Location-Based Data Dissemination for Spatial Queries in Wireless Broadcast Environments

来源 :Journal of Computer Science & Technology | 被引量 : 0次 | 上传用户:simetl1
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Most current research on Location-Based Services(LBSs,for short) assumes point-to-point wireless communication, where the server processes a query and returns the query result to the user via a point-to-point wireless channel. However,LBSs via point-to-point wireless channel suffer from a tremendous amount of traffic and service requests from the user and thereby result in poor performance.In this paper,we present broadcast-based spatial query processing algorithms designed to support k-NN(k-Nearest Neighbor) and range queries via a wireless network.The task of the query processor is to selectively monitor the wireless broadcast channel,when the data items are disseminated by the server,according to their locations.Experiments are conducted to evaluate the performance of the proposed algorithms.Comprehensive experiments illustrate that the presented algorithms are highly scalable and are more efficient than the previous techniques in terms of both access time and energy consumption. Most current research on Location-Based Services (LBSs, for short) assumes point-to-point wireless communication, where the server processes a query and returns the query result to the user via a point-to-point wireless channel. However, LBSs via point-to-point wireless channel suffer from a tremendous amount of traffic and service requests from the user and thereby result in poor performance.In this paper, we present broadcast-based spatial query processing algorithms designed to support k-NN (k- Nearest Neighbor) and range queries via a wireless network. The task of the query processor is to selectively monitor the wireless broadcast channel, when the data items are disseminated by the server, according to their locations. Experiments are evaluate to the performance of the proposed algorithms.Comprehensive experiments illustrate that the presented algorithms are highly scalable and are more efficient than the previous techniques in terms of both access time and energy consumption.
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