C-RAN架构下一种基于分形定理的载波迁移预测算法

作为C-RAN关键技术之一的实时虚拟化技术要求实现硬件处理资源的虚拟化管理,实现物理资源的动态分配和负载均衡,保证虚拟基站的实时性,处理时延和抖动可控。为提高物理资源的动态分配和负载均衡的效率,在传统虚拟机迁移策略基础上结合分形理论,提出一种动态载波迁移预测算法,避免了因瞬时负载峰值触发载波迁移而带来不必要的迁移开销。该算法通过对物理资源负载离散历史数据进行分形拼贴拟合出完整负载曲线,然后根据分形维度不变性实现对未来数据的预测。为实现对该算法的仿真,结合C-RAN的系统架构搭建了一个基于并行离散事件仿真(parallel discrete event simulation PDES)的验证平台,仿真结果表明该算法能在有效减少虚拟基站迁移次数的同时确保达到负载均衡的目的。

A Fractal Theorem Based on Prediction Algorithm for Carrier Migration Application in C-RAN Architecture

As one of the key technologies of C-RAN, the Real-Time-Virtualization ask for virtual management of hardware resources to implement the dynamic allocation of physical resources and load balancing, and ensure the real-time performance of virtual base station, processing delay and jitter controllable. Taking the burst and transient load in the C-RAN centralized access network system, we can improve the effectiveness of the migration algorithm to reduce unnecessary migrations. To achieve this goal, we propose a method to detect the potential overload points, which combined with traditional virtual machine migration and fractal theory. The simulation results show that this method has high prediction accuracy, which can effectively reduce the number of migration of virtual base station and ensure the load balance at the same time.