Randomized Signal Processing and Decentralized Coding for Robust Large-Scale Distributed Systems

不同领域的多项进步催化了从集中式架构向大规模网络中的分布式计算和协作通信方向的范式转变。对可伸缩性的需求对单个节点的成本和资源施加了限制，从而导致节点不精确、统计变化和不可靠。系统的基本挑战是通过从数字中获得强度来克服这些单独不可靠的组件，并形成一个强大、可靠、健壮并能够满足特定性能保证的网络。本提案旨在发展实现这一愿景所需的理论基础，重点关注随机信号处理和分散网络编码的重要作用，以解决两个重要的系统属性，本提案的基础是发展理论基础和建设性的解决方案，以理解随机信号处理和分散编码在由不可靠的、资源受限的元素组成的分布式系统中的作用。基于可扩展性、鲁棒性、节点成本和资源限制以及缺乏全局系统协调的重要考虑，我们建议探索以下重要研究领域：分布式存储和大规模网络中无处不在的数据访问建立在一类新的分散擦除码；通过新颖地使用随机网络编码和不协调的通信策略，在由廉价、未调谐的无线电和分布式发射机组成的网络中实现可靠通信；1.2更广泛的影响研究旨在探索随机信号处理和分散编码的基本局限性，并将这些理论结构转化为大规模网络中高效实用算法的设计和部署。我们的工作将适用于广泛的应用，从计算机科学应用，如点对点网络到系统理论辅助容错电路设计。在实现这项技术转让的过程中，我们将大力利用伯克利无线研究中心（BWRC）的实施能力，以及伯克利无线基金会中心的理论实力。为了延续加州大学伯克利分校的丰富传统，这项创新研究的理论和算法结果将被纳入伯克利分校的EECS课程。将继续强调本科生研究助理的参与，以帮助培养学术界和工业界信号处理和通信领域的未来领导者。

Multiple advances in diverse fields have catalyzed a paradigm shift away from centralized architectures and in the direction of distributed computing and cooperative communications in large-scale networks. The requirement for scalability imposes constraints on the cost and resources of individual nodes, resulting in nodes that are imprecise, statistically varying, and unreliable. The fundamental systems challenge is to overcome these individually unreliable components by deriving strength from numbers, and to form a network that is strong, reliable, robust, and capable of meeting specific performance guarantees. This proposal seeks to develop the theoretical foundations needed to realize this vision, focusing on the vital role of randomized signal processing and decentralized network coding to address two important system attributes, scalability and robustness.1.1 Intellectual MeritsThe basis of this proposal is to develop both the theoretical foundations and constructive solutions for understanding the role of randomized signal processing and decentralized coding in distributed systems comprised of unreliable, resource-constrained elements. Motivated by the important considerations of scalability, robustness, node cost and resource limitations, and a lack of global system coordination, we propose to explore the following important research areas:. Distributed storage and ubiquitous access to data in large-scale networks founded on a new class of decentralized erasure codes;. Reliable communication in networks comprised of cheap, untuned radios and distributed transmitters through the novel use of randomized network coding and uncoordinated communication strategies;. Distributed data representation and summarization based on randomized multiresolution transforms and randomized in-network signal processing.1.2 Broader ImpactOur research is aimed at exploring the fundamental limits of randomized signal processing and decentralized coding, and the technology transfer of these theoretical constructs into the design and deployment of efficient and practical algorithms for large-scale networks. Our work will apply to a broad range of applications, ranging from computer science applications like peer-to-peer networks to system-theory-aided fault tolerant circuit design. In instrumenting this technology transfer, we will heavily leverage the implementational capabilities of the Berkeley Wireless Research Center(BWRC), as well as the theoretical prowess of the Berkeley Wireless Foundations Center. In continuing with a rich tradition at UC Berkeley, the theoretical and algorithmic results coming out of this innovative research will be integrated into the EECS curricula at Berkeley. The involvement of undergraduate research assistants will continue to be emphasized, helping to educate future leaders in signal processing and communications for both academia and industry.