Through researching and analyzing the management and maintenance problems in virtual router platform, a three-layer virtual router architecture including control plane, forwarding plane and resource management plane was put forward. Control plane and forwarding plane were two basic function planes in virtual router, correspondingly carrying logical control plane and logical forwarding plane. In order to achieve dynamic management of virtual router, resource management plane was introduced. Resource management plane was regarded as one important function plane, which was used to manage and configure virtual router. The structure and mechanism of resource management plane were mainly expressed, and a prototype system to support static installment and dynamic adjustment of router instances was carried out. The experimental results prove that the maximum processing ability of resource management plane is about 3205 strategies/second, and it can complete establishment of router instance within one second, which can meet management requirements of virtual router platforms.

To deal with weak edge, intensity inhomogeneity and low contrast that may appear in finger-vein images, a new segmentation algorithm based on even-symmetric Gabor filter and level set method was proposed. Firstly, the even-symmetric Gabor filter was used to filter the finger-vein image through 8 different orientations; secondly, finger-vein image based on the 8 filtered results was reconstructed to obtain the high quality image with significantly improved gray contrast between target and background; finally, the level set algorithm combining local features and global features was applied to segment finger-vein image. Compared with the level set algorithm proposed by Li, et al. (LI C, HUANG R, DING Z, et al. A variational level set approach to segmentation and bias correction of images with intensity inhomogeneity. MICCAI'08: Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II. Berlin: Springer, 2008: 1083-1091), and Legendre Level Set (L2S) algorithm, the percentage of Area Difference (AD) of the proposed algorithm decreased by 1.116% and 0.370% respectively, and the Relative Difference Degree (RDD) reduced by 1.661% and 1.379% respectively. The experimental results show that the proposed algorithm can achieve better results compared with traditional level set image segmentation algorithms that only consider local information or global information.