  Google Scholar 

  35. Tadelis S (2013) Game theory: an introduction. Princeton University Press, Princeton

    MATH  Google Scholar 

  36. Osborne MJ, Rubinstein A (1994) A course in game theory. MIT Press, Cambridge

    MATH  Google Scholar 

  37. Mertens J, Sorin S, Zamir S (2015) Repeated games. Econometric society monographs. Cambridge University Press, Cambridge. https://books.google.com/books?id=AuYlBgAAQBAJ

  38. Chakravarty S, Mitra M, Sarkar P (2015) A course on cooperative game theory. Cambridge University Press, Cambridge. https://books.google.com/books?id=sp-TBQAAQBAJ

  39. Curiel I (2013) Cooperative game theory and applications: cooperative games arising from combinatorial optimization problems. Theory and decision library C . Springer, New York. https://books.google.com/books?id=BoXdBwAAQBAJ

  40. Nisan N, Roughgarden T, Tardos E, Vazirani V (2007) Algorithmic game theory. Cambridge University Press, Cambridge. https://books.google.com/books?id=YCu2alSw0w8C

  41. Easley D, Kleinberg J (2010) Networks, crowds, and markets: reasoning about a highly connected world. Cambridge University Press, Cambridge. https://books.google.com/books?id=atfCl2agdi8C

  42. Sandholm W (2010) Population games and evolutionary dynamics. Economic learning and social evolution. MIT Press, Cambridge. https://books.google.com/books?id=pZH6AQAAQBAJ

  43. Iot pet feeder—arduino project hub. https://create.arduino.cc/projecthub/circuito-io-team/iot-pet-feeder-10a4f3. Accessed 06/28/2019

  44. Truebench—linux cpu benchmarking system. https://truebench.the-toffee-project.org/index.php?page=home. Accessed 06/30/2019

  45. Kurose J, Ross K (2017) Computer networking: a top-down approach. Pearson, London. https://books.google.com/books?id=OljpOAAACAAJ

  46. Pdtoolbox\_matlab—file exchange—matlab central. https://www.mathworks.com/matlabcentral/fileexchange/. Accessed 07/11/2019

  47. Numpy—numpy. https://www.numpy.org/. Accessed 07/11/2019

  48. Statistics—mathematical statistics functions—python 3.7.4 documentation. https://docs.python.org/3/library/statistics.html. Accessed 07/11/2019

  49. Pydes pypi. https://pypi.org/project/pyDes/. Accessed 07/11/2019

  50. Hashlib—secure hashes and message digests—python 3.7.4 documentation. https://docs.python.org/3/library/hashlib.html. Accessed 07/11/2019

  51. Scikit-image: image processing in python—scikit-image. https://scikit-image.org/. Accessed 07/11/2019

  52. Home—scikit-video 1.1.11 documentation. http://www.scikit-video.org/stable/. Accessed 07/11/2019

  53. Azure latency test—azure speed test. http://www.azurespeed.com/. Accessed 07/14/2019

  54. Power consumption benchmarks | raspberry pi dramble. https://www.pidramble.com/wiki/benchmarks/power-consumption. Accessed 07/14/2019

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Authors and Affiliations

  1. Department of Computer Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran

    Hamidreza Mahini

  2. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Amir Masoud Rahmani

  3. Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Vietnam

    Amir Masoud Rahmani

  4. Department of Computer Science, Khazar University, Baku, Azerbaijan

    Amir Masoud Rahmani

  5. School of Computer Engineering, Iran University of Science and Technology (IUST), Tehran, Iran

    Seyyedeh Mobarakeh Mousavirad

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  1. Hamidreza Mahini
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  2. Amir Masoud Rahmani
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  3. Seyyedeh Mobarakeh Mousavirad
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Correspondence to Hamidreza Mahini.

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Mahini, H., Rahmani, A.M. & Mousavirad, S.M. An evolutionary game approach to IoT task offloading in fog-cloud computing. J Supercomput 77, 5398–5425 (2021). https://doi.org/10.1007/s11227-020-03484-8

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