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

在不同领域的多个进步已经催化了从集中式架构到大规模网络中的分布式计算和协作通信的方向的范式转变。可伸缩性的要求对各个节点的成本和资源施加了约束，导致节点不精确，统计变化和不可靠。基本的系统挑战是通过从数字中获得力量来克服这些单独不可靠的组件，并形成一个强大，可靠，鲁棒并且能够满足特定性能保证的网络。该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式网络编码在解决两个重要系统属性方面的重要作用，可扩展性和鲁棒性。1.1智力优点本提案的基础是为理解分布式系统中随机信号处理和分散编码的作用开发理论基础和建设性解决方案。由不可靠的、资源受限的元素组成的系统。出于对可扩展性、鲁棒性、节点成本和资源限制的重要考虑，以及缺乏全局系统协调，我们建议探索以下重要研究领域：分布式存储和无处不在的大规模网络中的数据访问建立在一类新的分散式擦除码上。通过随机网络编码和非协调通信策略的新颖使用，在由廉价的未调谐无线电和分布式发射机组成的网络中实现可靠通信;基于随机多分辨率变换和随机网络信号处理的分布式数据表示和摘要。1.2更广泛的影响我们的研究旨在探索随机信号处理和分散编码的基本限制，以及这些理论结构的技术转移到大规模网络的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，从计算机科学的应用，如对等网络系统理论辅助容错电路设计。在仪器这种技术转让，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。在继续在加州大学伯克利分校丰富的传统，理论和算法的结果出来的创新研究将被整合到EECS课程在伯克利分校。本科生研究助理的参与将继续得到强调，有助于教育未来的领导者在信号处理和通信的学术界和工业界。

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.