Location-Based Spatial Query Processing in Wireless Broadcast Environments

Location-Based Spatial Query Processing in Wireless Broadcast Environments.

Abstract:

Location-based spatial queries (LBSQ s) refer to spatial queries whose answers rely on the location of the inquirer. Efficient processing of LBSQ s is of critical importance with the ever-increasing deployment and use of mobile technologies. We show that LBSQ s has certain unique characteristics that the traditional spatial query processing in centralized databases does not address. For example, a significant challenge is presented by wireless broadcasting environments, which have excellent scalability but often exhibit high-latency database access. In this paper, we present a novel query processing technique that, though maintaining high scalability and accuracy, manages to reduce the latency considerably in answering LBSQ s. Our approach is based on peer-to-peer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We demonstrate the feasibility of our approach through a probabilistic analysis, and we illustrate the appeal of our technique through extensive simulation results.

Existing System:

Existing techniques cannot be used effectively in a wireless broadcast environment, where only sequential data access is supported. It may not scale to very large user populations. In an existing system to communicate with the server, a client must most likely use a fee-based cellular-type network to achieve a reasonable operating range. Third, users must reveal their current location and send it to the server, which may be undesirable for privacy reasons.

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Proposed System:

This System is a novel approach for reducing the spatial query access latency by leveraging results from nearby peers in wireless broadcast environments. Our scheme allows a mobile client to locally verify whether candidate objects received from peers are indeed part of its own spatial query result set. The method exhibits great scalability: the higher the mobile peer density, the more the queries answered by peers. The query access latency can be decreased with the increase in clients.

System Requirement Specification:

Software Interface:

JDK 1.5.

Java Swing.

SQL Server.

Hardware Interface:

PROCESSOR             :         PENTIUM IV 2.6 GHz.

RAM                            :        512 MB DD RAM.

 MONITOR                 :        15” COLOR.

 HARD DISK              :         40 GB.

 KEYBOARD              :         STANDARD 102 KEYS.

 MOUSE                       :         3 BUTTON.

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