Competitive caching of contents in 5G edge cloud networks

The surge of mobile data traffic forces network operators to cope with capacity shortage. The deployment of small cells in 5G networks shall increase radio access capacity. Mobile edge computing technologies can be used to manage dedicated cache memory at the edge of mobile networks. As a result, data traffic can be confined within the radio access network thus reducing latency, round-trip time and backhaul congestion. Such technique can be used to offer content providers premium connectivity services to enhance the quality of experience of their customers on the move. In this context, cache memory in the mobile edge network becomes a shared resource. We study a competitive caching scheme where contents are stored at a given price set by the mobile network operator. We first formulate a resource allocation problem for a tagged content provider seeking to minimize the expected missed cache rate. The optimal caching policy is derived accounting for popularity of contents, spatial distribution of small cells, and caching strategies of competing content providers. Next, we study a game among content providers in the form of a generalized non-smooth Kelly mechanism with bounded strategy sets and heterogeneous players. Existence and uniqueness of the Nash equilibrium are proved. Finally, numerical results validate and characterize the performance of the system.

[1]  Suhas N. Diggavi,et al.  Multi-level coded caching , 2014, 2014 IEEE International Symposium on Information Theory.

[2]  T. Başar,et al.  Dynamic Noncooperative Game Theory, 2nd Edition , 1998 .

[3]  T. Başar,et al.  Dynamic Noncooperative Game Theory , 1982 .

[4]  Richard T. B. Ma,et al.  Price differentiation and control in the Kelly mechanism , 2013, Perform. Evaluation.

[5]  Xiaofei Wang,et al.  Cache in the air: exploiting content caching and delivery techniques for 5G systems , 2014, IEEE Communications Magazine.

[6]  Donald F. Towsley,et al.  On the complexity of optimal routing and content caching in heterogeneous networks , 2014, 2015 IEEE Conference on Computer Communications (INFOCOM).

[7]  Suhas N. Diggavi,et al.  Effect of number of users in multi-level coded caching , 2015, 2015 IEEE International Symposium on Information Theory (ISIT).

[8]  R. Michael Buehrer,et al.  Learning distributed caching strategies in small cell networks , 2014, 2014 11th International Symposium on Wireless Communications Systems (ISWCS).

[9]  Yue Cao,et al.  QoE-Driven DASH Video Caching and Adaptation at 5G Mobile Edge , 2016, ICN.

[10]  H. Vincent Poor,et al.  A Learning-Based Approach to Caching in Heterogenous Small Cell Networks , 2015, IEEE Transactions on Communications.

[11]  Eitan Altman,et al.  Generalising diagonal strict concavity property for uniqueness of Nash equilibrium , 2016 .

[12]  Chung Gu Kang,et al.  Mobile device-to-device (D2D) content delivery networking: A design and optimization framework , 2014, Journal of Communications and Networks.

[13]  David Hung-Chang Du,et al.  Design a progressive video caching policy for video proxy servers , 2004, IEEE Transactions on Multimedia.

[14]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[15]  Ming Xiao,et al.  Efficient Video Pricing and Caching in Heterogeneous Networks , 2016, IEEE Transactions on Vehicular Technology.

[16]  L. Shapley,et al.  Potential Games , 1994 .

[17]  Eitan Altman,et al.  Game theory approach for modeling competition over visibility on social networks , 2014, 2014 Sixth International Conference on Communication Systems and Networks (COMSNETS).

[18]  Laszlo A. Belady,et al.  A Study of Replacement Algorithms for Virtual-Storage Computer , 1966, IBM Syst. J..

[19]  Giuseppe Caire,et al.  Fundamental limits of distributed caching in D2D wireless networks , 2013, 2013 IEEE Information Theory Workshop (ITW).

[20]  Mihaela van der Schaar,et al.  Popularity-driven content caching , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[21]  Tamer Basar,et al.  Efficient signal proportional allocation (ESPA) mechanisms: decentralized social welfare maximization for divisible resources , 2006, IEEE Journal on Selected Areas in Communications.

[22]  Ramesh Johari,et al.  Efficiency loss in market mechanisms for resource allocation , 2004 .

[23]  L. Shapley,et al.  REGULAR ARTICLEPotential Games , 1996 .

[24]  Mehdi Bennis,et al.  Living on the edge: The role of proactive caching in 5G wireless networks , 2014, IEEE Communications Magazine.

[25]  Jeffrey G. Andrews,et al.  What Will 5G Be? , 2014, IEEE Journal on Selected Areas in Communications.

[26]  Walid Saad,et al.  Cache-aware user association in backhaul-constrained small cell networks , 2014, 2014 12th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[27]  J. Goodman Note on Existence and Uniqueness of Equilibrium Points for Concave N-Person Games , 1965 .