Caching resource sharing in radio access networks: a game theoretic approach

Abstract

Deployment of caching in wireless networks has been considered an effective method to cope with the challenge brought on by the explosive wireless traffic. Although some research has been conducted on caching in cellular networks, most of the previous works have focused on performance optimization for content caching. To the best of our knowledge, the problem of caching resource sharing for multiple service provider servers (SPSs) has been largely ignored. In this paper, by assuming that the caching capability is deployed in the base station of a radio access network, we consider the problem of caching resource sharing for multiple SPSs competing for the caching space. We formulate this problem as an oligopoly market model and use a dynamic non-cooperative game to obtain the optimal amount of caching space needed by the SPSs. In the dynamic game, the SPSs gradually and iteratively adjust their strategies based on their previous strategies and the information given by the base station. Then through rigorous mathematical analysis, the Nash equilibrium and stability condition of the dynamic game are proven. Finally, simulation results are presented to show the performance of the proposed dynamic caching resource allocation scheme.

Keywords

Video caching / Oligopoly market / Game theory / Nash equilibrium / Stability analysis

References

[1] Agiza, H.N., Bischi, G.I., Kopel, M., 1999. Multistability in a dynamic Cournot game with three oligopolists. Math. Comput. Simul., 51(1-2):63–90.

[2] Ahlehagh, H., Dey, S., 2014. Video-aware scheduling and caching in the radio access network. IEEE/ACM Trans. Netw., 22(5):1444–1462.

[3] Arai, S., Fadlullah, Z.M., Ngo, T., , 2014. An efficient method for minimizing energy consumption of user equipment in storage-embedded heterogeneous networks. IEEE Wirel. Commun., 21(4):70–76.

[4] Bastug, E., Bennis, M., Debbah, M., 2014. Living on the edge: the role of proactive caching in 5G wireless networks. IEEE Commun. Mag., 52(8):82–89.

[5] Beyranvand, H., Lim, W., Maier, M., , 2015. Backhaulaware user association in FiWi enhanced LTE-A heterogeneous networks. IEEE Trans. Wirel. Commun., 14(6):2992–3003.

[6] Breslau, L., Cao, P., Fan, L., , 1999. Web caching and Zipf-like distributions: evidence and implications. Proc. IEEE INFOCOM Jointly with the 18th Annual Conf. of the IEEE Computer and Communications Societies, p.126–134.

[7] Cha, M., Kwak, H., Rodriguez, P., , 2009. Analyzing the video popularity characteristics of large-scale user generated content systems. IEEE/ACM Trans. Netw., 17(5):1357–1370.

[8] Chaudhry, M.T., Ling, T.C., Hussain, S.A., , 2015. Thermal-aware relocation of servers in green data centers. Front. Inform. Technol. Electron. Eng., 16(2): 119–134.

[9] Chuang, M.C., Chen, M.C., 2015. A mobile proxy architecture for video services over high-speed rail environments in LTE-A networks. IEEE Syst. J., 9(4):1264–1272.

[10] Ding, J., Huang, T., Liu, J., , 2015. Virtual network embedding based on real-time topological attributes. Front. Inform. Technol. Electron. Eng., 16(2):109–118.

[11] Dufwenberg, M., 2011. Game theory. Wiley Interdiscip. Rev. Cogn. Sci., 2(2):167–173.

[12] Erman, J., Gerber, A., Hajiaghayi, M., , 2011. To cache or not to cache: the 3G case. IEEE Internet Comput., 15(2):27–34.

[13] Golrezaei, N., Mansourifard, P., Molisch, A.F., , 2014. Base-station assisted device-to-device communications for high-throughput wireless video networks. IEEE Trans. Wirel. Commun., 13(7):3665–3676.

[14] Gu, J.X., Wang, W., Huang, A.P., , 2014. Distributed cache replacement for caching-enable base stations in cellular networks. Proc. IEEE Int. Conf. on Communications, p.2648–2653.

[15] Hamidouche, K., Saad, W., Debbah, M., 2014. Many-tomany matching games for proactive social-caching in wireless small cell networks. Proc. 12th Int. Symp. on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, p.569–574.

[16] Kelley, C., 2003. Solving Nonlinear Equations with Newton’s Method. Society for Industrial and Applied Mathematics.

[17] Kryftis, Y., Mavromoustakis, C.X., Mastorakis, G., , 2014. Resource usage prediction for optimal and balanced provision of multimedia services. Proc. IEEE 19th Int. Workshop on Computer Aided Modeling and Design of Communication Links and Networks, p.255–259.

[18] Lee, D., Choi, J., Kim, J.H., , 2001. LRFU: a spectrum of policies that subsumes the least recently used and least frequently used policies. IEEE Trans. Comput., 50(12):1352–1361.

