网络大规模分布式压缩与分散信息路由研究
On Large Scale Distributed Compression and Dispersive Information Routing for Networks
摘要：
本文研究大型网络中的分布式信源编码问题。对分布式编码的常规方法的实际部署构成存在威胁的主要障碍是解码器复杂度随着源的数量和编码速率的指数增长。这种复杂性的增长使得许多传统方法甚至对于中等规模的网络也不切实际。在本文中，我们提出了一种新的解码范式，大规模分布式压缩解码器的复杂性是明确控制在设计过程中。我们的方法的核心是一个模块，称为“位子集选择器”，其作用是明智地提取一个适当的子集，每个单独的源解码接收到的位。我们提出了一个实用的设计策略，基于确定性退火（DA）的联合设计的系统组件，使直接优化的解码器的复杂性失真的权衡，从而所需的可扩展性。我们还指出了大规模分布式压缩问题和传感器网络中的相关问题之间的直接联系，即相关源的分散信息路由。这使我们能够扩展大规模分布式压缩的背景下提出的设计原则，设计高效的路由器，最低成本的相关源在整个网络中的通信。在真实数据集和合成数据集上的实验提供了比传统方法大幅度增益的证据。
英文摘要：
This paper considers the problem of distributed source coding for a large network. A major obstacle that poses an existential threat to practical deployment of conventional approaches to distributed coding is the exponential growth of the decoder complexity with the number of sources and the encoding rates. This growth in complexity renders many traditional approaches impractical even for moderately sized networks. In this paper, we propose a new decoding paradigm for large scale distributed compression wherein the decoder complexity is explicitly controlled during the design. Central to our approach is a module called the "bit-subset selector" whose role is to judiciously extract an appropriate subset of the received bits for decoding per individual source. We propose a practical design strategy, based on deterministic annealing (DA) for the joint design of the system components, that enables direct optimization of the decoder complexity-distortion trade-off, and thereby the desired scalability. We also point out the direct connections between the problem of large scale distributed compression and a related problem in sensor networks, namely, dispersive information routing of correlated sources. This allows us to extend the design principles proposed in the context of large scale distributed compression to design efficient routers for minimum cost communication of correlated sources across a network. Experiments on both real and synthetic data-sets provide evidence for substantial gains over conventional approaches.
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