Distributed caching in 5G networks: An Alternating Direction Method of Multipliers approach

International audience—We consider the problem of distributed caching in next generation mobile cellular networks (a.k.a., 5G) where densely-deployed small base stations (SBSs) are able to store and deliver users' content accordingly. In particular, we formulate the optimal cache allocation policy as a convex optimization problem where a subset of SBSs have their own i) local cost function which captures backhaul consumption aspects in terms of bandwidth and ii) a set of local network parameters and storage constraints. Given the fact that no coordination involves between SBSs, we then solve this problem distributively using the Alternating Direction Method of Multipliers (ADMM) approach. The proposed ADMM-based algorithm relies on the application of random Gauss-Seidel iterations on the Douglas-Rachford splitting operator, which results in a low-complexity and easy-to-implement solution for SBSs. We examine the convergence of our proposed algorithm via numerical simulations with different parameters of interest such as storage capacity distribution of SBSs, content catalogue size, demand intensity and demand shape. Our numerical results show that the proposed algorithm performs well in terms of convergence and requires less iterations as the number of contents in the catalogue increases

Breaking the Economic Barrier of Caching in Cellular Networks: Incentives and Contracts

In this paper, a novel approach for providing incentives for caching in small cell networks (SCNs) is proposed based on the economics framework of contract theory. In this model, a mobile network operator (MNO) designs contracts that will be offered to a number of content providers (CPs) to motivate them to cache their content at the MNO's small base stations (SBSs). A practical model in which information about the traffic generated by the CPs' users is not known to the MNO is considered. Under such asymmetric information, the incentive contract between the MNO and each CP is properly designed so as to determine the amount of allocated storage to the CP and the charged price by the MNO. The contracts are derived by the MNO in a way to maximize the global benefit of the CPs and prevent them from using their private information to manipulate the outcome of the caching process. For this interdependent contract model, the closed-form expressions of the price and the allocated storage space to each CP are derived. This proposed mechanism is shown to satisfy the sufficient and necessary conditions for the feasibility of a contract. Moreover, it is shown that the proposed pricing model is budget balanced, enabling the MNO to cover all the caching expenses via the prices charged to the CPs. Simulation results show that none of the CPs will have an incentive to choose a contract designed for CPs with different traffic loads.Comment: Accepted for publication at Globecom 201

The edge cloud: A holistic view of communication, computation and caching

The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth generation (5G) communication networks. This ambitious goal requires a paradigm shift towards a vision that looks at communication, computation and caching (3C) resources as three components of a single holistic system. The further step is to bring these 3C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing: Principles and Applications", P. Djuric and C. Richard Eds., Academic Press, Elsevier, 201