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A system-level design approach for dynamic resource coordination and energy optimization in sensor network platforms

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationConference Record of the 47th Asilomar Conference on Signals, Systems and Computers
PublisherIEEE COMPUTER SOCIETY PRESS
Pages1436-1441
Number of pages6
ISBN (Print)9781479923908
DOIs
Publication statusPublished - 2013
Publication typeA4 Article in a conference publication
Event2013 47th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: 3 Nov 20136 Nov 2013

Conference

Conference2013 47th Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period3/11/136/11/13

Abstract

Strict run-time and resource constraints in wireless sensor networks (WSNs) introduce complex design problems that need to be addressed systematically. Recent processor platforms for WSNs have groups of peripheral devices that are used for data sensing and processing. Hardware interrupts are commonly used as an efficient method for handling data acquisition from such peripherals. Dynamic control for multiple interrupts and efficient handling of power consumption on embedded processors are important issues when implementing dynamic, data-driven signal processing applications, where the structure of processing subsystems may need to be adapted at run-time based characteristics of input data and associated operating conditions. To address these issues, we introduce a dataflow-based design approach based on integrating interrupt-based signal acquisition in the context of parameterized synchronous dataflow (PSDF) modeling. This application of PSDF provides a useful foundation for structured development of power- and energy-efficient wireless sensor network systems for dynamic, data-driven applications systems (DDDAS), including DDDAS that employ intensive acquisition and processing of signals from heterogeneous sensors. To demonstrate our proposed new signal-processing-oriented, dataflow-based design approach - which we refer to as DDPSDF (data-driven PSDF) - we have implemented an embedded speech recognition system using the proposed DDPSDF techniques. We demonstrate that by applying our DDPSDF approach, energy- and resource-efficient embedded software can be derived systematically from high level models of DDDAS functional structure.

Keywords

  • Dataflow graphs, DDDAS, Digital signal processing, Parameterized dataflow, Wireless sensor networks