This document discusses energy efficient processing of reverse skyline queries in wireless sensor networks. It proposes using a full skyband approach to minimize communication costs among sensor nodes when evaluating range reverse skyline queries. It also discusses optimization mechanisms for improving the performance of multiple reverse skyline queries, including vertical and horizontal optimizations. Extensive experiments on real and synthetic data demonstrate the efficiency and effectiveness of the proposed approaches.

1. Energy Efficient Reverse Skyline
Query Processing over Wireless
Sensor Networks
Project Code : JNW 01

2. TARGETJ SOLUTIONS
REAL TIME PROJECTS
IEEE BASED PROJECTS
EMBEDDED SYSTEMS
PAPER PUBLICATIONS
MATLAB PROJECTS
targetjsolutions@gmail.com
(0)9611582234, (0)9945657526

3. Abstract:
Reverse skyline query plays an important role in many sensing
applications, such as environmental monitoring, habitat monitoring, and
battlefield monitoring. Due to the limited power supplies of wireless sensor
nodes, the existing centralized approaches, which do not consider energy
efficiency, cannot be directly applied to the distributed sensor environment.
In this paper, we investigate how to process reverse skyline queries energy
efficiently in wireless sensor networks. Initially, we theoretically analyzed
the properties of reverse skyline query and proposed a skyband-based
approach to tackle the problem of reverse skyline query answering over
wireless sensor networks. Then, an energy-efficient approach is proposed
to minimize the communication cost among sensor nodes of evaluating
range reverse skyline query. Moreover, optimization mechanisms to
improve the performance of multiple reverse skylines are also discussed.
Extensive experiments on both real-world data and synthetic data have
demonstrated the efficiency and effectiveness of our proposed approaches
with various experimental settings

4. Introduction
AS an important and popular query operator for multiple criteria
decision making, skyline and its variants, such as constrained skyline
dynamic skyline and reverse skyline have been applied in many
applications. Given a data set P, a traditional skyline retrieves all the
points in P that are not dominated by others. A point p1 dominates
another point p2, if p1 is not worse than p2 for each dimension I nd p1
is better than p2 for at least one dimension j. Fig. 1a shows an example
of traditional skyline in 2D space and points p1, p2, and p6 are the
skyline points In addition to traditional skyline, dynamic skyline with
respect to qðdenoted as DSðq; PÞÞ has been proposed to retrieve all
the points that are not dynamically dominated by others. For the sake
of simplicity, we adopt the definition of dynamic attributes proposed
in . A point p1 dynamically dominates p2 with respect to qðdenoted as
p1 _q p2Þ, if it holds that: 1) jp1½i_ _ q½i_j _ jp2½i_ _ q½i_j, for each
dimension i 2 D, and 2) there exists at least one dimension j 2 D, such
that jp1½j_ _ q½j_j < jp2½j_ _ q½j_j.

5. Literature Survey
Goal of Project
 Our goal is to carefully and properly adjust the relation of semidominance,
such that the modified relation becomes transitive (in turn, the query
becomes decomposable).
 After that, we are able to take the advantage of in-network aggregation
techniques to efficiently get the query results. This way, the base station can
calculate reverse skyline without introducing false dismissals.
 In order to achieve the goal above, we introduce another novel concept,
namely full dominance, between any two data points

6. Existing System:
Recently it is found that wireless sensor networks (WSNs) offer a very economic
and effective platform to monitor the environment.
To satisfy different application demands, we conduct various types of queries over
WSNs, for example min, max top-k, and skyline. The de facto limit to processing
queries in WSNs is the energy constraint, since sensor nodes are generally battery
powered, and in many WSNs (e.g., an unattended and hard-to-reach environment),
it is impossible or at least very difficult to change their batteries. Wireless
communication is the major energy consumer in WSNs, and therefore, if we can
reduce the amount of communication during query processing, the energy
consumption can be significantly reduced and the lifetime of the WSNs as a whole
can be prolonged.

7. Dis-Advantage
Almost all existing work has focused on reducing the
communication cost for a specific type of query.
As one of the important operators in WSN
applications, the energy-efficiency of RS query
processing also needs to be studied in depth.
Therefore, in this work, we study energy-efficient
approaches to answer reverse skyline (RS) queries
over WSNs

8. Proposed System:
We propose an energy-efficient approach to evaluate reverse skyline query in
WSNs, based on the full skyband which contains all necessary information for the
base station to reconstruct the reverse skyline. Then, the transmission of nonfull
skyline points is avoided by pointing out which full skyline points belong to the
reverse skyline. Furthermore, the proposed approaches are also extended to
support range reverse skyline and multiple reverse skyline queries.
2. We theoretically analyze the relationship between reverse skylines on different
dimensional spaces or query ranges, and propose two optimization mechanisms,
vertical and horizontal optimizations, to improve the performance of multiple reverse
skyline evaluation in WSNs.
3. Lastly, our extensive experimental studies using both real-world data and
synthetic data show that the proposed approach can significantly reduce the
communication cost among sensor nodes and save the energy consumption during
the evaluation of RS queries in WSNs

9. Advantages of Proposed System:
1. it is impossible or at least very difficult to change
their batteries. Wireless communication is the major
energy consumer in WSNs, and therefore,
if we can reduce the amount of communication
during query processing, the energy consumption can
be significantly reduced and the lifetime of the WSNs
as a whole can be prolonged

10. Requirement Analysis:
Software Requirements :
Operating System: Windows XP professional
Front End : Microsoft Visual Studio .Net 2005
Language : Visual C#.Net
Back End : SQL Server 2000

11. Hardware Requirements :
Processor : Pentium III / IV
Hard Disk : 40 GB
Ram :
256 MB
Monitor : 15VGA Color
Mouse :
Ball / Optical
Keyboard : 102 Keys

12. System User & Admin
login
Design Details Access the
database
continuously
Due to continuous
access & more user
access DB reaches
critical limit
Sensor 1 will give
alert signal for
critical limit
Sensor 2 will
continuously
monitor the critical
limit point

14. MODULE DECRIPTION:
Reverse Skyline Query:
 In all kind of applications, different users may have different preferences, and
it is quite common to have multiple queries in different subspaces which are posed into the WSN
(Wireless Sensor Networks) simultaneously to gather interesting information. Skyline queries over
databases have many important applications such as sensor data monitoring and business planning.
Skyline queries accurately and efficiently over data has become increasingly important. Reverse
skyline queries, which retrieve a set of objects whose dynamic skyline contains a given query point,
are useful and valuable for many applications such as business location and environmental
monitoring applications. Though there are several methods for processing reverse skyline queries,
they are based on pre-processing. Since they waste time and space to pre-compute necessary data
and to manage the pre-computed data, they are not feasible for some applications.

15. Optimization:
We implement two kinds of Optimization here one is
Vertical Optimization and another one is Horizontal
Optimization.

16. Vertical Optimization:
The Vertical Optimization technique is used for
multiple queries by using the relationship between
reverse skylines with respect to different subspaces
but the same query range.

17. Horizontal Optimization:
The Horizontal Optimization technique is used for
the relationship between reverse skylines with the
same subspace but different query ranges.

18. Trace the Database by using
Sensors:
The two sensors have been implemented to monitor the entire
database activities.
Out of this two sensors one sensor will monitor the entire
databases, in real time applications simultaneously more
number of users will access the databases, due to this problem
there might have a chance for any database to get its critical
point, to know the critical point alert one sensor is continuously
monitoring the database. Once any database reaches the critical
point it will give alert signal. The role of another sensor is to
monitor the critical point limit databases due to this we can
avoid major problems occurs in databases .