Loading [MathJax]/extensions/MathMenu.js
Composing pervasive data using iQL | IEEE Conference Publication | IEEE Xplore

Composing pervasive data using iQL


Abstract:

The emergence of pervasive networked data sources, such as Web services, sensors, and mobile devices, enables context-sensitive, mobile applications. We have developed a ...Show More

Abstract:

The emergence of pervasive networked data sources, such as Web services, sensors, and mobile devices, enables context-sensitive, mobile applications. We have developed a programming model for writing such applications, in which entities called composers accept data from one or more sources, and act as sources of higher-level data. We have defined and implemented a nonprocedural language, iQL, specifying the behavior of composers. An iQL programmer expresses requirements for data sources rather than identifying specific sources; a runtime system discovers appropriate data sources, binds to them, and rebinds when properties of data sources change. The language has powerful operators useful in composition, including operators to generate, filter, and abstract streams of values.
Date of Conference: 20-21 June 2002
Date Added to IEEE Xplore: 07 August 2002
Print ISBN:0-7695-1647-5
Conference Location: Callicoon, NY, USA
No metrics found for this document.

1. Composition of Pervasive Data

We are witnessing explosive growth in pervasive networked data sources, such as web services, fixed sensors measuring traffic or weather, and mobile devices reporting position. These data sources enable context-sensitive, mobile applications, such as location monitoring, fleet management, and emergency notification. Such an application must specify how the raw data provided by networked data sources is composed into the higher-level data that it needs. We have developed a programming model and a language, named , for specifying data-composition rules. We have implemented the language and a runtime system that frees the application developer from many of the details that must be addressed when dealing with such data sources, including the management of widely varying protocols and formats, the discovery of appropriate data sources, and the replacement of data sources that have failed or become unreachable.

Usage
Select a Year
2024

View as

Total usage sinceJan 2012:56
00.511.522.53JanFebMarAprMayJunJulAugSepOctNovDec202002100100
Year Total:8
Data is updated monthly. Usage includes PDF downloads and HTML views.
Contact IEEE to Subscribe

References

References is not available for this document.