基于知识描述和遗传算法的跨域虚拟网络映射

摘要

In a network virtualization environment, multi-domain virtual network embedding (MVNE) deals with properly partitioning a virtual network (VN) request into sub-VN requests across multiple domains for embedding with the aim of minimizing the embedding cost. Resource matching and VN partitioning are two key phases in MVNE. However, a resource matching algorithm capable of providing accurate numerical attribute matching and VN users’ diversified mapping constraints specification has not been explicitly studied by the existing research. Moreover, an efficient solution is needed for MVNE which is NP-hard. This paper provides an OWL and SWRL based resource matching algorithm and a genetic algorithm based VN partitioning algorithm to tackle the problems mentioned above. The correctness of the presented method is proved by theoretical analysis, and the validity of the method is assessed by simulation experiments in terms of efficiency, performance, and stability.%网络虚拟化环境下的跨域虚拟网络映射是指当物理网络由多个自治域构成时，以最小化虚拟网络映射开销为目标，将虚拟网络请求恰当地划分为多个虚拟子网请求，并分别指派给相应自治域以完成映射。资源匹配和虚拟网络划分是跨域虚拟网络映射中的两个关键阶段。然而，现有的资源匹配算法无法支持精确的数值属性匹配，也无法满足虚拟网络用户对表达多样化映射约束的需求，故实用性不高。此外，虚拟网络划分属于NP问题，目前也缺乏高效的求解方法。针对上述两个阶段中存在的问题，分别提出了基于OWL及SWRL的资源匹配算法和基于遗传算法的虚拟网络划分算法。理论分析证明了该方法的正确性。仿真实验从效率、性能及稳定性方面验证了该方法的有效性。