The Research Of Retrieval Optimized On Optimized Retrieval Cache Method Which Base On Multi-level Of Massive Sensor Data

With the rapid rising of the Internet, sensing electronic devices and the rapid development of computer technology, how to improve the retrieval efficiency of mass-sensor data has become an urgent problem to be solved. Recently most of the research focuses on the real-time sensor data processing, while ignoring history sensor data retrieval optimization studies. This paper focuses on sensor data query optimization, Based on the massive, real-time and time-related characteristics of sensor data, in the background of the in massive traffic sensor data, The optimization of in order to optimize the efficiency of data retrieval massive perceive as the goal, the paper mainly analysis in a distributed processing on Massive sensory data as well as cache hit and horizontal division based on time and so on, the main research work is as below:1. Distributed processing of Massive sensor data, the main idea is that using read and write data separation, so when the user concurrent access the application, it will greatly reduce the load on a single database server.2. Using horizontal partitioning based on the time on the massive sensor data, it will avoid scanning all the tables and greatly improve the efficiency of searching data.3. It proposes multi-level cache matching algorithm which combinates with massive sensory data and Memcached Server features, so that the efficiency of the cache hit rate has been greatly improved.4. The Detection System of Sensor Data Traffic Detection is the research background. The paper performs experiment on the distributed processing, horizontal division and multi-level cache on the sensor data of traffic of vehicles. Through the study on the related technologies and analysis of experimental results of The Detection System of Sensor Data Traffic Detection, It is proved that the technical solutions proposed in this paper can effectively optimize sensing data retrieval efficiency, it can control the query time at the millisecond level in order to meet the needs of users.