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With the development of network virtualization technology,the deployment of service function chain in multi-domain network brings new challenges to the optimization of service function chain.The traditional deployment method usually optimizes a single target,which is not suitable for multi-objective optimization,and cannot measure and balance the weight among optimization targets.Therefore,in order to optimize the delay,network load balancing and acceptance rate of large-scale service function chain deployment requests synchronously,a data normalization processing scheme is proposed,and a two-step SFC deployment algorithm based on reinforcement learning is designed.The algorithm takes transmission delay and load balancing as feedback parameters and balances the weight relationship between them,and the SFC acceptance rate is optimized by using reinforcement learning framework simultaneously.The experimental results show that,the delay of the algorithm is reduced by 71.8% compared with LASP method,the acceptance rate is increased by 4.6% compared with MDSP method,and the average load balancing is increased by 39.1% compared with GREEDY method under the large-scale requests.The multi-objective optimization effect is guaranteed.

Aiming at the problem that it is difficult to quickly realize digital modeling due to the large number of parts of the full-pitch stacked winding of large-scale hydroelectric generators and the complex connection logic between the wire bars, this paper proposes a modeling method of full-pitch stacked winding of generators driven by connection logic. Firstly, based on 3D modeling software and the 3D visualization application engine platform, an interactive virtual component model library is constructed. Then, according to the electrical principle of the full-pitch stacked winding, the connection logic is converted into a two-dimensional sequence with clear relationship, so that the winding can be quickly visualized in the virtual scene. Finally, the logic driving model that can be quickly understood by the computer, auxiliary applications such as generator stator winding structure cognition and fault repair is designed. This method shortens the time to construct the 3D model of stator winding, and at the same time, the combination of clear hierarchical equipment tree and 3D visualization model and human-computer interaction interface helps operation and maintenance personnel quickly understand the complex structure of winding and its assembly relationship. [ABSTRACT FROM AUTHOR]

A survivability strategy based on CRDD（conditional risk disjunction degree） in multi-domain optical networks was provided in order to overcome the defect of the scalability constrained and provide differentiated service. The con- cept of CRDD was provided in this strategy, then the intra-domain virtual links reflection was achieved and the end-to-end work route and backup route to differentiate service reliability were computed with CRDD. The results show that the supported survivability strategy not only can differentiate the service reliability, reduce the blocking probability of service, but also can improve reliability for service requirement by 6.5% on average.