CAREER: New Architectures for Distributed Compression and Communication of Delay-Sensitive Information in Sensor Networks

在由能量和复杂性受限的廉价传感器组成的传感器网络中，底层信息场是分布式的，在物理运动(例如，地震波、声波在地理区域上传播)方面具有一定的动力学特性，并且对延迟敏感，需要实时重建。此外，在这种多终端环境中，“比特”不是信息的通用货币，因为多用户压缩和通信的分离令人遗憾地不是最优的。在该项目中，通过考虑一种新的动态压缩模型和一种用于时延敏感信息的分布式传输的新的多方图结构来解决这两个问题。在这种新的压缩模型中，某些节点上的可用信息是随时间变化的。该模型被称为具有前馈的信源编码。这在信息压缩问题中引发了一种全新的动力。此外，在本项目考虑的分布式信息传输体系结构中，多部图被用作分布式压缩和分布式通信之间的离散接口。这导致了基于多终端传感器的信息处理系统的模块化设计。利用这些机制，本项目的目标是实现一个自组织的传感器网络，该网络具有一种新的体系结构，能够比目前任何系统都能够执行更有效的分布式和延迟敏感的复杂信息场的表示、通信和实时重建。这一研究工作还得到了一项教育努力的补充，该努力旨在培训年轻工程师，使其能够熟练地构建、管理和开发这种大规模复杂的信息系统。这个项目考虑的具体问题是课程中项目工作的发展，本科教育和研究的综合努力，以及带有分布式信号处理和通信课程的课程开发。

In sensor networks comprised of energy- and complexity-limited inexpensive sensors, the underlying information field is distributed, endowed with certain dynamics in terms of physical movement (for example: seismic, acoustic waves traveling over a geographical region) and delay-sensitive that warrant real-time reconstruction. Further, in such multi-terminal settings, ``bit'' is not the universal currency of information, as the separation of multiuser compression and communication is sadly suboptimal. In thisproject these two issues are addressed by considering a new dynamic compression model and a new multi-partite graph-based architecture for distributed transmission of delay-sensitive information.In this new compression model the information available at certain nodes is changing as a function of time. This model is referred to as source coding with feedforward. This induces a completely new dynamism inthe information compression problem. Further, in the architecture for transmission of distributed information considered in this project, multi-partite graphs are used as a discrete interface between distributed compression and distributed communication. This leads to a modular design of multi-terminal sensor-based information processing systems. Using these mechanisms, the goal of this project is to realize a self-organizing sensor network enabled with a new architecture that is capable of performing more efficient representation, communication and real-time reconstruction of distributed and delay-sensitive complex information fields than possible by any system today. This research effort is complemented by an educational effort to train young engineers to become skilled in construction, management and development of such massively complex information systems. The specific issues considered in this project are development of project work in the courses, integrated undergraduate education and research effort, and curriculum development with a course on distributed signal processing and communication.