Efficient multi dimensional web information discovery in wireless sensor network

Abstract

Data which related to more than two dimensions is known as newlinemultidimensional data. the multidimensional data has sensed by the wireless newlinesensor network (wsn) is nature. the increasing availability of small-size newlinesensor devices during the last few years and the large amount of data that they newlinegenerate has led to the necessity for more efficient methods regarding data newlinemanagement. the multidimensional data storage and retrieval is an important newlinething in wsn. here a models have been introduced which can be used for newlinedata gathering and information management in sensor networks which newlineprovides some advantages through the utilization of semantic web newlinetechnologies. the efficient multidimensional data storage and retrieval techniques newlinehave some problems in their works. generally, the cube based storage newlineapproaches are developed for storing multidimensional data and indexing newlineschemes are developed for efficient retrieval of multidimensional data. these newlinetwo techniques also have the following pitfalls in their work. newlinethe data are dynamic in wsn which means it get changed for newlineevery second so it need to be updated in every storage and retrieval approach newlinebut it does not addressed in multiple works. first the cube-based storage newlineapproach does not try to find the related words using distance measuring newlineconcepts. this means calculating the distance between dimensionality helps to newlineidentify the related words for getting fast retrieval. newlinethe spatio-temporal data is a type of multidimensional data which newlinegives both location and time base information. generally, the spatio-temporal newlinedata are unevenly distributed in the network newline newline