Modeling distributed signal processing applications

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

10 Citations (Scopus)

Abstract

Wireless Sensor Networks in general and Body Sensor Networks in particular enable sophisticated applications in pervasive healthcare, sports training and other domains, where interconnected nodes work together. Their main goal is to derive context from raw sensor data with feature extraction and classification algorithms. Body sensor networks not only comprise a single sensor type or family but demand different hardware platforms, e.g., sensors to measure acceleration or blood-pressure, or tiny mobile devices to communicate with the user. The problem arises how to efficiently deal with these heterogeneous platforms and programming languages. This paper presents a distributed signal processing framework based on TinyOS and nesC. The framework forms the basis for a Model-Driven Software Development approach. By raising the level of abstraction formal models hide implementation specifics of the framework in a Platform Specific Model. A Platform Independent Model further lifts modeling to functional and non-functional requirements independent from platforms. Thereby we promote cooperation between domain experts and software engineers and facilitate reusability of applications across different platforms.

Original languageEnglish
Title of host publicationProceedings - 2009 6th International Workshop on Wearable and Implantable Body Sensor Networks, BSN 2009
PublisherIEEE Computer Society Press
Pages103-108
Number of pages6
ISBN (Print)9780769536446
DOIs
Publication statusPublished - 2009
Event2009 6th International Workshop on Wearable and Implantable Body Sensor Networks, BSN 2009 - Berkeley, CA, United States
Duration: 3 Jun 20095 Jun 2009

Publication series

NameProceedings - 2009 6th International Workshop on Wearable and Implantable Body Sensor Networks, BSN 2009

Conference

Conference2009 6th International Workshop on Wearable and Implantable Body Sensor Networks, BSN 2009
CountryUnited States
CityBerkeley, CA
Period03.06.200905.06.2009

Keywords

  • Body sensor networks
  • Model-driven software development
  • Signal processing
  • Wireless sensor networks

Fingerprint Dive into the research topics of 'Modeling distributed signal processing applications'. Together they form a unique fingerprint.

Cite this