A compression algorithm is proposed in this paper for reducing the size of sensor data. By using a dictionary-based lossless compression algorithm, sensor data can be compressed efficiently and interpreted without decompressing. The correlation between redundancy of sensor data and compression ratio is explored. Further, a parallel compression algorithm based on MapReduce [1] is proposed. Meanwhile, data partitioner which plays an important role in performance of MapReduce application is discussed along with performance evaluation criteria proposed in this paper. Experiments demonstrate that random sampler is suitable for highly redundant sensor data and the proposed compression algorithms can compress those highly redundant sensor data efficiently.
随着GIS(地理信息系统)的发展与完善,它的开发工具也日趋成熟。MapInfo公司顺应这发展潮流,开发了MapInfo以及MapX控件,可以实现复杂的GIS系统设计。根据桂林市规划地图,首先利用MapInfo 9.5构建地图数据,然后通过Geoset Manager生成Geoset格式文件,最后在Visual Studio 2008编程环境下、利用C#编程语言对MapX控件进行二次开发,最终实现桂林市电子地图。
