Energy Efficient Reverse Skyline Query Processing over Wireless Sensor Networks

Energy Efficient Reverse Skyline Query Processing over Wireless Sensor Networks

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

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 [8], top-k [9], [10], and skyline [11], [12]. 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.

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

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

Advantage:

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

Requirements:

Hardware Requirement:-

                       Hard Disk                    -           20 GB

                       Monitor                       -           15’ Color with VGI card support

                       RAM                            -           Minimum 256 MB

                       Processor                    -           Pentium III and Above (or) Equivalent

                       Processor speed         -           Minimum 500 MHz

            Software Requirement:-

                       Operating System      -           Windows XP

                       Platform                      -           Visual Studio .Net 2005 & Above

                       Database                     -           SQL Server 2005

                       Languages                   -           C#.Net, ADO.Net