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Sensor networks are Distributed Real-time Embedded (DRE) systems that often operate in open environments where operating conditions, workload, resource availability, and connectivity cannot be accurately characterized a priori. The South East Alaska MOnitoring Network for Science, Telecommunications, Education, and Research (SEAMONSTER) project illustrates many common system management and dynamic operation challenges in a representative sensor network, including adapting to changes in network topology, effective reaction to local environmental changes, and power management through system sleep/wake cycles. This paper discusses a case study for applying middleware and autonomous agent technologies from the Multi-agent Architecture for Coordinated Responsive Observations (MACRO) to these challenges in the SEAMONSTER sensor network.

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Format:PDFSize:452 KB
Date:May 2008
Pages:6

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