There is a general consensus about the success of Internet architecture in academia and industry. However, with the development of diversified application, the existing Internet architecture is facing more and more challenges in scalability, security, mobility and performance. A novel evolvable Internet architecture framework is proposed in this paper to meet the continuous changing application requirements. The basic idea of evolvability is relaxing the constraints that limit the development of the architecture while adhering to the core design principles of the Internet. Three important design constraints used to ensure the construction of the evolvable architecture, including the evolvability constraint, the economic adaptability constraint and the manageability constraint, are comprehensively described. We consider that the evolvable architecture can be developed from the network layer under these design constraints. What's more, we believe that the address system is the foundation of the Internet. Therefore, we propose a general address platform which provides a more open and efficient network environment for the research and development of the evolvable architecture. 相似文献
A polycrystalline high-density magnesium fluoride, fabricated into plates or shapes by hot-pressing, exhibits high in-line transmittance from 2.5 to 6.0 m, and single-crystal magnesium fluoride extends from 0.1 to 6.0 m. The ultimate and practical transmittance of hot-pressed magnesium fluoride using intrinsic and extrinsic reflectance, absorptance and scattering mechanisms, are investigated. The intrinsic scattering mechanism due to the polycrystalline structure is basically responsible for the tremendous difference in transmittance in the short wavelength region of the spectrum. The in-line transmittance of polycrystalline and singlecrystal MgF2 is discussed in terms of sample thickness. 相似文献
Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.