Research Of Skyline Query Processing On Uncertain Dataset Of WSNs

With the rapid development of computer and the communication technology, the computer network technology become more perfect. Many practical applications using network technology such as financial information, geological surveying, astronomical observation, meteorology, sensor networks and data integration, generate a large number of data streams. Because of the complexity of the network environment, the data stream exist the inevitable uncertainty. So, the technical processing of uncertain data streams has engaged many scholars’attention. The rapid development of sensor networks in environmental monitoring and event supervision makes the performance of sensor get a good show. However, because most wireless sensor’s computing power, storage capacity, processing power is limited and the date which generate in the process of data collection, date communication is uncertainties, the existing technology can’t be applied directly to query processing. Skyline query processing technology is often used to deal with the multiple objective decision problems, and the most application of the uncertain data streams are multi-objective problems. Therefore, the application of skyline query must have a good effect. Although Skyline has much comprehensive study, most methods focus on certain data streams. So, they can’t be applied to the uncertain data streams directly.Based on the research and analysis of the existing uncertainty Skyline query algorithm, combined with the characteristics of sensor networks, a class of algorithms VDPS about the based technology of Skyline query processing have been proposed in this paper. The experimental data of those algorithms come from a large number of real data and a variety of distribution data which are generated by the standard data generation algorithm. Experimental results show that few time needed when we query the inversely related query bulk distribution dataset Skyline dataset. And when the dataset is extended to multi-dimensional, the real-time of the algorithm is still good. In this paper, we also study the distributed Skyline query technology, a new technology on uncertain data sets, and propose a Skyline query methods based on space division technology. This method is suitable for large-scale Skyline query processing on uncertain data sets. When Skyline query is required for multi-user query, in order to achieve the purpose of the space to reduce the computational resources, we propose a method through setting user preferences queue area of molecular. The experimental results show that this method can effectively control the number of sub-space, and the algorithm has a better real-time, and it can response to most user’s requires immediately.