Collaborative Research: Fault Tolerance Analysis and Design of Clustered Sensor Networks

协作研究：集群传感器网络容错分析与设计

• 批准号: 0727305
• 负责人: Yu Ding
• 金额: $ 16.13万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0727305&HistoricalAwards=false
• 关键词: Collaborative; Research; Fault; Tolerance; Analysis

The objective of this collaborative research project between the University of Iowa and Texas A&M University is to provide solutions that enable efficient fault-tolerance analysis of clustered sensor networks and further establish a design method for achieving a robust and reliable system. The approach is to explore efficient solutions by considering the cluster structures embedded in most real-world sensor networks. A number of decomposition-based algorithms will be designed for clustered sensor networks to substantially reduce the computational complexity in fault tolerance analysis. In addition, efficient Monte Carlo sampling and heuristics methods will be applied for design evaluation and optimization of sensor networks. The models and algorithms will be validated and tested using both wireless sensor networks in laboratory environments and real-world distributed sensor systems in industry.If successful, the project will enhance the understanding of the robust and reliable operations of distributed sensor networks. This fundamental research will contribute broadly to the applications of radio-frequency identification networks used in manufacturing enterprises and other types of wireless sensor networks used for logistics and transportation control. The application of fault tolerance analysis and design methods will lead to reliable operations and reduce the occurrence of false positives in distributed sensor networks. Meanwhile, the collaborative nature of this research will provide students a multidisciplinary training and will bring industrial perspective to the universities. It will contribute to the infrastructure for research and education by upgrading the current research labs, motivating students to pursue careers in relevant areas, and engaging teachers from minority-serving high schools. The resulting methodologies from this project will be broadly disseminated through publications, seminars, and workshops.

爱荷华大学和德克萨斯A＆M大学之间的合作研究项目的目的是提供解决方案，以实现群集传感器网络的有效耐故障分析，并进一步建立一种设计方法，以实现可靠和可靠的系统。该方法是通过考虑嵌入大多数真实世界传感器网络中的群集结构来探索有效的解决方案。许多基于分解的算法将设计用于聚类的传感器网络，以大大降低容错分析中的计算复杂性。此外，有效的蒙特卡洛采样和启发式方法将应用于传感器网络的设计评估和优化。这些模型和算法将在实验室环境中使用无线传感器网络和行业中现实世界的分布式传感器系统进行验证和测试。如果成功，该项目将增强对分布式传感器网络强大而可靠的操作的理解。这项基本研究将在制造企业和其他类型的无线传感器网络中用于物流和运输控制的无线传感器网络的射频标识网络的应用。容错分析和设计方法的应用将导致可靠的操作，并减少分布式传感器网络中误报的发生。同时，这项研究的协作性质将为学生提供多学科培训，并将工业视角带给大学。它将通过升级当前的研究实验室，激励学生从事相关领域的职业，并吸引来自少数派服务的高中的教师，从而为研究和教育的基础设施做出贡献。该项目的最终方法将通过出版物，研讨会和研讨会大致传播。