Concerning the problem that traditional trajectory pattern mining methods have the problems of slow mining and large maximum amount of memory, a method of mining trajectory interval patterns based on spatial proximity searching was proposed. The implementation of the proposed method consists of five phases:1) Space-time discretization is performed on the trajectories, and space-time cell sequences corresponding to trajectories are achieved. 2) All the space-time cell sequences are scanned to get all no-duplication spatial cells, and all frequent spatial cells are obtained by the inclusion operation of the spatial cells and the cell sequences. 3) Frequent spatial cells are transformed into frequent interval patterns of length one. 4) Candidate interval patterns with the frequent spatial cells as units are generated by spatial proximity searching, and the support value of the candidate patterns are calculated by matching the patterns and the space-time cell sequences. 5) Based on the set support threshold, all frequent interval patterns are obtained. The experimental results show that the proposed method has the advantages of faster mining and less maximum amount of memory than traditional methods. Furthermore, in terms of running time, the proposed method has better stability and scalability performance than traditional methods. This method is helpful to the trajectory pattern mining methods to increase the mining speed and reduce the maximum amount of memory.

In the field of dense crowd scene, in order to improve the defects of present anomaly detection methods in real-time performance and applicability, a real-time method was proposed based on the optical flow feature and Kalman filtering. Firstly, the global optical flow value was extracted as the movement feature. Then the Kalman filtering was used to process the global optical flow value. The residual was analyzed based on the assumption that the residual obeyed a Gauss distribution in normal condition which was validated by the hypothesis testing. Then the parameter of the residual probability distribution was calculated through the Maximum Likelihood (ML) estimation. Finally, under a certain confidence coefficient level, the confidence interval of normal condition and the judgment formula of abnormal condition were obtained, which could be used to detect the abnormal events. The experimental result shows that, for the videos with the size of 320×240, the average detection time of the proposed method can be as low as 0.023 s/frame and the accuracy can reach above 95%. As a result, the proposed method has high detection efficiency and good real-time performance.

Large clusters have been developed to multicore era, and multicore architecture makes new demands on parallel computation. Message Passing Interface (MPI） is the most commonly used parallel programming model, and collective communications is an important part of the MPI standard. Efficient collective communications algorithm plays a vital role in improving the performance of parallel computation. This paper first analyzed the architecture features of KD60 and communication hierarchy characteristics under multicore architecture, and then introduced the implementation of collective communications algorithm in MPICH2 and pointed out its deficiencies. At last, this article took broadcasting as an example, using an improved algorithm based on CMP architecture，which changes the communication mode of the original algorithm. At the same time, this paper optimized the algorithm according to the architecture characteristics of KD60. The experimental results show that the improved algorithm improves the performance of broadcast in MPI.

In an open real-time system, the coexistence of different kinds of real-time and non real-time applications makes the system scheduling mechanism face new requirements and challenges. One scheduling mechanism of the open systems was introduced, and that the nonpreemptable sections may influence system schedulability in non real-time applications scheduling was pointed out. And then, a scheme which can remedy the limitations about the previous scheduling scheme was presented and the two-level scheduling scheme of open real-time system was improved. Ultimately, the schedulability of hard real-time applications, soft real-time applications and non real-time applications was guaranteed.