Study on Library Location Awareness Service under Cloud Computing Environment
WANG Nenghui
Abstract：Combining with the rapidly-developing cloud computing technology,this paper proposes a parallel naive Bayesian probability calculation method based on MapReduce architecture,so as to solve the problem that library location awareness server using WLAN-based location fingerprinting algorithm takes too long when processing large-scale location data. This method can quickly calculate fingerprint database and work out the posterior probability of located targets at each record through MapReduce ar?chitecture,and then determine the location coordinates of targets with the posterior probability obtained as weight,thus improving the performance of library location awareness server in terms of location accuracy and time responsiveness and perfecting the quality of library location awareness services. Besides,in this paper,library indoor location experiment using the proposed parallel naive probability calculation method is conducted,and comparison experiment is made between the proposed method and serial naive Bayesian probability calculation method. Experiment results show that the improved location calculation method can not only effec?tively shorten the computing time of location process,but also ensure location accuracy so as to fully meet location service require?ments.
Keywords：cloud computingMapReduceBayesianlibrarylocation based service
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 778-784 )