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

CNS Core: Small:On Parallelizing Optical Network Design Problems:Towards Network Optimization as a Service

CNS 核心：小型：关于并行光网络设计问题：走向网络优化即服务

基本信息

批准号：
1907142
负责人：
George Rouskas
金额：
$ 43.91万
依托单位：
North Carolina State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-10-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1907142&HistoricalAwards=false
关键词：
CNS Core Small Parallelizing Optical

项目摘要

Planning, deploying, and engineering the networks that make up the Internet infrastructure involve complex problems generically referred to as "network design" problems. Effective and efficient solutions to network design problems are crucial to the operation and economics of the Internet and its ability to support critical and reliable education, government, commercial and science-related communication services. Network design gets increasingly difficult as networks grow larger. This research project aims to address this challenge by investigating new approaches for tackling network design problems for large networks in a scalable manner. This project aims to make contributions that will lead to a paradigm shift in efficient, scalable solutions to network design problems. The project approach will be to develop parallel solutions that are applicable to a wide range of problems by exploiting a feature common to all, namely, that the optimization process incorporates both a routing aspect and a resource allocation aspect. The research plan is to partition the solution space across the routing dimension into a set of mutually exclusive and collectively exhaustive subspaces, which may be explored in parallel as independent subproblems. Specifically, each subspace corresponds to a fixed routing path for each node pair, and the corresponding subproblem involves searching only for an optimal resource assignment along the given paths. Consequently, subproblems are independent of each other and may be solved in parallel by leveraging available cluster/cloud computing resources to speed up the overall execution time. The approach will look at intelligent ways to prune the set of subspaces that practically need to be explored. The algorithmic results of this project will be integrated into an open-source tool that will be made available to students, researchers, and practitioners. The research will lay the foundation for a future "Network Optimization as a Service (NOaaS)" model for network optimization to be delivered remotely and on demand as a cloud service.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.

规划、部署和设计构成Internet基础设施的网络涉及通常称为“网络设计”问题的复杂问题。网络设计问题的有效和高效解决方案对互联网的运行和经济及其支持关键和可靠的教育、政府、商业和科学相关通信服务的能力至关重要。随着网络规模的扩大，网络设计变得越来越困难。该研究项目旨在通过研究以可扩展的方式解决大型网络的网络设计问题的新方法来解决这一挑战。该项目旨在为有效、可扩展的网络设计问题解决方案的范式转变做出贡献。项目方法将是开发并行的解决方案，适用于广泛的问题，通过利用一个共同的特征，即，优化过程结合了路由方面和资源分配方面。研究计划是将整个路径维上的解空间划分为一组相互排斥和集体穷举的子空间，这些子空间可以作为独立的子问题并行地进行探索。具体来说，每个子空间对应于每个节点对的固定路由路径，相应的子问题只涉及沿给定路径搜索最优资源分配。因此，子问题彼此独立，可以通过利用可用的集群/云计算资源来并行解决，从而加快整体执行时间。该方法将着眼于智能的方法来修剪实际需要探索的子空间集。这个项目的算法结果将被整合到一个开源工具中，供学生、研究人员和从业者使用。该研究将为未来的“网络优化即服务（NOaaS）”模型奠定基础，该模型将以云服务的形式远程按需交付网络优化。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。