Robust Aggregation in Sensor Network: An Efficient Frequent Itemset and Number of Occurrence Counting
Sensor networks are collection of sensor nodes which co-operatively send sensed data to base station. As sensor nodes are battery driven, an efficient utilization of power is essential in order to use networks for long duration hence it is needed to reduce data traffic inside sensor networks, reduce amount of data that need to send to base station. The aim of the project is to develop scalable aggregation methods to extract useful information from the data the sensors collect. Partitioning large set of data, for the result of horizontal aggregation, in to homogeneous dataset is important task in this system. Association rule apriority algorithm using SQL is best suited for implementing this operation.