Live data views: Programming pervasive applications that use "timely" and "dynamic" data

In the absence of generic programming abstractions for dynamic data in most enterprise programming environments, individual applications treat data streams as a special case requiring custom programming. With the growing number of live data sources such as RSS feeds, messaging and presence servers, multimedia streams, and sensor data, a general-purpose client-server programming model is needed to easily incorporate live data into applications. In this paper, we present Live Data Views, a programming abstraction that represents live data as a time-windowed view over a set of data streams. Live Data Views allow applications to create and retrieve stateful abstractions of dynamic data sources in a uniform manner, via the application of intra- and inter- stream operators. We provide details of our model and evaluate a proof-of-concept Live Data Views implementation to monitor traffic conditions on a highway. We also provide the preliminary design of a J2EE-based implementation, and outline some of the research challenges raised by this abstraction in a distributed computing environment.