NETS-NOSS: Routing and Topology Design of Hierarchical Sensor Networks

NETS-NOSS：分层传感器网络的路由和拓扑设计

• 批准号: 0519554
• 负责人: Mark Shayman
• 金额: $ 41.8万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0519554&HistoricalAwards=false
• 关键词: NETS; NOSS; Routing; Topology; Design

A hierarchical sensor network is a sensor network that contains relay nodes appropriately distributed throughout the network. The relays are advantaged nodes that are connected by wireless transmission to form a backbone. Transmission in the backbone may use a different frequency and have longer range than the transmissions between sensor nodes. The backbone nodes may also have larger energy supplies than the sensor nodes. A message travels through one or more sensor nodes until it reaches a relay. Then it is transmitted in the backbone until it reaches a sink (destination) node. The presence of the backbone limits traffic among the sensor nodes thereby reducing interference and prolonging battery life.In order to design hierarchical sensor networks, it is necessary to determine how many relays are required, where they should be located, to which relay a sensor message should be directed, and what route the message should follow. This project pursues two lines of investigation to address these issues. The first develops analogies between sensor networks and the theory of electrostatics. It is applicable to networks with high sensor density. The discrete problem of routing is replaced by the continuous problem of finding a forwarding direction (vector field) at each point in the plane in such a way that a performance index (e.g., energy efficiency) is optimized. The optimal vector field can be obtained by solving a pair of partial differential equations that are analogous to Maxwell's equations in electrostatics. Making this approach distributed and applicable to hierarchical networks are important problems to be solved. The second line of investigation is concerned with the development of theory and algorithms for obtaining hierarchical sensor networks that have desirable topological properties such as k-connectivity and d-hop dominant backbones. Graph theory techniques are applied here.The project is expected to result in algorithms for the design and operation of sensor networks that have high throughput, are energy efficient, and avoid passing messages through regions in which communication may be unreliable due to environmental conditions. Potential applications include sensing of forest fires.

分层传感器网络是一种包含适当分布在整个网络中的中继节点的传感器网络。中继是通过无线传输连接以形成主干的有利节点。主干网中的传输可以使用不同的频率，并且比传感器节点之间的传输具有更长的传输距离。骨干节点也可能比传感器节点有更大的能量供应。消息经过一个或多个传感器节点，直到到达中继。然后在主干网中传输，直到到达接收（目的）节点。骨干网络的存在限制了传感器节点之间的通信，从而减少了干扰并延长了电池寿命。为了设计分层传感器网络，有必要确定需要多少个继电器，它们应该位于何处，传感器消息应该定向到哪个继电器，以及消息应该遵循什么路由。为了解决这些问题，本项目进行了两条调查路线。第一部分将传感器网络与静电理论进行类比。适用于传感器密度较大的网络。将路由的离散问题替换为在平面上的每个点上寻找转发方向（向量场）的连续问题，从而使性能指标（例如能源效率）得到优化。最优矢量场可以通过求解一对类似于静电学中的麦克斯韦方程组的偏微分方程得到。使这种方法具有分布式和适用于分层网络是需要解决的重要问题。研究的第二条线是关于理论和算法的发展，以获得具有理想拓扑特性的分层传感器网络，如k-连通性和d-hop主导骨干。图论技术在这里被应用。该项目预计将为传感器网络的设计和操作提供算法，这些算法具有高吞吐量，节能，并避免通过可能由于环境条件而导致通信不可靠的区域传递消息。潜在的应用包括对森林火灾的感知。