The three primary colors of mobile systems

In this article, we present the notion of "mobile 3C systems" in which communications, computing, and caching (i.e., 3C) make up the three primary resources/functionalities, akin to the three primary colors, of a mobile system. We argue that in future mobile networks, the roles of computing and caching are as intrinsic and essential as communications, and only the collective usage of these three primary resources can support the sustainable growth of mobile systems. By defining the 3C resources in their canonical forms, we reveal the important fact that caching affects the mobile system performance by introducing non-causality into the system, whereas computing achieves capacity gains by performing logical operations across mobile system entities. Many existing capacity-enhancing techniques such as coded multicast, collaborative transmissions, and proactive content pushing can be cast in the native 3C framework for analytical tractability. We further illustrate the mobile 3C concepts with practical examples, including a system on broadcast-unicast convergence for massive media content delivery. The mobile 3C design paradigm opens up new possibilities as well as key research problems bearing academic and practical significance.

[1]  Panganamala Ramana Kumar,et al.  Computing and communicating functions over sensor networks , 2005, IEEE Journal on Selected Areas in Communications.

[2]  Wen Tong,et al.  Enabling technologies for 5G air-interface with emphasis on spectral efficiency in the presence of very large number of links , 2015, 2015 21st Asia-Pacific Conference on Communications (APCC).

[3]  Geng Wu,et al.  5G Network Capacity: Key Elements and Technologies , 2014, IEEE Vehicular Technology Magazine.

[4]  Martin Hilbert,et al.  The World’s Technological Capacity to Store, Communicate, and Compute Information , 2011, Science.

[5]  Wei Yu,et al.  Multi-Cell MIMO Cooperative Networks: A New Look at Interference , 2010, IEEE Journal on Selected Areas in Communications.

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

[7]  Urs Niesen,et al.  Fundamental limits of caching , 2012, 2013 IEEE International Symposium on Information Theory.

[8]  Arogyaswami Paulraj,et al.  MIMO channel capacity for the distributed antenna , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[9]  Rudolf Ahlswede,et al.  Network information flow , 2000, IEEE Trans. Inf. Theory.

[10]  Hui Liu,et al.  Push-Based Wireless Converged Networks for Massive Multimedia Content Delivery , 2014, IEEE Transactions on Wireless Communications.

[11]  Nikos Fotiou,et al.  A Survey of Information-Centric Networking Research , 2014, IEEE Communications Surveys & Tutorials.

[12]  Xinbing Wang,et al.  On content-centric wireless delivery networks , 2014, IEEE Wireless Communications.

[13]  Zhisheng Niu,et al.  TANGO: traffic-aware network planning and green operation , 2011, IEEE Wireless Communications.

[14]  Robert G. Gallager,et al.  Finding parity in a simple broadcast network , 1988, IEEE Trans. Inf. Theory.

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