The rapid development of emerging vehicular edge computing (VEC) brings new opportunities and challenges for dynamic resource management. The increasing number of edge data centers, roadside units (RSUs), and network devices, however, makes resource management a complex task in VEC. On the other hand, the exponential growth of service applications and end-users makes corresponding QoS hard to maintain. Intent-Based Networking (IBN), based on Software-Defined Networking, was introduced to provide the ability to automatically handle and manage the networking requirements of different applications. Motivated by the IBN concept, in this paper, we propose a novel approach to jointly orchestrate networking and computing resources based on user requirements. The proposed solution constantly monitors user requirements and dynamically re-configures the system to satisfy desired states of the application. We compared our proposed solution with the state-of-the-art networking embedding algorithms using real-world taxi GPS traces. Results show that our proposed method is significantly faster (up to 95%) and can improve resource utilization (up to 76%) and the acceptance ratio of computing and networking requests with various priorities (up to 71%). We also present a small-scale prototype of the proposed intent management framework to validate our solution.
翻译:新兴智能边缘计算(VEC)的快速发展为动态资源管理带来了新的机遇和挑战。然而,越来越多的边缘数据中心、路侧单元(RSU)和网络设备使得VEC中的资源管理变得复杂。另一方面,服务应用程序和终端用户的指数级增长使得相应的QoS难以维护。基于软件定义网络的网络意图技术引入了智能网络动态管理的概念,为不同应用程序提供自动处理和管理网络需求的能力。本文提出了一种新颖的方法,根据用户需求联合编排网络和计算资源。所提出的解决方案不断监测用户需求,并动态重新配置系统以满足应用程序的期望状态。我们使用真实的出租车GPS跟踪数据,将我们提出的解决方案与现有的网络嵌入算法进行了比较。结果表明,我们提出的方法具有显著的速度优势(最高达95%),可以提高资源利用率(最高达76%),并且可以提高具有不同优先级的计算和网络请求的接受率(最高达71%)。我们还提供了一个小规模的原型来验证我们提出的意图管理框架。