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ENERGY EFFICIENCY SCHEMES FOR ACCURACY-GUARANTEED SENSOR DATA AGGREGATION USING SCALABLE COUNTING

Platform : java

IEEE Projects Years : 2012 - 13

ENERGY EFFICIENCY SCHEMES FOR ACCURACY-GUARANTEED SENSOR DATA AGGREGATION USING SCALABLE COUNTING

Aim

 

            The main aim of this project is an enhance the robustness of the aggregate computation and efficiently avoiding communication failure by over counting problem in Sensors Networks.

 

Abstract

 

            Sensor networks have received considerable attention in recent years, and are employed in many applications. In these applications, statistical aggregates such as Sum over the readings of a group of sensor nodes are often needed. One challenge for computing sensor data aggregates comes from the communication failures, which are common in sensor networks. To enhance the robustness of the aggregate computation, multipath-based aggregation is often used. However, the multipath-based aggregation suffers from the problem of over counting sensor readings. The approaches using the multipath-based aggregation therefore need to incorporate techniques that avoid over counting sensor readings. In this paper, we present a novel technique named scalable counting for efficiently avoiding the over counting problem.

 

Existing System

 

 

  • The multipath-based aggregation suffers from the problem of over counting sensor readings.
  • Sensor nodes typically are limited in computing power, network bandwidth, storage capability, and energy supply.
  • A major shortcoming with the tree-based aggregation is that it is not robust against communication failures.

 

 

 

 

 

Proposed System

 

  • We provide theoretical analyses that show the advantages of the scalable counting technique over previously proposed techniques.
  • The scalable counting technique efficiently compute the aggregates under a given accuracy guarantee.
  • Reliability and Robustness.
  • Scalable Counting techniques efficiently avoiding the over counting problem and providing reliable communication between sensor nodes.

 

Disadvantages

 

  • Communication failures, which are common in sensor networks.
  • Limited computing power, storage capability and energy supply.
  • The existing system not robust against communication failure

 

Advantages

  • The proposed system focuses on having an accuracy guarantee for an aggregate result.
  • SC technique reduces the transmission costs of the aggregate computation.
  • SC technique requires much less space when comparing with previous techniques.

 

Modules

 

  • Client-server
  • Sensor data
  • File Transferring
  • Scalable Counting

 

 

 

 

 

Client-server

 

            Client-server communicate enable us to communicate two each other nodes by mean of port number. Only if it’s connected they can transfer the data each other.

 

Sensor Data

 

            This module will enable us to transfer the files with each other node which are connected by the port number. The each and every communication between the two nodes have unique port numbers.

 

File Transferring

 

            File transferring allows transferring the files with each other node which are connected by the port number. This form will enable to choose the file as user wish.

 

Scalable counting

 

          Scalable counting count the data size and file transferring time while sending the data from sender to the receiver. Once if its reached sender via shortest path in a particular time then whenever your requesting for that particular file the sending time will be the same.

Techniques

 

  • Sensor Data Aggregation Using SC Sketches
  • Sensor Data Aggregation Using Adaptive SC Sketches

 

Hardware Requirements

 

System                           :        Pentium dual core processor

Operating System           :        windows xp, win7, windows vista

Ram                               :        1GB ram

Peripheral devices                   :        key board, mouse

 

 

 

 

Software Requirements

 

Domain                          :        Knowledge and Data Engineering

Front end                       :        Java, HTML, and JSP

Back end                        :        MS-Access, My sql

 

 



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