Map data display is the basic information representation mode under embedded real-time navigation. After a navigation display data set （NDIS_SET） with several dimensions and corresponding mathematical description fo...Map data display is the basic information representation mode under embedded real-time navigation. After a navigation display data set （NDIS_SET） with several dimensions and corresponding mathematical description formula are designed, a series of rules and algorithms are advanced to optimize embedded navigation data and promote data index and input efficiency. A new parallel display algorithm with navigation data named N PDIS is then presented to adapt to limited embedded resources of computation and memory after a normal navigation data display algorithm named NDIS and related problems are analyzed, N_PDIS can synchronously create two preparative bitmapa by two parallel threads and switch one of them to screen automatically. Compared with NDIS, the results show that N_PDIS is more effective in improving display efficiency.展开更多
A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on t...A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on the improved Hilbert curve, the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases. Thus, the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.展开更多
To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the sch...To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.展开更多
Mining association rules from large database is very costly. We develop a parallel algorithm for this task on shared-memory multiprocessor (SMP). Most proposed parallel algorithms for association rules mining have to ...Mining association rules from large database is very costly. We develop a parallel algorithm for this task on shared-memory multiprocessor (SMP). Most proposed parallel algorithms for association rules mining have to scan the database at least two times. In this article, a parallel algorithm Scan Once (SO) has been proposed for SMP, which only scans the database once. And this algorithm is fundamentally different from the known parallel algorithm Count Distribution (CD). It adopts bit matrix to store the database information and gets the support of the frequent itemsets by adopting Vector-And-Operation, which greatly improve the efficiency of generating all frequent itemsets. Empirical evaluation shows that the algorithm outperforms the known one CD algorithm.展开更多
Task scheduling determines the performance of NOW computing to a large extent. However, the computer system architecture, computing capability and system load are rarely proposed together. In this paper, a biggest het...Task scheduling determines the performance of NOW computing to a large extent. However, the computer system architecture, computing capability and system load are rarely proposed together. In this paper, a biggest heterogeneous scheduling algorithm is presented. It fully considers the system characteristics (from application view), structure and state. So it always can utilize all processing resource under a reasonable premise. The results of experiment show the algorithm can significantly shorten the response time of jobs.展开更多
In order to solve the bottleneck problem of the traditional K-Medoids clustering algorithm facing to deal with massive data information at the time of memory capacity and processing speed of CPU, the paper proposed a ...In order to solve the bottleneck problem of the traditional K-Medoids clustering algorithm facing to deal with massive data information at the time of memory capacity and processing speed of CPU, the paper proposed a parallel algorithm MapReduce programming model based on the research of K-Medoids algorithm. This algorithm increase the computation granularity and reduces the communication cost ratio based on the MapReduce model. The experimental results show that the improved parallel algorithm compared with other algorithms, speedup and operation efficiency is greatly enhanced.展开更多
文摘Map data display is the basic information representation mode under embedded real-time navigation. After a navigation display data set （NDIS_SET） with several dimensions and corresponding mathematical description formula are designed, a series of rules and algorithms are advanced to optimize embedded navigation data and promote data index and input efficiency. A new parallel display algorithm with navigation data named N PDIS is then presented to adapt to limited embedded resources of computation and memory after a normal navigation data display algorithm named NDIS and related problems are analyzed, N_PDIS can synchronously create two preparative bitmapa by two parallel threads and switch one of them to screen automatically. Compared with NDIS, the results show that N_PDIS is more effective in improving display efficiency.
基金Funded by the National 863 Program of China （No. 2005AA113150）, and the National Natural Science Foundation of China （No.40701158）.
文摘A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data items. Based on the improved Hilbert curve, the algorithm can be designed to achieve almost-uniform spatial data partitioning among multiple disks in parallel spatial databases. Thus, the phenomenon of data imbalance can be significantly avoided and search and query efficiency can be enhanced.
基金supported by the National Grand Fundamental Research of China (973 Program) under Grant No. 2011CB302601the National High Technology Research and Development of China (863 Program) under GrantNo. 2013AA01A213+2 种基金the National Natural Science Foundation of China under Grant No. 60873215the Natural Science Foundation for Distinguished Young Scholars of Hunan Province under Grant No. S2010J5050Specialized Research Fund for the Doctoral Program of Higher Education under Grant No. 20124307110015
文摘To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.
文摘Mining association rules from large database is very costly. We develop a parallel algorithm for this task on shared-memory multiprocessor (SMP). Most proposed parallel algorithms for association rules mining have to scan the database at least two times. In this article, a parallel algorithm Scan Once (SO) has been proposed for SMP, which only scans the database once. And this algorithm is fundamentally different from the known parallel algorithm Count Distribution (CD). It adopts bit matrix to store the database information and gets the support of the frequent itemsets by adopting Vector-And-Operation, which greatly improve the efficiency of generating all frequent itemsets. Empirical evaluation shows that the algorithm outperforms the known one CD algorithm.
文摘Task scheduling determines the performance of NOW computing to a large extent. However, the computer system architecture, computing capability and system load are rarely proposed together. In this paper, a biggest heterogeneous scheduling algorithm is presented. It fully considers the system characteristics (from application view), structure and state. So it always can utilize all processing resource under a reasonable premise. The results of experiment show the algorithm can significantly shorten the response time of jobs.
文摘In order to solve the bottleneck problem of the traditional K-Medoids clustering algorithm facing to deal with massive data information at the time of memory capacity and processing speed of CPU, the paper proposed a parallel algorithm MapReduce programming model based on the research of K-Medoids algorithm. This algorithm increase the computation granularity and reduces the communication cost ratio based on the MapReduce model. The experimental results show that the improved parallel algorithm compared with other algorithms, speedup and operation efficiency is greatly enhanced.
