EFFICIENT COMPUTATION OF RANGE AGGREGATES AGAINST
UNCERTAIN LOCATION BASED QUERIES
In many applications, including location based services, queries may not be precise. In this paper, we study the problem of efficiently computing range aggregates in a multidimensional space when the query location is uncertain. Specifically, for a query point Q whose location is uncertain and a set S of points in a multi-dimensional space, we want to calculate the aggregate (e.g., count, average and sum) over the subset SI of S, Q has at least probability θ within the distance γ to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to effectively and efficiently remove data points from verification. Our comprehensive experiments based on both real and synthetic data demonstrate the efficiency and scalability of our techniques.
This motivates us to follow the filtering-and-verification paradigm for the uncertain aggregate query computation. Particularly, in the filtering phase, effective and efficient filtering techniques will be applied to prune or validate the points. The algorithm consists of two phases. In the filtering phase for each entry e of RS to be processed, we do not need to further process e if it is pruned or validated by the filter F. We say an entry e is pruned (validated) if the filter can claim Pfall (p, γ) < θ (Pfall (p, γ) ≥ θ) for any point p within embb. The counter cn is increased by |e| if e is validated where |e| denotes the aggregate value of e (i.e., the number of data points in e). Otherwise, the point p associated with e is a candidate point if e corresponds to a data entry and all child entries of e are put into the queue for further processing if e is an intermediate entry. The filtering phase terminates when the queue is empty. In the verification phase candidate points are verified by the integral calculations.
The existing techniques for processing location based spatial queries regarding certain query points and data points are not applicable or inefficient when uncertain queries are involved.
1. Query location is uncertain.
2. In those applications, searching such a location may not only request targets but may also damage other civilian objects details.
Our techniques will be presented based on the aggregate count. Nevertheless, they can be immediately extended to cover other aggregates, such as min, max, sum, avg, etc. In this application, the risk of civilian casualties may be measured by the total number n of civilian objects which are within γ distance away from a possible blast point with at least θ probability. It is important to avoid the civilian casualties by estimating the likelihood of damaging civilian objects once the aiming point of a distance (km) is determined.
1. Avoid damaging civilian objects.
2. Filtering technique is applied.
FILTERING AND VERIFICATION:
When User wants to Search any Civilian Objects like Hotels, Hospitals, Banks, etc., to generate & verify the database then gave exact details. If, he wants to Advanced Search, to give exact range values, apart from that civilian objects details to be displayed with Civilian Objects categorized and calculate the distance details.
Admin Verify the User Requests and check the user requests is contain in our database or not. If the database contains the user requests to calculate the Range (Distance) value, and then send Response to the Appropriate Values, suppose the request doesn’t contain in the database send response is ‘Record Not Found’ that query sent to the particular User.
User Verify the Admin Responses and the user requests is match with database the query produce with the Correct Results and Download the word file, otherwise not download. If the database contains the user requests to calculate the Range (Distance) value, suppose the request doesn’t contain in the database received response is ‘Record Not Found’ but if matching results are retrieved.
UPLOAD CIVILIAN OBJECTS WITH DISTANCE:
Admin can upload the Civilian Objects details with Correct Location (area), Address, Phone and Upload Civilian Objects Profile (.doc) file. If calculate distance in one location to another location so the admin entry the details for distance and admin can view the User Details also.
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• Ram : 512 Mb.
• Operating system : Windows XP.
• Coding Language : ASP.Net with C#
• Database : Sql Server 2005.