NeTS: Small: Generalized Submodular Optimization for Integrated Networked Sensing Systems

NeTS：小型：集成网络传感系统的广义子模块优化

• 批准号: 1017701
• 负责人: Yixin Chen
• 金额: $ 44.32万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1017701&HistoricalAwards=false
• 关键词: NeTS; Small; Generalized; Submodular; Optimization

Wireless sensor networks are evolving from specialized platforms to shared infrastructure for multiple applications. Shared sensor networks offer flexibility, adaptivity, and cost-effectiveness through dynamic resource allocation among different applications. Shared sensor networks face the critical need for optimizing Quality of Monitoring (QoM) subject to resource constraints. The emerging QoM optimization problems in shared sensor networks are computationally challenging due to their nonlinear, discrete, and dynamic nature. This project exploits a key property known as submodularity that many QoM attributes of physical phenomena exhibit. This project develops efficient and theoretically sound distributed approaches for QoM optimization, through a novel integration of submodular optimization in a market-based approach. It further studies online algorithms which can quickly adapt to network and application dynamics, partition-based algorithms that scale effectively for large-scale networks, and new optimization algorithms that can accommodate the optimization of energy consumption and heterogenous networks. Expected results of this project include theory, algorithms, and software for managing and optimizing a new generation of integrated networked sensing systems with high societal and environmental impact. The project also deploys an integrated sensor network for environmental monitoring in Tyson Research Center of Washington University for environmental and ecological research. This study promotes interdisciplinary collaboration with environmental and biological scientists, as well as outreach activities for high-school students.

无线传感器网络正在从专用平台发展为多应用的共享基础设施。共享传感器网络通过在不同应用之间动态分配资源，提供灵活性、自适应性和成本效益。共享传感器网络面临的关键需求，优化质量监测（库姆）的资源约束。共享传感器网络中出现的库姆优化问题由于其非线性、离散性和动态性而在计算上具有挑战性。这个项目利用了一个关键的属性，称为子模块化，许多物理现象的库姆属性展示。该项目通过将子模块优化新颖地集成到基于市场的方法中，开发出高效且理论上合理的分布式方法来进行库姆优化。它进一步研究了能够快速适应网络和应用动态的在线算法，能够有效扩展大规模网络的基于分区的算法，以及能够适应能耗和异构网络优化的新优化算法。 该项目的预期成果包括管理和优化新一代集成网络传感系统的理论、算法和软件，这些系统具有很高的社会和环境影响。该项目还在华盛顿大学泰森研究中心部署了一个用于环境监测的集成传感器网络，用于环境和生态研究。这项研究促进了与环境和生物科学家的跨学科合作，以及高中学生的外联活动。