Calder query grid service: insights and experimental evaluation

We have architected and evaluated a new kind of data resource, one that is composed of a logical collection of ephemeral data streams that could be viewed as a collection of publish-subscribe "channels" over which rich data-access and semantic operations can be performed. This paper contributes new insight to stream processing under the highly asynchronous stream workloads often found in data-driven scientific applications, and presents insights gained through porting a distributed stream processing system to a grid services framework. Experimental results reveal limits on stream processing rates that are directly tied to differences in stream rates.