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

在由能量和复杂性有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，在物理运动方面具有一定的动态性（例如：地震波，在地理区域上传播的声波）和延迟敏感性，保证实时重建。 此外，在这样的多终端设置中，“比特”不是信息的通用货币，因为多用户压缩和通信的分离是可悲的次优的。在这个项目中，这两个问题通过考虑一个新的动态压缩模型和一个新的基于多部图的延迟敏感信息分布式传输架构来解决，在这个新的压缩模型中，在某些节点上可用的信息是随着时间而变化的.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，在该项目中考虑的分布式信息传输的架构中，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。 使用这些机制，该项目的目标是实现一个自组织传感器网络启用一个新的架构，能够执行更有效的表示，通信和实时重建的分布式和延迟敏感的复杂信息领域比可能的任何系统今天。这一研究工作得到了教育工作的补充，以培训年轻的工程师，使他们能够熟练地建造、管理和开发这种大规模复杂的信息系统。在这个项目中考虑的具体问题是在课程，综合本科教育和研究工作，课程开发与分布式信号处理和通信课程的项目工作的发展。

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.