Location-Dependent Query Processing: Semantic Cache for Real-Time Smart City Analytics

With the advent of wireless sensor networks and their deep integration with the world have enabled users worldwide to achieve benefits from location-based services through mobile applications, the problems such as low bandwidth, high network traffic, and disconnections issues are normally extracted from mobile services. An efficient database system is required to manage mentioned problems. Our research work finds the probability of user's next locations. A mobile user (query issuer) changes its position when performing a specific mobile search, where these queries change and repeat the search with the issuer position. Moreover, the query issuer can be static and may perform searches with varying conditions of queries. Data is exchanged with mobile devices and questions that are formulated during searching for query issuer locations. An aim of the research work is achieved through effectively processing of queries in terms of location-dependent, originated by mobile users. Significant studies have been performed in this field in the last two decades. In this paper, our novel approach comprise of usage of semantic caches with the Bayesian networks using a prediction algorithm. Our approach is unique and distinct from the traditional query processing system especially in mobile domain for the prediction of future locations of users. Consequently, a better search is analyzed using the response time of data fetch from the cache.