Distributed sensor systems have become a highly active research area due to their potential for providing diverse new capabilities. Such systems allow intelligent dense monitoring of physical environments, which makes them immensely useful for data collection and analysis. While much ongoing research has addressed networking, communication and low–level self–configuration issues in such systems, there are also significant challenges pertaining to systematic design, algorithm development and analysis, and abstract modeling in order to achieve efficient and robust realizations of large–scale distributed sensor systems. The large number of sensor devices involved, severe power, computational and memory limitations, resource heterogeneity, dense deployment and frequent failures pose novel challenges to design, algorithms, analysis and implementation. <b>Keywords:</b> Computation and programming models<br>Energy models, minimization, awareness<br>Distributed algorithms for collaborative information processing<br>Theoretical performance analysis: complexity, correctness, scalability, fault–tolerance<br>Abstractions for modular design<br>Languages, operating systems<br>Task allocation, reprogramming and reconfiguration<br>Dynamic resource management<br>Scalable, heterogeneous architectures (node and system–level)<br>Communication and processing primitives<br>Middleware interfaces<br>Design, simulation and optimization tools for deployment and operation<br>Design automation and application synthesis techniques<br>Case studies: lessons from real world deployments<br>
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DCOSS
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Santa FeNM
Country
United States
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