Research On Data Source Quality For Sensor Cloud

With the rise of sensor clouds,in many scenarios,people are more inclined to pass sensor data to the cloud.This way the cloud accumulates a lot of historical data.If you can predict the quality of the data source,you can mark the quality when the sensor pushes the data to the cloud and the cloud stores the data in the database.Secondly,if the application or query needs to pull data from the sensor in real time,it can avoid the inferior data pollution polling result,and save resources such as network bandwidth.In a sensor cloud,values in the same region are usually provided by more than one data source,but data from different data sources are biased.In this paper,the data source quality in the sensor cloud is studied,and the data source quality measurement model is given.Formally define the data source quality description as a quality matrix that describes the overall quality of the data source.As the amount of data will continue to increase,the quality matrix will be simplified,and the simplification result can reflect the commonality or difference of the quality of the same data source in diverse scenarios.Quality assessment issues for multiple data sources facing the same entity are studied based on areas of interest to the user.Design efficient evaluation methods for different simplification goals to avoid a decline in overall service quality due to the time loss of the data source.When the user is interested in the local information of the monitoring area,but the number of entities and entities in the area is unknown,the concept of the sensor monitoring entity is formalized to study the quality assessment of multiple data sources for multiple entities.It is reduced to the entity identification problem and a cluster-based method is proposed.Efficiently assess the quality of data sources by combining quality assessment methods for data sources that target the same entity.