Xiangang Zhao

A Parallelization Research for FY Satellite Rainfall Estimate Day Knock off Product Algorithm

With the development of satellite remote sensing technology, more and more requirements are put forward on the timeliness and stability of the satellite weather service system. The FY satellite rainfall estimate day knock off product algorithm runs longer, about 20 minutes, which affects the estimated rainfall product generated timeliness. Research and development of parallel optimization algorithms based on the needs of satellite meteorological services and their effectiveness in practical applications are necessary ways to enhance the high-performance and high-availability capabilities of satellite meteorological services. So aiming at this problem, we started the parallel algorithm research based on the analysis of precipitation estimation algorithm. Firstly, we explained the steps of precipitation estimated date knock off product algorithm; secondly, we analyzed the four main calculation module calculating the amount of algorithms; thirdly, multithreaded parallel algorithm and MPI parallelization was designed. Finally, the multithreaded parallel and MPI parallelization were realized. Experimental results show that the multithreaded parallel and MPI parallelization algorithm could greatly improve the overall degree of computational efficiency. And, MPI parallelization mode has a higher operating efficiency. The performance of parallel processing is closely related to the architecture of the computer. From the perspective of service scheduling and product algorithms, the MPI parallelization approach is adopted to achieve the purpose of improving service quality.

A Multitasking Run Time Prediction Method based on GBDT in Satellite Ground Application System

In satellite ground application system, it will cause resource constraints when running multiple tasks. To accurately measure out the task run time, this paper proposed a task running time estimation method based gradient boosting decision tree (GBDT). Firstly, according to various features of the time series variables classify applications. The predicted values are given for each node in the tree according to GBDT algorithm. Then through the establishment of multiple trees, the loss function is minimized. Finally, the most accurate predictions are calculated. After analysis, the proposed algorithm has a high accuracy ground.

A Cloud Computing Platform for FY-4 Based on Resource Scheduling Technology

In FY-4 satellite ground application system, Computer & network system (CNS) possesses computationally intensive, complex data structures, etc. To improve the overall efficiency of computing and storage performance of FY-4 system, we propose a cloud computing platform for FY-4 based on resource scheduling technology. We adopt a separate hierarchical scheduling design. The separation of operation scheduling and resource scheduling brings rich flexibility. The proposed cloud platform architecture of FY-4 including the infrastructure layer, the resource scheduling layer, the job scheduling bus layer and the application layer. In addition, the equipment selection and resource pooling design are presented.

A Resource Scheduling Method with Rough Set for Virtual Cluster

Virtual cluster is widely used in the satellite ground system, how to improve the efficiency of resource scheduling as the key to the entire system. This paper proposed a resource scheduling method with rough set for virtual cluster. Firstly, the resource domain of the target server is determined according to the rough set theory. Then, the rough set parameter calculation is performed on the server load. Finally, tasks are assigned by the importance of server load. Simulation results show that the proposed method can effectively improve the whole cluster resource utilization.

The Analysis Meteorological Satellite Software Based on Principal Component

How to provide reasonable hardware resources and improve the efficiency of soft-ware is paid more and more attention. In this paper, a set of software classification method based on software operating characteristics is proposed. The method uses software run-time resource consumption to describe the software running characteristics. Principal component analysis (PCA) is used to reduce the dimension of software running feature data and to interpret software characteristic information. Simulation results show that the proposed method can optimize the allocation of software hardware resources and improve the efficiency of software operation.

A Resource Mapping Method in Cloud-Based Satellite Ground System

The cloud-based computing platform of FY-meteorological satellite ground application system carried more and more tasks, which need to improve the efficiency of tasking virtual resource utilization within the limited system resources. When resource mapping mission, which not only need to consider the priority of the task, but also consider the relationship between resource needs and allocated resources. According to these characteristics requirements, this paper proposed a resource mapping method based on multi-priority coefficient. First, the definition of task weights were given, and the definition of task queue priority factors were given according to the task queuing time. Then, the correlation coefficient method was introduced to calculate the correlation coefficient between tasks required for processing resources and resource pool that can be allocated resources. Finally, task comprehensive priority measure were calculated according to the conditions of multi-resource mapping and the multipriority factors. Experimental results show that the proposed method can improve the cloud system resource utilization, and can meet the timely needs of multi-tasking.