An Experimental Evaluation of Distributed Data Stream Processing using Lightweight RDBMS SQLite

Abstract

The data generated at a very high rate by sensors and RFIDs are required to be handled by continuous queries keeping real time response. DSMSs (Data Stream Management systems) are used in several cases of these large scale systems for its purpose. This paper describes the results of experimental evaluation of distributed data stream processing using SQLite which is a lightweight RDBMS as a stream processing engine node. In particular, it is necessary to correspond also to the increasing data rate flexibly in data stream processing. This paper proved that it could respond to the increase in a data rate by adding a processing node dynamically. In that case, it is necessary to perform synchronous processing in two or more processing nodes. Therefore, within the limits of this experiment, it turned out that it is realizable by performing synchronous processing by the side which divides and passes data.