Mobility-Aware Coded Probabilistic Caching Scheme for MEC-Enabled Small Cell Networks

Caching on the edge has been recognized as an effective solution to tackle the backhaul constraint of network densification. However, most related works ignored user mobility in wireless networks, which is unreasonable under the background of network densification. For a more flexible and context-aware caching decision, the concept of caching on the edge can be extended to mobile edge computing (MEC) that enables computation and storage resources at mobile edge networks. With MEC servers deployed on base stations, a huge amount of collected radio access network context data can be analyzed and utilized to render a caching scheme adaptive to user’s context-aware information. In this regard, a novel mobility-aware coded probabilistic caching scheme is proposed for MEC-enabled small cell networks (SCNs). Different from previous mobility-aware caching schemes, user mobility and distributed storage are incorporated into a conventional probabilistic caching scheme, with the aim of throughput maximization. Based on stochastic geometry theory and a modified mobility model of discrete random jumps, the explicit expression of throughput is derived. Due to the complexity of the expression, two light-weight heuristic algorithms are provided to numerically obtain the optimal solutions. Moreover, a significant trade-off among the gains of mobility diversity, content diversity, and channel selection diversity is discussed, and we further numerically analyze how such a trade-off is influenced by user mobility, content popularity, and backhaul capacity, with some fundamental insights into the application of the proposed scheme in MEC-enabled SCNs. The superiority of our proposed scheme is demonstrated by the comparisons with the classical M most popular caching scheme and the conventional probabilistic caching scheme. Numerical results show that our proposed caching scheme achieves higher throughput than those of the other two, especially when users of intense mobility request contents, of which the popularity profile is not skewed, in MEC-enabled SCNs with poor backhaul capacity, indicating that the proposed caching scheme is a promising solution for network densification.

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

[2]  Chedia Jarray,et al.  The effects of mobility on the hit performance of cached D2D networks , 2016, 2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[3]  Dong Liu,et al.  Caching at the wireless edge: design aspects, challenges, and future directions , 2016, IEEE Communications Magazine.

[4]  Ejaz Ahmed,et al.  A survey on mobile edge computing , 2016, 2016 10th International Conference on Intelligent Systems and Control (ISCO).

[5]  Jean-Yves Le Boudec,et al.  Power Law and Exponential Decay of Intercontact Times between Mobile Devices , 2007, IEEE Transactions on Mobile Computing.

[6]  Wan Choi,et al.  Caching Placement in Stochastic Wireless Caching Helper Networks: Channel Selection Diversity via Caching , 2016, IEEE Transactions on Wireless Communications.

[7]  Xing Zhang,et al.  Energy Efficiency Analysis of Heterogeneous Cache-Enabled 5G Hyper Cellular Networks , 2016, 2016 IEEE Global Communications Conference (GLOBECOM).

[8]  Alexandros G. Dimakis,et al.  Distributed Storage Allocations , 2010, IEEE Transactions on Information Theory.

[9]  Jun Rao,et al.  Optimal caching placement for D2D assisted wireless caching networks , 2015, 2016 IEEE International Conference on Communications (ICC).

[10]  Alexandros G. Dimakis,et al.  FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers , 2013, IEEE Transactions on Information Theory.

[11]  Alexandros G. Dimakis,et al.  FemtoCaching: Wireless video content delivery through distributed caching helpers , 2011, 2012 Proceedings IEEE INFOCOM.

[12]  Khaled Ben Letaief,et al.  Mobility-aware caching for content-centric wireless networks: modeling and methodology , 2016, IEEE Communications Magazine.

[13]  Seyed Pooya Shariatpanahi,et al.  Mobility increases throughput of wireless device-to-device networks with coded caching , 2016, 2016 IEEE International Conference on Communications (ICC).

[14]  Xing Zhang,et al.  A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications , 2017, IEEE Access.

[15]  Jiming Chen,et al.  Experimental analysis of user mobility pattern in mobile social networks , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[16]  Min Chen,et al.  Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks , 2016, Sensors.

[17]  Konstantinos Poularakis,et al.  Exploiting user mobility for wireless content delivery , 2013, 2013 IEEE International Symposium on Information Theory.

[18]  Hyunsoo Yoon,et al.  Analysis of Cell Sojourn Time in Heterogeneous Networks With Small Cells , 2016, IEEE Communications Letters.

[19]  Giuseppe Caire,et al.  Fundamental Limits of Caching in Wireless D2D Networks , 2014, IEEE Transactions on Information Theory.

[20]  Leonard J. Cimini,et al.  MobiCacher: Mobility-aware content caching in small-cell networks , 2014, 2014 IEEE Global Communications Conference.

[21]  Tony Q. S. Quek,et al.  Cooperative Caching and Transmission Design in Cluster-Centric Small Cell Networks , 2016, IEEE Transactions on Wireless Communications.

[22]  Pablo Rodriguez,et al.  I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system , 2007, IMC '07.

[23]  Ian F. Akyildiz,et al.  Mobility Management in Next Generation Wireless Systems , 1999, ICCCN.

[24]  Jeffrey G. Andrews,et al.  Femtocell networks: a survey , 2008, IEEE Communications Magazine.

[25]  Mohsen Guizani,et al.  5G wireless backhaul networks: challenges and research advances , 2014, IEEE Network.