Data Redundancy Reduction in Wireless Sensor Network

Abstract

In Wireless Sensor Network, sensor nodes are randomly deployed where the sensor nodes are not situated faraway from each other. Thus, an overlapping area is generated due to intersection of their sensing ranges. If an event occurs within the overlapping area, all the sharing nodes sense the same event and produce redundant and correlated data. Data redundancy exhaust network resources and increase network overhead. Data aggregation and numerous data redundancy reduction algorithms are employed to solve this problem. This paper reviews modern data redundancy reduction used sleep schedule model to solve the redundancy. All proposed algorithms are classified on the basis of network coverage and similarity among sensory data which can be used in reducing redundancy in WSN effectively.