The IoT Resource Allocation Improvement in Fog Computing Using Non-Cooperative Game Theory

Document Type : Original Article

Authors

1 Associate Professor, Department of Computer, Islamic Azad University, Boroujerd Branch, Boroujerd, Iran

2 Assistant Professor, Computer Department, Ayatollah Borujerdi University, Borujerd, Iran

Abstract

A modern architecture called fog computing is used in the IoT-based network systems. Providing data services is economical and low latent in the fog computing architecture. This paper addresses the main challenge of allocating computing resources in fog computing. Solving the resource allocation challenge leads to increased profits, economic savings, and optimal use of the computing systems. In this survey, resource allocation has been improved by using the combined Nash equilibrium algorithm and the auction algorithm. In the proposed method, each player is assigned a specific matrix. Each player’s matrix includes fog nodes, data service subscribers, and data service operators. At each stage of the algorithm, each player generates the best strategy based on the strategy of the other players. The results show the superiority of fog node utility and data service operator utility in the proposed method compared with the Stackelberg game algorithm. The first comparison is based on the changes of subscribers in which the productivity of the node with 240 used subscribers in the proposed method is 6852.8 whilst it is 5510.2 in the Stackelberg method with the same conditions. The second comparison is based on the service rate of the resource control blocks (μ) in which the productivity of the data service operator with μ=4 in the proposed method is 1.35E + 07 whilst it is 1E + 7 in the Stackelberg method with the same conditions .

Keywords


[1]  H. Zhang, Y. Xiao, S. Bu, D. Niyato, F. R. Yu, and Z. Han, "Computing resource allocation in three-tier IoT fog networks: A joint optimization approach combining Stackelberg game and matching," IEEE Internet of Things Journal, vol. 4, no. 5, pp. 1204-1215, 2017.
[2]  H. Zhang, Y. Xiao, S. Bu, D. Niyato, R. Yu, and Z. Han, "Fog computing in multi-tier data center networks: A hierarchical game approach," in 2016 IEEE international conference on communications (ICC), 2016: IEEE, pp. 1-6. 
[3]  Y. Cao, S. Chen, P. Hou, and D. Brown, "FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation," in 2015 IEEE international conference on networking, architecture and storage (NAS), 2015: IEEE, pp. 2-11. 
[4]  V. Stantchev, A. Barnawi, S. Ghulam, J. Schubert, and G. Tamm, "Smart items, fog and cloud computing as enablers of servitization in healthcare," Sensors & Transducers, vol. 185, no. 2, pp. 121-128, 2014.
[5]  J. K. Zao et al., "Augmented brain computer interaction based on fog computing and linked data," in 2014 International conference on intelligent environments, 2014: IEEE, pp. 374-377. 
[6]  J. Zhu, D. S. Chan, M. S. Prabhu, P. Natarajan, H. Hu, and F. Bonomi, "Improving web sites performance using edge servers in fog computing architecture," in 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering, 2013: IEEE, pp. 320-323. 
[7]  B. P. Rao, P. Saluia, N. Sharma, A. Mittal, and S. V. Sharma, "Cloud computing for Internet of Things & sensing based applications," in 2012 Sixth International Conference on Sensing Technology (ICST), 2012: IEEE, pp. 374-380. 
[8]  C. C. Byers and P. Wetterwald, "Fog computing distributing data and intelligence for resiliency and scale necessary for iot: The internet of things (ubiquity symposium)," Ubiquity, vol. 2015, no. November, pp. 1-12, 2015.
[9]  S. Agarwal, S. Yadav, and A. K. Yadav, "An architecture for elastic resource allocation in fog computing," Int. J. Comput. Sci. Commun, vol. 6, no. 2, pp. 201-207, 2015.
[10]         M. Aazam and E.-N. Huh, "Dynamic resource provisioning through fog micro datacenter," in 2015 IEEE international conference on pervasive computing and communication workshops (PerCom workshops), 2015: IEEE, pp. 105-110. 
[11]         A. Munir, P. Kansakar, and S. U. Khan, "IFCIoT: Integrated Fog Cloud IoT: A novel architectural paradigm for the future Internet of Things," IEEE Consumer Electronics Magazine, vol. 6, no. 3, pp. 74-82, 2017.
[12]         A. A. Alsaffar, H. P. Pham, C.-S. Hong, E.-N. Huh, and M. Aazam, "An architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing," Mobile Information Systems, vol. 2016, 2016.
[13]         A. Shahidinejad, "A Mutual Authentication Protocol for IoT Users in Cloud Environment," Electronic and Cyber Defense, 2021. (In Persian)
[14]         S. K. Roy and A. Bhaumik, "Intelligent water management: a triangular type-2 intuitionistic fuzzy matrix games approach," Water resources management, vol. 32, no. 3, pp. 949-968, 2018.
[15]         A. Bhaumik, S. K. Roy, and D.-F. Li, "Analysis of triangular intuitionistic fuzzy matrix games using robust ranking," Journal of Intelligent & Fuzzy Systems, vol. 33, no. 1, pp. 327-336, 2017.
[16]         A. Bhaumik, S. K. Roy, and G. W. Weber, "Hesitant interval-valued intuitionistic fuzzy-linguistic term set approach in Prisoners’ dilemma game theory using TOPSIS: a case study on Human-trafficking," Central European Journal of Operations Research, vol. 28, no. 2, pp. 797-816, 2020.
[17]         A. Bhaumik, S. K. Roy, and D.-F. Li, "(α, β, γ)-cut set based ranking approach to solving bi-matrix games in neutrosophic environment," Soft Computing, vol. 25, no. 4, pp. 2729-2739, 2021.
[18]         A. Bhaumik and S. K. Roy, "Intuitionistic interval-valued hesitant fuzzy matrix games with a new aggregation operator for solving management problem," Granular Computing, vol. 6, no. 2, pp. 359-375, 2021.
[19]         A. Bhaumik, S. K. Roy, and G. W. Weber, "Multi-objective linguistic-neutrosophic matrix game and its applications to tourism management," Journal of Dynamics & Games, vol. 8, no. 2, p. 101, 2021.
[20]         E.-S. Ammar, M. Brikaa, and E. Abdel-Rehim, "A study on two-person zero-sum rough interval continuous differential games," OPSEARCH, vol. 56, no. 3, pp. 689-716, 2019.
[21]         A. Mebrek and A. Yassine, "Intelligent Resource Allocation and Task Offloading Model for IoT Applications in Fog Networks: A Game-Theoretic Approach," IEEE Transactions on Emerging Topics in Computational Intelligence, 2021.
[22]         D. M. Khudhur, T. A. Yahiya, and P. Kirci, "Applying Game Theory Concept to Improve Resource Allocation in Mobile Edge Computing," in International Conference on Mobile Web and Intelligent Information Systems, 2021: Springer, pp. 108-118.
Volume 9, Issue 4 - Serial Number 36
Serial No. 36, Winter Quarterly
February 2022
Pages 147-158
  • Receive Date: 11 September 2021
  • Revise Date: 18 December 2021
  • Accept Date: 16 October 2021
  • Publish Date: 20 February 2022