课题基金 / 基金详情

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

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
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-05-01 至 2011-08-31

项目摘要

项目成果

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中文摘要
翻译
带宽和/或能源的有效利用是大多数ad-hoc和传感器网络应用成功的必要条件。该项目专注于分布式带宽/能量优化算法的开发,该算法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、媒体访问控制、路由和流量控制算法的开发,这些算法优化(完全或近似地)网络的吞吐量或生命周期,同时在单个节点上构成最小的通信开销。项目目标还包括理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程序特征选择适当的精度级别。本项目所考虑的问题对于在广泛的应用场景(包括环境数据收集、军事和救济行动以及健康监测)中有效管理特设网络和传感器网络至关重要。此外,虽然该项目只关注大规模的自组织和传感器网络,但这项研究的结果有望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可用的模拟工具,一个青少年博物馆展览,以及一个关于网络中分布式优化方法的研究生课程。将有意识地努力使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。
英文摘要
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.
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