Abstract: Data stream clustering is an active research area that has recently used to discover knowledge from continuously generated large amounts of data. There are various data stream clustering algorithms have been developed and proposed to perform clustering on data stream. Clustering is the task of arrangement a set of objects so that objects in the identical group are more related to each other than to those in other groups (clusters). The data stream clustering imposes several challenges that need to be addressed; some of them are dealing with dynamic data, capable of performing processing on fast incoming objects, also capable to perform incremental processing of data objects, and ability to address time, memory and cost limitations.
Keywords: Affinity Propagation, Autonomic Computing, Clustering, Data stream, Grid Monitoring.