Large Scale Optimization with Applications in Communication Networks

大规模优化及其在通信网络中的应用

• 批准号: 36426-2012
• 负责人: Jaumard, Brigitte
• 金额: $ 2.48万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=593006
• 关键词: Large; Scale; Optimization; Applications; Communication

My research program deals with theoretical research on large scale optimization methods with applications to different engineering problems arising in communication networks and artificial intelligence. It is built upon some of the results obtained in the previous 6 years, with some involving national or international collaborations. There are three research axes: (i) theoretical advances on decomposition methods and meta-heuristics; (ii) applications to problems arising in communication networks such as the design of mixed-line-rate optical networks, energy-efficient designs and management through, e.g., energy-efficient and survivable logical topologies, provisioning of multicast traffic and (iii) applications in artificial intelligence. The first axis is motivated by the need to solve ever larger optimization problems, with guarantees on the quality of the generated solutions. The applications of the second axis are related to the continued growth of Internet traffic, and the steady increase in the usage of on-demand applications which leads to challenging optimization problems in communication networks. Solutions always need to take into account the capacity limits for some of the existing technology (e.g., processing speed of the electronic routers vs. amount of the traffic to be switched/routed). As well, energy consumption must be tamed in order to avoid unsustainable power requirements in the next coming years. Indeed, the rate of advances in technological and operational efficiency must increase faster than the rate of traffic growth. In terms of operational efficiency, we propose to optimize the design and management of mixed-line rate networks, to enhance the bandwidth usage in order to reduce the energy consumption, and to optimize the provisioning and the protection of the multicast traffic.

我的研究计划介绍了有关大规模优化方法的理论研究，并应用了在通信网络和人工智能中引起的不同工程问题的应用。它建立在过去6年中获得的一些结果，其中一些涉及国家或国际合作。有三个研究轴：（i）关于分解方法和元映射的理论进步； （ii）在通信网络中出现的问题的应用，例如混合利率光学网络的设计，节能设计和管理通过，例如，能源效率和可生存的逻辑拓扑，多播流量的提供以及（III）应用在人工智能中的应用。第一个轴是出于解决越来越多的优化问题的需要，并保证生成的解决方案的质量。第二轴的应用与互联网流量的持续增长以及按需应用程序的使用稳定增加有关，这导致了通信网络中有挑战的优化问题。解决方案始终需要考虑到某些现有技术的容量限制（例如，电子路由器的处理速度与要切换/路由的流量数量）。同样，必须驯服能源消耗，以避免在未来几年内使用不可持续的功率要求。实际上，技术和运营效率的进步速度必须比交通增长率更快。在运营效率方面，我们建议优化混合线速率网络的设计和管理，以增强带宽的用法，以减少能源消耗，并优化对多播流量的配置和保护。