International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 2 Issue: 4 838 – 845 _______________________________________________________________________________________________ 838 IJRITCC | April 2014, Available @ http://www.ijritcc.org _______________________________________________________________________________________ Comparative Study On Data Aggregation Techniques for Wireless Sensor Networks Abhijith H V Dept. of Information Science and Engineering BMS College of Engineering Bangalore, India abhijithhv.mithra@gmail.com Dr M Dakshayini Dept. of Information Science and Engineering BMS College of Engineering Bangalore, India dakshayini.ise@bmsce.ac.in Abstract— The Wireless Sensor Networks (WSN) is one of the emerging technologies in the field of wireless ad-hoc networks. It consists of several low cost and low power sensor nodes which are capable of sensing, processing and communicating the various environmental parameters. These sensor nodes are randomly and densely deployed in the region of interest. The denser deployment of sensor nodes leads to the sensing and transmission of redundant information. Routing of such redundant data not only saturates the network resources, but also results in the wastage of energy and hence reduces the network lifetime. Data aggregation is the techniques which aggregate the data from different sensor nodes and reduces the redundant transmissions. Data aggregation ensures the efficient utilization of energy and hence enhances the network lifetime. In this paper, we present a survey on different data aggregation techniques for Wireless Sensor Networks. Keywords- Data Aggregation; WSN; Network Lifetime; Energy; Sensor Node; Redundant Data. __________________________________________________*****_________________________________________________ I. INTRODUCTION The Wireless Sensor Networks is one among the emerging networking technologies of 21 st century. Wireless Sensor Networks have received attention from both academics and industry because of its wider application range. Wireless Sensor Network consists of a large number of low-power, and multifunctional sensor nodes, with sensing, wireless communications and computation capabilities. These sensor nodes can communicate over short distance via wireless medium and collaborate to accomplish a common task, for example, environment monitoring, military surveillance, and industrial process control. The sensor nodes are energy constrained, therefore it is inefficient for all the sensor nodes to transmit the sensed data directly to the sink node. Data sensed by the sensor nodes which are nearer to each other is redundant. In addition, it is difficult for the sink node to process huge amount of data. Hence, there is a need for a method which combines the data from different sensor nodes and reduces the number of packets to be transmitted to the sink node. This results in the saving of energy and increase in the network lifetime. Wireless sensor nodes require less power for processing the data than compared to transmitting data. It is preferable to do in network processing inside network and reduce packet size. Since sensor nodes may generate significant redundant data, similar packets from multiple nodes can be aggregated so that the number of transmissions is reduced. This can be accomplished by data aggregation Techniques. Data aggregation is a process of combining the data from multiple sensor nodes to avoid redundant transmission and provide aggregated information to the sink node. The Data aggregation attempts to collect the critical data from the neighboring and intermediate sensor nodes and make it available to the base station in an energy efficient manner with minimum data latency. Data latency is important in many applications such as environment monitoring, where the freshness of data is also an important factor. The main goal of data-aggregation algorithms is to collect and aggregate data in an energy efficient manner so that network lifetime is increased. The working of Data aggregation algorithm is shown in the figure 1. The data from different sensor nodes are passed to the data aggregation algorithm. The data aggregation algorithm aggregates the data based on the application by using different data aggregation functions such as, max, min, count, average, sum, concat. Then the aggregated data is transmitted to the sink node [1]. Figure 1: General architecture of the data aggregation algorithm The remaining sections of the paper are structured as follows: Section II provides the performance characteristics of data aggregation techniques. Section III describes the classification of data aggregation techniques. Section IV describes the different data aggregation protocols. Section V draws the conclusions. II. PERFORMANCE CHARACTERISTICS A. Data Accuracy The definition of data accuracy depends on the specific application for which the sensor network is designed. For instance, in a target localization problem, the estimate of the target location at the sink determines the data accuracy. In many cases there may be chance of compromising data Sensor data collected from sensor nodes Data aggregation algorithm Aggregated data Sensor base station /sink node