Abstract
To improve the user experience, an increasing number of mobile applications offload their computing tasks to servers with powerful computing capabilities. The fog radio access network (F-RAN) incorporates the concept of “fog computing” into the access network architecture, endowing an edge network with computing, storage, communication and control functions. In this paper, we consider a multiple fog access point (F-AP) and a multiuser F-RAN, where each user generates two different tasks: communication and computation. To satisfy the diverse quality of service requirements of different users, we jointly optimize the spectrum access, computation offloading and radio resource allocation. The problem is modeled as a mixed integer nonlinear programming problem, which is difficult to solve. In view of this, we propose a genetic algorithm based on convex optimization, i.e., the genetic convex optimization algorithm (GCOA), which divides the mixed integer nonlinear programming problem into two parts, i.e., optimization and convex optimization, to solve it in polynomial time. Simulation results are provided to verify the effectiveness of the algorithm.
Highlights
In the fifth generation (5G) mobile radio system, the rapid popularity of mobile terminals will greatly challenge the existing communication infrastructure and network topology [1]
Motivated by improving the quality of service of users, this paper jointly considers communication and computing resource allocation in the fog radio access network (F-RAN)
All users are directly connected to the BBU pool, all users access according to optimal channel conditions, and all computing tasks are offloaded to the BBU pool for computing, and all users access and calculate according to optimal channel conditions The tasks are all calculated in the fog access point (F-AP) node as three primary chromosomes, and the rest are randomly generated
Summary
In the fifth generation (5G) mobile radio system, the rapid popularity of mobile terminals will greatly challenge the existing communication infrastructure and network topology [1]. In [17], [18], and [19], the joint allocation of radio and computing resources to save time and energy when offloading tasks to the cloud was considered. Y. Ma et al.: Joint Allocation on Communication and Computing Resources for Fog Radio Access Networks and collaborative offloading methods in the F-RAN. References [26] and [27] considered the fog node cooperation mode and selected the appropriate number of fog nodes to perform user computing tasks on the premise of meeting the communication resource constraints. References [28] and [29] considered the optimization problem of minimizing the sum of the energy and delay consumed by offloading in the case of multiple users, a fog node and a cloud server.
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