Design of reliable and efficient communication and computing systems: architecture, code design, and optimization

三个重要的技术趋势构成了现代信息经济的基础：无处不在的宽带数字通信的出现，我们从巨大的数据集中提取有用和可操作信息的能力的巨大进步，以及根据摩尔定律计算能力的持续扩展。在每个这些领域的当前挑战的激励下，并从这些领域汲取见解和最新进展，我们将解决三个协同研究项目。第一个是架构理解，第二个是算法设计，第三个是更广泛的应用。第一个项目涉及如何最好地为流数据构建通信系统。无线行业预测，在未来十年中，容量需要增加1000倍。但是，尽管许多重要性日益增加的应用涉及实时内容交付，但这种数据的流性质与大多数通信系统的基于块的设计不匹配。我们将开发这些系统中的可靠性和延迟之间的权衡的基本限制，也将开发所需的编码方法来实现这些限制。我们的第二个项目利用数学优化技术来开发新的纠错码解码算法。我们的方法有可能解决一些长期存在的问题，具有重要的工业意义的纠错。在我们的期末专题中，我们将探讨大规模计算系统的功率感知设计和操作。通过将排队和无线路由技术的知识与对电路和计算机体系结构的洞察相结合，我们将开发用于大型数据中心的任务调度和电源管理的新算法。

Three important technological trends underlie the modern information economy: the emergence of ubiquitous broadband digital communications, great advances in our ability to extract useful and actionable information from enormous data sets, and the continued scaling of computational power according to Moore's Law. Motivated by current challenges in each of these areas, and drawing together insights and recent advances from across these areas, we will tackle three synergistic research projects. The first is in architectural understanding, the second in algorithmic design, the third in broader applications. The first project concerns how best to architect communication systems for streaming data. The wireless industry is forecasting the need for a 1000-fold increase in capacity over the next decade. But, while many applications of increasing importance involve real-time content delivery, the streaming nature of this data is ill-matched to the block-based designs of most communication systems. We will develop fundamental limits on the tradeoff between reliability and delay in these systems and will also develop the required coding approaches to achieve those limits. Our second project draws upon techniques of mathematical optimization to develop novel algorithms for decoding error-correcting codes. Our approach has the potential to resolve some long-standing issues of great industrial importance in error correction. In our final project we will investigate power-aware design and operation of large-scale computational systems. By combining knowledge of queuing and techniques of wireless routing with insight into circuits and computer architecture, we will develop new algorithms for task scheduling and power management in large-scale data centers.