A resource optimization method in Internet of Vehicles network based on non-orthogonal multiple access

Abstract

The present invention relates to the field of resource optimization in the Internet of Vehicles network, in particular to a resource optimization method for the Internet of Vehicles network based on non-orthogonal multiple access technology. When processing vehicle tasks in the vehicle edge computing system assisted by NOMA, the vehicle edge computing The principle of minimizing the total energy consumption of the system is to determine the system's unloading and caching decisions, and the allocation of computing and caching resources, that is, considering the random traffic arrival of vehicle users and queue stability, computing unloading decisions and content caching decisions through joint optimization, and The allocation of computing and cache resources is defined as a stochastic optimization problem; using Lyapunov optimization theory, a dynamic joint computing offloading, content caching, and resource allocation algorithm is proposed to solve this problem, and it is decoupled into two independent sub-problems. Using 0-1 integer programming and linear programming to solve two sub-problems; the invention can effectively handle computing resources of mobile edge computing servers and reduce system energy consumption.

Description

technical field [0001] The invention relates to the field of resource optimization in the Internet of Vehicles network, in particular to a resource optimization method in the Internet of Vehicles network based on non-orthogonal multiple access. Background technique [0002] With the rapid development of the Internet of Things and the increasing popularity of computing-intensive mobile applications, existing mobile user equipment cannot meet the corresponding challenges in terms of application processing or energy supply. At the same time, driven by mobile video, online social media, etc., big data traffic is increasing exponentially, making mobile networks face computational constraints. Although the wireless spectrum has been fully utilized by, for example, ultra-dense networks, the backhaul may become a new bottleneck, unable to bear the huge business traffic. Future wireless networks are expected to support a host of computationally intensive and latency-sensitive applic...

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