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RINGS: Resilient Delivery of Real-Time Interactive Services Over NextG Compute-Dense Mobile Networks

RINGS：通过 NextG 计算密集型移动网络弹性交付实时交互服务

基本信息

批准号：
2148315
负责人：
Andreas Molisch
金额：
$ 90万
依托单位：
University of Southern California
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-05-01 至 2025-04-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2148315&HistoricalAwards=false
关键词：
RINGS Resilient Delivery Real Time

项目摘要

Real-time interactive (RTI) services are anticipated to be the ‘’next big thing” in information technology, merging the areas of sensing, computation, and communications that until recently have been treated separately. In traditional systems, these building blocks are not optimized to work with each other, and particularly not in real-time, constraining the type of services that can be offered. RTIs require real-time aggregation of distributed data streams onto edge/cloud compute servers that can process data as soon as it is generated. The goal of this project is to develop a general mathematical framework as well as concrete algorithms to provide such RTI services with guaranteed latencies. The results benefit the US economy by enabling more efficient, more reliable, and more resilient automation schemes, e.g., for smart factories and farms, as well as improved augmented/virtual reality. The interdisciplinary nature of the project benefits the students working on this project; a detailed plan for outreach and increasing participation of underrepresented groups strengthens the impact of the work.The project designs a general mathematical framework and concrete algorithms for reliable and resilient Real-time interactive (RTI) systems. In a first thrust, the project explores the limits of delivering latency-critical services reliably. The establishment of the reliable network stability region provides bounds on how much offered RTI traffic a network can support under the best of all algorithms. A packet-lifetime-based queuing model serves as the basis of Lyapunov-drift-inspired control algorithms that not only account for the packet delay but also takes cost such as energy consumption into account. A second thrust of the project develops robust NextG network control algorithms that can adapt to dynamic network states. Integration of the approaches in the first two thrusts under a common Lyapunov drift control framework is an avenue to enable reliable RTI service delivery, which is verified by the implementation of the algorithm on a Platform for Advanced Wireless Research (PAWR) community testbed.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

实时交互（RTI）服务预计将成为信息技术的“下一件大事”，它将传感、计算和通信领域合并在一起，直到最近这些领域一直被单独对待。在传统系统中，这些构建块没有被优化以相互协作，特别是不是实时的，从而限制了可以提供的服务类型。 RTI需要将分布式数据流实时聚合到边缘/云计算服务器上，这些服务器可以在数据生成后立即处理数据。这个项目的目标是开发一个通用的数学框架，以及具体的算法，以提供这样的RTI服务与保证的延迟。这些结果通过实现更高效、更可靠和更有弹性的自动化方案，使美国经济受益，例如，智能工厂和农场，以及改进的增强/虚拟现实。该项目的跨学科性质使从事该项目的学生受益;一个详细的外联计划和增加代表性不足的群体的参与加强了工作的影响。该项目设计了一个通用的数学框架和具体的算法，用于可靠和弹性的实时交互（RTI）系统。在第一个推力中，该项目探索了可靠地提供延迟关键服务的限制。可靠网络稳定区域的建立提供了在所有算法中最好的算法下网络可以支持多少提供的RTI业务的界限。基于数据包生命周期的排队模型作为Lyapunov漂移启发的控制算法的基础，不仅考虑了数据包延迟，而且还考虑了能量消耗等成本。该项目的第二个重点是开发强大的NextG网络控制算法，可以适应动态网络状态。在共同的李雅普诺夫漂移控制框架下，前两个推力中的方法的集成是实现可靠的RTI服务交付的途径，该算法在先进无线研究平台（PAWR）上的实现得到了验证该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.