权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

NeTS: Small: Optimal Delivery of Augmented Information Services Over Next-Generation Cloud Networks

NeTS：小型：通过下一代云网络优化增强信息服务交付

基本信息

批准号：
1816699
负责人：
Andreas Molisch
金额：
$ 49.98万
依托单位：
University of Southern California
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2022-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1816699&HistoricalAwards=false
关键词：
NeTS Small Optimal Delivery Augmented

项目摘要

Moving data and services from local computers into the cloud has been one of the major trends in information technology over the past years. This trend has upended the computer industry, and provides benefits, for example, in terms of more efficient use of computing resources (which can now be shared by different users) and centralized software updates (which increase security). In a related trend, most information such as video is now stored in the cloud, and delivered to the users on demand, replacing local storage methods such as DVDs and DVRs. Augmented information (AgI) services, an important extension of that trend, combine content delivery and computation, for example, when the original video source data are processed on their way to the destination to create augmented reality, telepresence, real-time surveillance, or industrial automation. This project investigates how such joint communication and computation can be done in the most efficient way in terms of energy, cost, or other criteria that might be important to the consumer or provider. Transmitting information over large distances is usually via multiple "hops", i.e., it goes from the source via several intermediate nodes to the destination. For example, the information could be routed from a source in Los Angeles via Denver, Dallas, Atlanta, to New York. The necessary processing could be done at any of those nodes, or might be distributed among different nodes with different associated costs. Since processing can make the files larger or smaller (e.g., transcoding functions), this also has an impact on the communication cost to the next nodes. This project investigates the fundamental performance limits of this type of network and develops practical algorithms that can do the routing and assignment of processing resources in an efficient way. The goals of the project are to: (i) develop a universal model for AgI services, as a generalization of traditional information services; (ii) formalize the AgI service distribution problem (AgI-SDP) for the quasi-static case, where placement of information and assignment of resources changes only slowly and provide a complexity classification for each major service class and design fast approximation algorithms for the AgI-SDP in its different categories; (iii) develop formulations and algorithms that dynamically adjust the configuration of AgI services in response to unknown changes in cloud network conditions and service demands; and (iv) validate the algorithms by experimentation on testbeds at Bell Labs.The services covered by the AgI model range from network services (e.g., 5G network slices) to automation services (e.g., smart buildings, industrial automation, smart transportation), to augmented experience services (e.g., virtual reality, immersive video), and efficient design of such systems thus has great impact on the economy, ecology (energy savings) and user experience of a wide variety of services. Optimization of such distributed systems also enhance the robustness of computation and communication infrastructure to disruptions from natural disasters and other events. The project includes a strong outreach and education program including having undergraduates and graduate students perform experiments at the project collaborator's state-of-the-art laboratory at Bell Labs.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.

过去几年，将数据和服务从本地计算机转移到云端一直是信息技术的主要趋势之一。这种趋势颠覆了计算机行业，并带来了好处，例如，更有效地使用计算资源（现在可以由不同的用户共享）和集中的软件更新（提高了安全性）。在一个相关的趋势中，大多数信息，如视频，现在都存储在云端，并按需交付给用户，取代了本地存储方式，如dvd和dvr。增强信息（AgI）服务是这一趋势的重要延伸，它将内容交付和计算相结合，例如，当原始视频源数据在到达目的地的途中进行处理时，可以创建增强现实、远程呈现、实时监控或工业自动化。这个项目研究了如何在能源、成本或其他可能对消费者或供应商重要的标准方面以最有效的方式完成这种联合通信和计算。远距离传输信息通常要经过多个“跳”，也就是说，信息从源处经过几个中间节点到达目的地。例如，信息可以从洛杉矶的一个来源经丹佛、达拉斯、亚特兰大发送到纽约。必要的处理可以在这些节点中的任何一个完成，也可以在具有不同相关成本的不同节点之间进行分配。由于处理可以使文件变大或变小（例如，转码功能），这也会影响到与下一个节点的通信成本。该项目研究了这类网络的基本性能限制，并开发了实用的算法，可以有效地进行处理资源的路由和分配。该项目的目标是：(i)为AgI服务开发一个通用模型，作为传统信息服务的概括；（ii）形式化准静态情况下的AgI服务分布问题（AgI- sdp），其中信息的放置和资源的分配变化缓慢，并为每个主要服务类别提供复杂性分类，并为AgI- sdp的不同类别设计快速逼近算法；（iii）根据云网络条件和业务需求的未知变化，开发动态调整AgI服务配置的公式和算法；（iv）通过在贝尔实验室的测试台上进行实验来验证算法。AgI模型涵盖的服务范围从网络服务（如5G网络切片）到自动化服务（如智能建筑、工业自动化、智能交通），再到增强体验服务（如虚拟现实、沉浸式视频），这些系统的高效设计对各种服务的经济、生态（节能）和用户体验都有很大影响。这种分布式系统的优化还增强了计算和通信基础设施对自然灾害和其他事件中断的鲁棒性。该项目包括一个强大的推广和教育计划，包括让本科生和研究生在项目合作者位于贝尔实验室的最先进的实验室进行实验。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。