The distributed computing systems place greater demands on incremental state recognition， node consistency synchronization， and seamless service switching during continuous task running. However， the existing mechanisms still have limitations in awareness of cluster state structure， node consistency control， and controllable service version switching， which hinder stable service running under frequent state evolution. Therefore， Zynco was proposed， a lightweight and distributed framework for runtime state coevolution. Zynco was designed with three core mechanisms： a fingerprint-based and structure-aware incremental recognition mechanism， by which only effective state changes were transmitted and a sliding version chain was maintained； a feedback protocol combining User Datagram Protocol （UDP） multicast with Transmission Control Protocol （TCP） control channels， to achieve efficient distribution and acknowledgment of state among multiple nodes； a three-layer service structure with listener-based routing， thereby enabling smooth service switching and consistent rollback. Experimental results show that， in a 20-node cluster， Zynco requires only 27 s to complete state synchronization for incremental updates involving 54 GB of file data， without task interruption or state tearing during service switching； under a 1 000 QPS （Queries Per Second） load， Zynco has the response jitter time below 8 ms. It can be seen that Zynco is efficient， stable， controllable， and can provide good operational support for state?driven distributed high?performance services in massive?data collaborative update scenarios.

In order to meet the needs of tropospheric wireless communication system design and optimization, based on parabolic wave equation and Split Step Wavelet Method (SSWM), the tropospheric radio wave propagation characteristics were studied, and the wave propagation characteristic analysis software was developed. Fristly,a method for analyzing the tropospheric propagation characteristics based on split step wavelet method was presented by establishing a computation scene of numerical solution. Then, the tropospheric radio wave propagation characteristics analysis software was developed based on the proposed analysis method and Matlab.The numerical results show that the convergence of the proposed SSWM is better than that of Split Step Fourier Method (SSFM); tropospheric propagation loss is closely related to antenna height and elevation:the smaller the antenna elevation angle, the smaller the propagation loss; the larger the antenna height, the smaller the propagation loss; the propagation loss in an evaporation duct environment is smaller than that in the standard atmospheric environment. In addition, the developed analysis software has a user-friendly graphical user interface and is simple and flexible to operate.

Palm-dorsal vein recognition using Uniform Discrete Curvelet Transform （UDCT） was proposed in this paper. With the palm-dorsal Region Of Interest (ROI) extraction and image preprocessing, UDCT of the curvelet Transform was used on ROI. Then, the curvelet coefficients phase variance was encoded. Finally, the Chi-square distance of histogram of the coding was used for vein recognition. The experimental results show that this proposed method can identify palm-dorsal vein images with high robustness and high speed even with poor-quality images.