Nowadays, while the demand for capacity continues to expand, the blossoming of Internet of Everything is bringing in a paradigm shift to new perceptions of communication networks, ushering in a plethora of totally unique services. To provide these services, Virtual Network Functions (VNFs) must be established and reachable by end-users, which will generate and consume massive volumes of data that must be processed locally for service responsiveness and scalability. For this to be realized, a solid cloud-network Integrated infrastructure is a necessity, and since cloud and network domains would be diverse in terms of characteristics but limited in terms of capability, communication and computing resources should be jointly controlled to unleash its full potential. Although several innovative methods have been proposed to allocate the resources, most of them either ignored network resources or relaxed the network as a simple graph, which are not applicable to Beyond 5G because of its dynamism and stringent QoS requirements. This paper fills in the gap by studying the joint problem of communication and computing resource allocation, dubbed CCRA, including VNF placement and assignment, traffic prioritization, and path selection considering capacity constraints as well as link and queuing delays, with the goal of minimizing overall cost. We formulate the problem as a non-linear programming model, and propose two approaches, dubbed B\&B-CCRA and WF-CCRA respectively, based on the Branch \& Bound and Water-Filling algorithms. Numerical simulations show that B\&B-CCRA can solve the problem optimally, whereas WF-CCRA can provide near-optimal solutions in significantly less time.

翻译：当前，在容量需求持续增长的同时，万物互联的蓬勃发展为通信网络的认知带来了范式转变，催生了一系列全新的服务。为了提供这些服务，需要建立虚拟网络功能（VNF）并使其能够被最终用户访问，这将产生并消耗海量数据，而这些数据必须在本地进行处理，以确保服务的响应性和可扩展性。要实现这一点，坚实的云网融合基础设施是必要的，由于云和网络域在特性上各不相同，且能力有限，因此需要联合控制通信与计算资源，以充分发挥其潜力。尽管已有多种创新方法被提出用于资源分配，但其中大多数要么忽略了网络资源，要么将网络简化为简单图，这些方法因5G演进网络的动态性和严格的QoS要求而不适用。本文通过研究通信与计算资源联合分配问题（称为CCRA），包括VNF放置与分配、流量优先级划分以及考虑容量约束、链路延迟和排队延迟的路径选择，以最小化总成本为目标填补了这一空白。我们将该问题建模为一个非线性规划模型，并基于分支定界（Branch & Bound）和注水算法（Water-Filling）分别提出了两种方法，即B&B-CCRA和WF-CCRA。数值仿真表明，B&B-CCRA能够最优地求解该问题，而WF-CCRA能够在显著更短的时间内提供近乎最优的解。