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Using Distributed Skyline Queries over Centralized Uncertain Data for Efficient

Platform : java

IEEE Projects Years : 2012 - 13

Using Distributed Skyline Queries over Centralized Uncertain Data for  

Efficient

 

Abstract:

 

The skyline operator has received considerable attention from the database community, due to its importance in many applications including multicriteria decision making, preference answering, and so forth. In many applications where uncertain data are inherently exist, i.e., data collected from different sources in distributed locations are usually with imprecise measurements, and thus exhibit kind of uncertainty. Taking into account the network delay and economic cost associated with sharing and communicating large amounts of distributed data over an internet, an important problem in this scenario is to retrieve the global skyline tuples from all the distributed local sites with minimum communication cost. Based on the well-known notation of the probabilistic skyline query over centralized uncertain data, in this paper, we propose the notation of distributed skyline queries over uncertain data. Furthermore, two communication- and computation-efficient algorithms are proposed to retrieve the qualified skylines from distributed local sites. Extensive experiments have been conducted to verify the efficiency, the effectiveness and the progressiveness of our algorithms with both the synthetic and real data sets.

 

Index Terms—Skyline,  distributed database,  uncertain data.

 

Existing System :

 

The Skyline operations are used to extend database system and received the large data from Database. This is used to give importance for many application with uncertain data. Generally many applications are not supporting the uncertain data. The uncertain data collected from source in distributed location is insecure and inaccurate. Important problem in this scenario is to retrieve the global skyline tuples from all the distributed local sites with minimum communication cost.

 

Proposed System:

 

          In this system are used to skyline queries is over centralized uncertain data. This purpose of proposed system used efficient algorithm. We can retrieve the tuples from distributed system with minimum communication cost and financial cost even there is network delay. To verify the real and copy of data from efficient algorithm. This algorithm are used to clear the fault in that operation.

 

Algorithm:

 

PROPOSED:

 

we empirically evaluate the efficiency and progressiveness of the proposed distributed DSUD(distributed skyline over uncertain data) algorithm and     its enhanced version e-USDU algorithm.

 

EXISTING:

 

Since the baseline approach, which simply asks all the participants to send their entire uncertain databases to the coordinator, is too communication expensive. We will consider the DSUD algorithm as the baseline algorithm, and compare e-DSUD against this baseline solution.

 

 

 

 

 

Resource Requirements :      

 

Software Requirements :

 

                        Operating system                     :           Windows7

 

                        Front End                                 :           Java

 

                        Back End                                 :           Database, SQL Server             

 

            Hardware Requirements :

 

                        Processor                                 :           Pentium Dual Core 2.00GHZ  

 

                        Hard disk                                 :           40GB

 

                        Mouse                                      :           PC tech

 

                        RAM                                        :           2GB(minimum)

 

                        Keyboard                                 :           120keys enhanced

 

 MODULES:

 

1. NETWORK MODULE

 

2. DESIGN MODULE

 

3. SOURCE MODULE

 

4. PROCESS MODULE

 

1. NETWORK  MODULE:

 

Developed efficient algorithms for retrieving the skyline in P2P networks. The algorithm demands that the data of the peers are organized using an overlay network.

 

Specifically, bandwidth consumption is measured by the number of tuples transmitted over the network

 

           

 

2. DESIGN MODULE:

 

The design of  communication efficient algorithms for retrieving the skyline tuples with the global skyline probability larger than a threshold from distributed sites, with computation overhead also as a major consideration. APR-tree is designed for pruning sub trees that do not contain any qualified skyline results, thus to accelerate the skyline query procedure.

 

3. SOURCE MODULE:

 

We first introduce the uncertainty data model and its corresponding possible world semantics. Then, we define the problem of probabilistic skyline retrieval over distributed uncertain data and clarify the underlying assumptions.

 

 

 

 

 

 

 

 

 

 

 

4. PROCESS MODULE:

 

We provide more details about the background and the related work. Based on the general framework we proposed, the drawback of choosing inappropriate feedbacks in the query  processing procedure is analyzed, which makes the feedback  mechanism in our method more reliable.  We add how to continuously maintain the skyline results when data updates happen at local sites, and the scenario of distributed retrieval of specified subspace skyline is also discussed. some optimization techniques are integrated into the implementation issues to achieve better performance. Finally, we reconsider the experimental settings and conduct extensive experiments to evaluate the performance of our proposed algorithms.



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