CAREER: Local Information Based Distributed Optimization of Resources in Large-Scale Adhoc and Sensor Networks

职业：大规模自组织网络和传感器网络中基于本地信息的分布式资源优化

• 批准号: 0448316
• 负责人: Koushik Kar
• 金额: $ 40.05万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0448316&HistoricalAwards=false
• 关键词: CAREER; Local; Information; Based; Distributed

Efficient usage of bandwidth and/or energy is necessary for the success of a majority of ad-hoc and sensor network applications. This project focuses on the development of distributed bandwidth/energy optimization algorithms that require only local network topology or state information, and yet guarantee a performance close to the global or local optimum. More specifically, this project involves the development of distributed node wakeup, medium access control, routing and flow control algorithms that optimize (exactly or approximately) the throughput or lifetime of the network, while posing minimal overhead of communication on the individual nodes. The project objectives also include understanding the fundamental trade-offs between optimization accuracy and communication complexity, so that the appropriate level of accuracy can be chosen based on the network and application characteristics.The questions considered in this project are crucially important for the efficient management of ad-hoc and sensor networks in a wide range of application scenarios, including environmental data gathering, military and relief operations, and health monitoring. Moreover, although the project is focused only on large-scale ad-hoc and sensor networks, the results of this research are expected to influence a larger body of science and engineering, including optimization theory, stochastic control and distributed algorithms. The expected outcomes of this project also include a publicly available simulation tool, a junior museum exhibit, and a graduate level course on distributed optimization methods in networking. A conscious effort will be made towards engaging women and other under-represented groups in the research and educational programs related to this project.

带宽和/或能量的有效利用对于大多数ad-hoc和传感器网络应用的成功是必要的。该项目的重点是分布式带宽/能量优化算法的开发，只需要本地网络拓扑或状态信息，但保证性能接近全局或局部最优。更具体地说，该项目涉及分布式节点唤醒，介质访问控制，路由和流量控制算法的开发，优化（精确或近似）的吞吐量或网络的生命周期，同时对各个节点的通信开销最小。该项目的目标还包括了解优化精度和通信复杂性之间的基本权衡，以便可以根据网络和应用特性选择适当的精度水平。该项目中考虑的问题对于在广泛的应用场景中有效管理ad-hoc和传感器网络至关重要，包括环境数据收集，军事和救援行动以及健康监测。此外，虽然该项目只关注大规模的ad-hoc和传感器网络，但这项研究的结果预计将影响更大的科学和工程领域，包括优化理论，随机控制和分布式算法。该项目的预期成果还包括一个公开的仿真工具，一个初级博物馆展览，以及一个研究生水平的网络分布式优化方法课程。将有意识地努力让妇女和其他代表性不足的群体参与与该项目有关的研究和教育方案。