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NSF NOSS Workshop

Join us for the NOSS Workshop at the School of Mines on October 18-19, featuring key insights into sensor networks from experts in the field. Notable presentations include Guru Parulkar from NSF, Vijay Raghavan from DARPA discussing research challenges, and D. Rychaudhuri from Rutgers WINS Lab on writing effective grant proposals. Key topics include extreme scale sensor networks, auto-calibration, collaborative signal processing, security challenges, energy modeling, and the development of high-fidelity simulation tools. Gain valuable knowledge in pervasive computing and enhance your research capabilities.

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NSF NOSS Workshop

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  1. NSF NOSS Workshop 10/18-19 School of Mines

  2. Related Info on NOSS Workshop • http://toilers.mines.edu/NOSS/Infoagenda.html with links to the presentations of PIs, invited speakers, and NSF program manager Guru Parulkar. • Vijay Raghavan of DARPA presents technical challenges. • D. Rychaudhuri of Rutgers WINS Lab discuss research challenges in Sensor Nets and Pervasive Computing. He also gave an excellent presentation on how to write effective grant proposals!

  3. Research Challenges in Sensor Networks from Vijay Raghavan of DARPA • Extreme Scale • Auto Calibration of UGS Network • Collaborative Signal Processing • Robust Self-Localization • Deployment (Coverage/Communications) • Self-Stablization (based on local info; distributed control • Platform Improvement • Composition of diverse applications from a suite of algorithms/protocols optimized for specific platforms

  4. Research Challenges in Sensor Networks • Security of sensor networks (Authentication; intrusion tolerance) • Energy Source • Models of computing for sensor networks.Investigate complexity measures that expose trade-off, platform independent, semantic of basic operations • Query of sensor networks (support distributed DB) • High fidelity simulation tools for characterizing performance (terrain;deploy statistics…) • Programming in the large: A new language/compiler that support the delay binding based on deployment characteristics, remote re-programming for bug fixes, adapting to environment

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