Multi-Objective Virtual Network Embedding Algorithm Based on Global Resource Capacity
Zhen Li, Xiangwei Zheng, Yuang Zhang, Qingshui Xue · 2017
Network virtualization is a dynamic context leading to imbalance for substrate network (SN) resources which can affect the virtual network (VN) request further. In this paper, we propose the GRC-mopso-VNE algorithm to solve the VNE problem taking link resources into consideration in the stage of node mapping. A novel metric is developed, i.e., global resource capacity (GRC), to evaluate the mapping potential of each node. In the mapping process, we consider the vector GRC to accomplish node mapping and adopt the shortest path routing at link mapping. When virtual node request is rejected using this method, we take the multi-objective particle swarm optimization (MOPSO) algorithm into account at node mapping striving for the minimization of resource consumption and load balancing. Through the simulation, the proposed algorithm demonstrates better performance in terms of the VN acceptance ratio, long-term average cost and revenue comparing to G-SP, D-ViNE, R-ViNE and the GRC-VNE that only considers the GRC.