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

该补助金为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）决策的调查提供资金。这些决定将被认为是在一个综合的方式，并特别强调将同时对传感器网络的三个理想的属性。这些属性是能量效率、容错性以及通信与计算权衡的利用。将开发旨在同时捕获这些特性并最小化能耗和/或最大化有效传感器网络寿命的非线性和非线性数学模型。这些模型将提供足够的灵活性，用于同时和/或单独做出上述战略-战术-作战决策。在方法方面，将制定有效的解决方案算法，在合理的时间框架内提供高质量的解决方案。这些算法将包括利用传感器网络的结构和操作的特殊性，在一个有效的方式，如果成功的方法，这批的结果将在无线传感器网络的理论研究引入新的途径，并提供新的分析模型和解决方法的重要实际问题，在这个发展中的领域。研究结果将为传感器网络提供理想的设计和运行特性，使这些不寻常的约束网络的好处最大化。此外，一个网络规划框架，强调不同的决策水平之间的相互关系下的独特的传感器网络属性的保护伞将被开发。这一框架将帮助我们理解决策过程中的动态变化，其中不同层次决策（战略-战术-作战）的时间框架并不像传统环境中那样不同。拟议的工作也将有助于整数和非线性优化问题的计算工具和方法。

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.