Resource Allocation for Information-Centric Virtualized Heterogeneous Networks With In-Network Caching and Mobile Edge Computing

Abstract

In order to better accommodate the dramatically increasing demand for data caching and computing services, storage and computation capabilities should be endowed to some of the intermediate nodes within the network, therefore increasing the data throughput and reducing the network operation cost. In this paper, we design a novel information-centric heterogeneous networks framework aiming at enabling content caching and computing. Furthermore, due to the virtualization of the whole system, communication, computing, and caching resources can be shared among all users associated with different virtual service providers. We formulate the virtual resource allocation strategy as a joint optimization problem, where the gains of not only virtualization but also caching and computing are taken into consideration in the proposed information-centric heterogeneous networks virtualization architecture. In addition, a distributed algorithm based on alternating direction method of multipliers is adopted in order to solve the formulated problem. Since each base station only needs to solve its own problem without exchange of channel state information by using the distributed algorithm, the computational complexity and signaling overhead can be greatly reduced. Finally, extensive simulations are presented to show the effectiveness of the proposed scheme under different system parameters.