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Abstract
Location-based services (LBS) enable mobile users to query points-of-interest (e.g., restaurants, cafes) on various features (e.g., price, quality). In addition, users require accurate query results with up-to-date travel times. Lacking the monitoring infrastructure for road traffic, the LBS may obtain live travel times of routes from online route APIs in order to offer accurate results. Our goal is to reduce the number of requests issued by the LBS significantly while preserving accurate query results. Our proposed work, the user has an access to router via an internet. Based on his present location he has to choose the destination point, and then LBS will communicate with server and shows you the nearest places of his choice. First, we propose K-NN Route analysis to exploit recent routes requested from route APIs to answer queries accurately. Then, we design effective lower/upper bounding techniques and ordering techniques to process queries efficiently. Also, we study parallel route requests to further reduce the query response time. Our experimental evaluation shows that our solution is three times more efficient than a competitor, and yet achieves high result accuracy (above 99 percent).Combine information across multiple routes in the log to derive lower/upper bounding travel times, which support efficient and accurate range and KNN search. Develop heuristics to parallelize route requests for reducing the query response time further. Evaluate our solutions on a real route API and also on a simulated route API for scalability tests.