Performance evaluation of rate-based join window sizing for asynchronous data streams

Our work is motivated by the large number of data stream sources that define mesoscale meteorology where asynchronous streams are commonplace. Techniques for performing filtering, aggregation, and transformation on multiple streams must be effective for the case of asynchronous streams. Rate Sizing algorithm (RS-Algo) links the number of events waiting to participate in a join to the rate of the streams responsible for their delivery. In this poster, we show the results of performance evaluation of the RS-Algo. The gains in memory utilization are largest under asynchronous streams.