Data Redundancy Implications in Wireless Sensor Networks

Abstract Redundancy ensures reliable data for decision making. Reliable data plays a very important role in the analysis, monitoring and forecasting of system behaviour whereas bad quality data may provide erroneous result in decision scheme. In Wireless Sensor Network (WSNs), nodes are densely deployed in a region to collect information. Sensors sense the similar data and forwards to sink. This similar data sometimes leads to redundancy at the sink. The redundant data results in more accuracy, reliability and security whereas elimination helps in energy saving as most of the energy of sink node gets waste in dealing with the redundant data. Data accuracy still needs to be preserved even if there is increase in network cost and/or time. Therefore, there is requirement of a mechanism in which we can extract information from the redundant data and be able to provide a more consistent, accurate and reliable data set in an energy efficient manner. The data fusion techniques help in maintaining the same. This paper presents the various data fusion approach that shows the impact of redundancy in the area of WSNs.

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