Aiming at the problems of high time complexity, slow convergence speed and error-prone matching of low coverage point cloud registration, a point cloud registration algorithm based on region segmentation was proposed. Firstly, the volume integral invariant was used to calculate the concavity and convexity of points on the point cloud, and then the concavity and convexity feature point sets were extracted. Secondly, the regions of the feature points were partitioned by the segmentation algorithm based on the mixed manifold spectral clustering, and the regions were registered by the Iterative Closest Point (ICP) algorithm based on Singular Value Decomposition (SVD), so that the accurate registration of point clouds could be achieved. The experimental results show that the proposed algorithm can greatly improve the coverage of point clouds by region segmentation, and the optimal rotation matrix of rigid body transformation can be calculated without iteration. The algorithm has the registration accuracy increased by more than 10% and the registration time reduced by more than 20%. Therefore, the proposed algorithm can achieve fast and accurate registration of point clouds with low coverage.

In order to effectively master protocol interactive behavior, a method to automatically build protocol interactive process based on message sequence chart was proposed. Firstly, according to the characteristics of the protocol interactive process, the dependency graph was defined to represent the partial order of events in message sequence, and the network flows were converted to dependency graphs. Secondly, the basic message sequences were used to describe protocol interactive behavior fragments, and the basic message sequences were mined by defining event maximum suffix. Finally, the maximum dependency graphs that were found out were connected and merged to build a message sequence chart. The experimental results show that the proposed method has a high accuracy and the built message sequence chart can visually represent the protocol interactive process.

Protocol state machine can describe the behavior of a protocol, which can help to understand the behavior logic of protocol. Oriented towards text protocols, a statistical method was firstly used to extract the semantic keyword of representative message type, and an adjacency matrix was used to describe the sequential relationship between the message types, based on which the protocol states were labeled and a state transition diagram was built. The experimental results show that the method can accurately describe the sequential relationship between the message types and abstract state machine model accurately.

In order to meet the needs of modern society for weather forecast and early warning service, a real-time weather forecast and abnormal weather early warning system was researched and implemented in the Android system. Based on the decision tree algorithm of C4.5 algorithm, the warning classification problem was resolved. By means of extracting the attributes with maximum gain rate as the features of training sample, a decision tree was built. A model of decision tree was got by the pruning weather warning evaluation and analysis and application were made on this model. The experimental results show that this method has advantages in the assessment of classification accuracy, with correct classification rate up to 85.8%.

In the network performance measurement, location error is one of the main factors which influence the accurate network delay measurement. To reduce location error, an improved method for delay measurement was proposed based on Windows Network Driver Interface Specification (NDIS). By using this method, the timestamp position was removed from application to NDIS Intermediate Driver (ID) which was embedded between Miniport Driver (MD) and Protocol Driver (PD), and then the measurement program could calculate the network delay according to those timestamps. Compared with the traditional method, the experimental results show that the proposed method can nearly eliminate location error, and make sure the measurement standard deviation to be lowered than 10μs under different packet-lengths and host-loads. The improved measurement method does not need additional software and hardware, so it has lower measurement cost and can be applied widely.

The standard particle swarm optimization in the evolution formula only considers both the colony's best fitness value and the individual's fitness values. Therefore, it leads to the low accuracy of the convergence on account of being lack of the diversity in later evolution period. In order to improve the accuracy of the algorithm, the paper proposed the core master group particle swarm, and combined a core master group particle swarm with the improved formula. The improved algorithm is proved through experiments to be more accurate.

Low expandability and overweight of telecom backbone in mainstream P2P network model have been hampering the development of P2P system. Though structured overlay network model solves part of problems, it is difficult to be applied into Internet due to its limitations. By analyzing other P2P models, this paper provided a hybrid model based P2P network model, and described some important processes in the model. A manager protocol and new key matching algorithm were also proposed to enhance the management and practicability of P2P network.