Live Data Views: Programming Pervasive Applications that Use “Timely” and “Dynamic” Data
Conference Proceeding Article
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.
IEEE Mobile Data Management Conference (MDM)
BLACK, J.; Castro, Paul; MISRA, Archan; and White, J..
Live Data Views: Programming Pervasive Applications that Use “Timely” and “Dynamic” Data. (2005). IEEE Mobile Data Management Conference (MDM). Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/691
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