ITR/Collaborative Research: Intelligent Topology Control and Energy Provisioning for Wireless Video Sensor Networks

无线视频传感器网络有着重要的应用。除了传统的监视和监控应用之外，这些网络最近还发现了许多新的应用，以增强国家安全，减少安全漏洞对国家关键基础设施的影响，提高政府预防、检测、响应和从人为和灾难性事件中恢复的能力。该项目将研究设计用于长时间监视的无线视频传感器网络。因此，本项目将探讨网络生命周期的几种定义，考虑到保持活动所需节点的百分比（对应于网络覆盖）以及节点基于其位置的不同优先级。pi将考虑影响网络寿命的几个重要因素，包括基站放置和网络连接拓扑。对视频传感器节点的功耗行为的分析表明，通信消耗的能量明显多于任何其他节点活动。通过监控和调整发射机的功率水平和网络流量路由拓扑，可以有效地控制这种功耗。通过智能基站布局和视频传感器节点之间的网络连接来调整网络拓扑结构，优化视频传感器节点的发射功率，从而延长网络寿命。我们发现，在计算几何领域开发的技术和算法可以帮助我们很好地理解问题的本质，并确定困难所在。更重要的是，这些方法使我们能够开发非常有用的性能界限来表征无线视频传感器网络的特性，这是进一步开发定制解决方案的基础。在这项研究中，我们计划进一步探索计算几何中的算法和技术，以研究拓扑控制（基站放置，时间拓扑，流量路由）对网络性能的影响，并表征无线视频传感器网络的基本特性。提出的研究内容包括基站放置和多跳路由的联合问题、基站放置约束的考虑以及动态变化的网络拓扑。除了理论研究外，还将开发一个软件工具包来实现本研究中开发的智能拓扑控制技术。拟议的研究还将促进研究机构的研究和教育的结合，并将对教育产生重大影响。参与该项目的学生将有机会探索解决资讯科技问题的创新方法。此外，这项研究的一些结果将被纳入pi机构的无线和传感器网络高级专题课程。

Wireless video sensor networks have important applications. In addition to their traditional surveillance and monitoring applications, these networks have recently found many new applications for enhancing national security, reducing the impact of security breaches on the nation's critical infrastructure, and improving the government's ability to prevent, detect, respond to, and recover from both man-made and catastrophic events. This project will examine a wireless video sensor network that is designed for surveillance over an extended period of time. Consequently, this project will explore several definitions for network lifetime, taking into account the percentage of nodes required to remain alive (corresponding to network coverage) and the different priorities of nodes based on their locations. The PIs will consider several important factors that affect network lifetime, including base-station placement and network connectivity topology. An analysis of power dissipation behavior at video sensor nodes suggests that communication consumes significantly more energy than any other node activity. This power consumption can be controlled effectively by monitoring and adjusting the power level of the transmitter and the network traffic routing topology. By adjusting the topology of the network through intelligent base station placement and network connectivity among the video sensor nodes, we can optimize the transmitter power of video sensor nodes, thus extending network lifetime. We have found that techniques and algorithms developed in the field of computational geometry can help us obtain a good understanding of the nature of the problem and identify where difficulties lie. More important, such approaches enable us to develop very useful performance bounds to characterize properties of wireless video sensor networks, which is the basis to further development of customized solutions. In this research, we plan to further explore algorithms and techniques from computational geometry to study the impact of topology control (base-station placement, temporal topology, traffic routing) on network performance and characterize basic properties for wireless video sensor networks. Proposed research components include, among others, joint problems of base-station placement and multihop routing, considerations of constraints on base-station placement, and dynamic varying network topology. In addition to theoretical study, a software toolkit will also be developed to implement the intelligent topology control techniques that are developed in this research.The proposed research will also foster the integration of research and education at the investigators' institutions and will have a significant impact on education. Students working on this project will have a unique opportunity to explore creative approaches and innovative methods for solving IT problems. In addition, some results from this research will be incorporated into an advanced topics class on wireless and sensor networks at the PIs' institutions.