[19] Liang, C., Yu, F.R., Zhang, X., 2015. Information-centric network function virtualization over 5G mobile wireless networks. IEEE Netw., 29(3):68–74.

[20] Liu, A., Lau, V., 2015. Exploiting base station caching in MIMO cellular networks: opportunistic cooperation for video streaming. IEEE Trans. Signal Process., 63(1): 57–69. 3

[21] Liu, J., Huang, T., Chen, J.Y., , 2011. A new algorithm based on the proximity principle for the virtual network embedding problem. J. Zhejiang Univ.-Sci. C (Comput. & Electron.), 12(11):910–918.

[22] Liu, Y.X., Li, K.L., Tang, Z., , 2015. Energy-aware scheduling with reconstruction and frequency equalization on heterogeneous systems. Front. Inform. Technol. Electron. Eng., 16(7):519–531.

[23] Malak, D., Al-Shalash, M., 2014. Optimal caching for deviceto-device content distribution in 5G networks. Proc. Globecom Workshops, p.863–868.

[24] Mavromoustakis, C.X., 2008. On the impact of caching and a model for storage-capacity measurements for energy conservation in asymmetrical wireless devices. Proc. 16th Int. Conf. on Software, Telecommunications and Computer Networks, p.243–247.

[25] Mavromoustakis, C.X., 2013. Mitigating file-sharing misbehavior with movement synchronization to increase endto-end availability for delay sensitive streams in vehicular P2P devices. Int. J. Commun. Syst., 26(12):1599–1616.

[26] Ming, Z.X., Xu, M.W., Wang, D., 2014. InCan: in-network cache assisted eNodeB caching mechanism in 4G LTE networks. Comput. Netw., 75(A):367–380.

[27] Nam, Y., Chung, J.M., 2015. Cooperative content delivery for cost minimization in wireless networks. Proc. 17th Asia-Pacific Network Operations and Management Symp. , p.566–568.

[28] Niyato, D., Hossain, E., 2007. A game-theoretic approach to competitive spectrum sharing in cognitive radio networks. Proc. IEEE Wireless Communications and Networking Conf. , p.16–20.

[29] Niyato, D., Hossain, E., 2008. Competitive spectrum sharing in cognitive radio networks: a dynamic game approach. IEEE Trans. Wirel. Commun., 7(7):2651–2660.

[30] Pedersen, H.A., Dey, S., 2014. Mobile device video caching to improve video QoE and cellular network capacity. Proc. 17th ACM Int. Conf. on Modeling, Analysis and Simulation of Wireless and Mobile Systems, p.103–107.

[31] Pedersen, H.A., Dey, S., 2016. Enhancing mobile video capacity and quality using rate adaptation, RAN caching and processing. IEEE/ACM Trans. Netw., 24(2):996–1010.

[32] Pingyod, A., Somchit, Y., 2014a. Content updating method in FemtoCaching. Proc. 11th Int. Joint Conf. on Computer Science and Software Engineering, p.123–127.

[33] Pingyod, A., Somchit, Y., 2014b. Rank-based content updating method in FemtoCaching. Proc. IEEE Region 10 Conf. , p.1–6.

[34] Sleator, D.D., Tarjan, R.E., 1985. Amortized efficiency of list update and paging rules. ACM Commun., 28(2):202–208.

[35] Sonis, M., 1996. Once more on Hénon map: analysis of bifurcations. Chaos Solit. Fract., 7(12):2215–2234.

[36] Wang, X.F., Chen, M., Taleb, T., , 2014. Cache in the air: exploiting content caching and delivery techniques for 5G systems. IEEE Commun. Mag., 52(2):131–139.

[37] Xie, R., Yu, F.R., Ji, H., 2012a. Dynamic resource allocation for heterogeneous services in cognitive radio networks with imperfect channel sensing. IEEE Trans. Veh. Technol., 61(2):770–780.

[38] Xie, R., Yu, F.R., Ji, H., , 2012b. Energy-efficient resource allocation for heterogeneous cognitive radio networks with femtocells. IEEE Trans. Wirel. Commun., 11(11):3910–3920.

[39] Xu, Y.M., Li, Y., Wang, Z.H., , 2014. Coordinated caching model for minimizing energy consumption in radio access network. Proc. IEEE Int. Conf. on Communications, p.2406–2411.

[40] Yang, C.C., Chen, Z.Y., Yao, Y., , 2014. Energy efficiency in wireless cooperative caching networks. Proc. IEEE Int. Conf. on Communications, p.4975–4980.

[41] Zhang, Y.D., Xu, X.J., Wang, X.L., , 2014. NC-COCA: network coding-based cooperative caching scheme. Proc. IEEE 17th Int. Conf. on Computational Science and Engineering, p.976–980.

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Zhejiang University and Springer-Verlag Berlin Heidelberg