Cognitive-Caching: Cognitive Wireless Mobile Caching by Learning Fine-Grained Caching-Aware Indicators

Caching content on mobile devices reduces not only the transmission of backhaul links but also the latency of content acquisition. However, in the existing caching schemes, the joint effect of the caching-aware indicator of users and content dimensions on the caching strategy is not considered. Thus, how to learn fine-grained caching- aware indicators and design caching schemes are still challenging issues. In order to solve these problems, in this article, we first propose the cognitive caching architecture and give the fine-grained caching-aware indicators metric. Then we design a cognitive caching scheme that includes what to do in cognitive caching and how to do cognitive caching. Finally, experimental results show that the proposed cognitive caching scheme is superior to other caching schemes in terms of learning regret and caching cost.

[1]  Jun Zhang,et al.  Exploiting Mobility in Cache-Assisted D2D Networks: Performance Analysis and Optimization , 2018, IEEE Transactions on Wireless Communications.

[2]  Marco Di Renzo,et al.  Optimal Cache Leasing from a Mobile Network Operator to a Content Provider , 2018, IEEE INFOCOM 2018 - IEEE Conference on Computer Communications.

[3]  Dario Pompili,et al.  Cooperative Hierarchical Caching and Request Scheduling in a Cloud Radio Access Network , 2018, IEEE Transactions on Mobile Computing.

[4]  Donald F. Towsley,et al.  The Role of Caching in Future Communication Systems and Networks , 2018, IEEE Journal on Selected Areas in Communications.

[5]  Min Chen,et al.  Opportunistic Task Scheduling over Co-Located Clouds in Mobile Environment , 2018, IEEE Transactions on Services Computing.

[6]  Yajun Wang,et al.  Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms , 2014, J. Mach. Learn. Res..

[7]  Ning Zhang,et al.  Content Popularity Prediction Towards Location-Aware Mobile Edge Caching , 2018, IEEE Transactions on Multimedia.

[8]  Xianfu Chen,et al.  SoftMobile: control evolution for future heterogeneous mobile networks , 2014, IEEE Wireless Communications.

[9]  Min Chen,et al.  Green and Mobility-Aware Caching in 5G Networks , 2017, IEEE Transactions on Wireless Communications.

[10]  Di Yuan,et al.  Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches , 2017, IEEE Transactions on Wireless Communications.

[11]  Shahid Mumtaz,et al.  Energy-Efficient Stable Matching for Resource Allocation in Energy Harvesting-Based Device-to-Device Communications , 2017, IEEE Access.

[12]  Peter Auer,et al.  Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.

[13]  Anja Klein,et al.  Context-Aware Proactive Content Caching With Service Differentiation in Wireless Networks , 2016, IEEE Transactions on Wireless Communications.

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