Abstract
As a promising technology, mobile edge computing (MEC) can provide an IT service environment and cloud-computing capabilities at the edge of the mobile network, and also can reduce latency, improve user experience. In this paper, we have proposed a MEC system consisting of one privately service provider (SP) and multiple mobile users (MU). A game theory approach for resource allocation optimization is proposed to analyze the interaction between the leader SP and the followers MUs. We have introduced the congestion factor between different MUs. In addition, we prove the existence of the Nash equilibrium (NE) by game theory method and design an efficient the best response (BR) algorithm to solve this problem. An optimal equilibrium strategy can be obtained by the BR algorithm, and experiment results have demonstrated the efficiency and feasibility of the algorithm.
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Dinh, T.Q., Tang, J., La, Q.D., Quek, T.Q.: Offloading in mobile edge computing: task allocation and computational frequency scaling. IEEE Trans. Commun. 65(8), 3571–3584 (2017)
Chen, Y., Zhang, N., Zhang, Y., Chen, X.: Dynamic computation offloading in edge computing for internet of things. IEEE Internet of Things J. 6(3), 4242–4251 (2019)
Wang, K., Yang, K., Magurawalage, C.S.: Joint energy minimization and resource allocation in C-RAN with mobile cloud. IEEE Trans. Cloud Comput. (TCC) 6(3), 760–770 (2017)
He, Y., Ren, J., Yu, G., Cai, Y.: Joint computation offloading and resource allocation in D2D enabled MEC networks. In: IEEE International Conference on Communications (ICC), pp. 1–6 (2019)
Cheng, K., Teng, Y., Sun, W., Liu, A., Wang, X.: Energy-efficient joint offloading and wireless resource allocation strategy in multi-MEC server systems. In: IEEE International Conference on Communications (ICC), pp. 1–6 (2018)
Hui, H., Zhou, C., An, X., Lin, F.: A new resource allocation mechanism for security of mobile edge computing system. IEEE Access 7, 116886–116899 (2019)
Sun, W., Liu, J., Yue, Y., Zhang, H.: Double auction-based resource allocation for mobile edge computing in industrial internet of things. IEEE Trans. Industr. Inf. 14(10), 4692–4701 (2018)
Han, D., Chen, W., Fang, Y.: A dynamic pricing strategy for vehicle assisted mobile edge computing systems. IEEE Wirel. Commun. Lett. 8(2), 420–423 (2018)
Gajic, V., Huang, J., Rimoldi, B.: Competition of wireless providers for atomic users. IEEE/ACM Trans. Netw. 22(2), 512–525 (2014)
Shen, F., Hamidouche, K., Bastug, E., Debbah, M.: A Stackelberg game for incentive proactive caching mechanisms in wireless networks. In: IEEE Global Communications Conference (GLOBECOM), pp. 1–6 (2016)
Zhao, K., Zhang, S., Zhang, N., Zhou, Y., Zhang, Y., Shen, X.: Incentive mechanism for cached-enabled small cell sharing: a Stackelberg game approach. In: IEEE Global Communications Conference (GLOBECOM), pp. 1–6 (2017)
Wu, B., Zeng, J., Ge, L., Tang, Y., Su, X.: A game-theoretical approach for energy-efficient resource allocation in MEC network. In: IEEE International Conference on Communications (ICC), pp. 1–6 (2019)
Liu, M., Liu, Y.: Price-based distributed offloading for mobile-edge computing with computation capacity constraints. IEEE Wirel. Commun. Lett. 7(3), 420–423 (2017)
Wan, X., Yin, J., Guan, X., Bai, G., Choi, B.Y.: A pricing based cost-aware dynamic resource management for cooperative cloudlets in edge computing. In: IEEE International Conference on Computer Communication and Networks (ICCCN), pp. 1–6 (2018)
Yang, S., Pan, L., Wang, Q., Liu, S.: To sell or not to sell: trading your reserved instances in Amazon EC2 marketplace. In: 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), pp. 939–948 (2018)
Zhang, M., Huang, J.: Mechanism design for network utility maximization with private constraint information. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp. 919–927 (2019)
Wang, C., Liang, C., Yu, F.R., Chen, Q., Tang, L.: Computation offloading and resource allocation in wireless cellular networks with mobile edge computing. IEEE Trans. Wireless Commun. 16(8), 4924–4938 (2017)
Zhang, J., Xia, W., Yan, F., Shen, L.: Joint computation offloading and resource allocation optimization in heterogeneous networks with mobile edge computing. IEEE Access 6, 19324–19337 (2018)
Acknowledgments
This work is partly supported by the National Natural Science Foundation of China (Nos. 61872044, 61902029), the Key Research and Cultivation Projects at Beijing Information Science and Technology University (No. 5211910958), the Supplementary and Supportive Project for Teachers at Beijing Information Science and Technology University (No. 5111911128), Beijing Municipal Program for Top Talent Cultivation (CIT & TCD201804055) and Qinxin Talent Program of Beijing Information Science and Technology University.
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Wu, B., Chen, X., Chen, Y., Li, Z. (2020). An Effective Resource Allocation Approach Based on Game Theory in Mobile Edge Computing. In: Zheng, Z., Dai, HN., Tang, M., Chen, X. (eds) Blockchain and Trustworthy Systems. BlockSys 2019. Communications in Computer and Information Science, vol 1156. Springer, Singapore. https://doi.org/10.1007/978-981-15-2777-7_31
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DOI: https://doi.org/10.1007/978-981-15-2777-7_31
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