Sensors: Models and Algorithms for Efficient Design and Operation of Wireless Sensor Networks

这笔资金用于调查无线传感器网络中有效和高效的部署(战略)、拓扑发现(战术)和数据路由(操作)决策。这些决定将以综合的方式加以考虑，并将特别强调与传感器网络有关的三个理想属性。这些属性是能效、容错和利用通信与计算的权衡。将开发旨在同时捕获这些特征并最小化能量消耗和/或最大化有效传感器网络寿命的整数和非线性数学模型。这些模型将提供足够的灵活性，用于同时和/或单独作出上述战略-战术-作战决策。在方法论方面，将开发有效的求解算法，在合理的时间范围内提供高质量的解决方案。这些算法将包括有效地利用传感器网络结构和操作的特殊性的方法。如果成功，这项拨款的结果将为无线传感器网络理论的研究引入新的途径，并为这一发展中的重要实际问题提供新的分析模型和解决方法。研究结果将为传感器网络提供理想的设计和运行特性，从而使这些异常受限的网络的收益最大化。此外，还将制定一个网络规划框架，强调在独特传感器网络属性的保护伞下不同决策层之间的相互关系。这一框架将帮助我们理解在不同层次的决策(战略-战术-行动)的时间框架与传统情况下不同的情况下所涉及的动态。拟议的工作还将有助于为整数和非线性优化问题提供计算工具和方法。

This grant provides funding for an investigation of effective and efficient deployment (strategic), topology discovery (tactical), and data routing (operational) decisions in wireless sensor networks. These decisions will be considered in an integrated fashion and special emphasis will be given on three desirable attributes regarding sensor networks simultaneously. These attributes are energy efficiency, fault tolerance, and exploitation of communication versus computation trade-offs. Integer and nonlinear mathematical models that aim to capture these characteristics simultaneously and minimize the energy consumption and/or maximize effective sensor network lifespan will be developed. These models will provide sufficient flexibility to be used for making the above strategic-tactical-operational decisions both simultaneously and/or individually. On the methodological side, efficient solution algorithms that provide high quality solutions in reasonable time frames will be developed. These algorithms will include approaches that utilize the specificities of sensor network structures and operations in an effective way.If successful, the results of this grant will introduce new avenues of research in the theory of wireless sensor networks and provide novel analytical models and solution methodologies for important practical problems in this developing area. The results will provide desirable design and operation characteristics for sensor networks so that the benefits from these rather unusually constrained networks are maximized. In addition, a network-planning framework that underlines the interrelationships among different decision levels under the umbrella of unique sensor network attributes will be developed. This framework will help us understand the dynamics involved in making decisions where time frames for different level decisions (strategic-tactical-operational) are not as different as in the traditional contexts. The proposed work will also contribute to the computational tools and methodologies available for integer and nonlinear optimization problems.