Resource Allocation in Software Defined Fog Vehicular Networks

Yaomin Zhang, Haijun Zhang, Keping Long, Xiaoming Xie, Victor C. M. Leung
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引用次数: 10

Abstract

Vehicular network is an important application scenario of the fifth generation (5G) mobile communications. Due to the increasing number of vehicles and the users' various requirements, resource allocation problem in vehicular networks becomes more serious and has attracted researchers' attention. In this paper, we investigate the resource allocation in software defined fog vehicular networks where we formulate the problem as a mean-field game (MFG). We present a state space function by considering both interference factors and energy availability. Then the problem can be modeled as a cost minimization with the constraint of state space. Through the mean-field approximation method, we derive the corresponding Hamilton-Jacobi-Bellman (HJB) and Fokker-Planck-Kolmogorov (FPK) equations. A joint finite difference algorithm is proposed to solve the coupled HJB and FPK equations. The numerical results are presented to show the effectiveness of the proposed algorithm.
软件定义雾车网络中的资源分配
车联网是第五代(5G)移动通信的重要应用场景。由于车辆数量的增加和用户需求的多样化,车联网中的资源分配问题日益严重,引起了研究者的关注。在本文中,我们研究了软件定义雾车网络中的资源分配问题,我们将问题表述为平均场博弈(MFG)。我们提出了一个同时考虑干扰因素和能量可用性的状态空间函数。然后将该问题建模为具有状态空间约束的成本最小化问题。通过平均场近似方法,导出了相应的Hamilton-Jacobi-Bellman (HJB)方程和Fokker-Planck-Kolmogorov (FPK)方程。提出了一种求解耦合HJB和FPK方程的联合有限差分算法。数值结果表明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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