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: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=544714
• 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.

我的研究项目涉及大规模优化方法的理论研究，并将其应用于通信网络和人工智能中出现的不同工程问题。它建立在过去六年取得的一些成果的基础上，其中一些成果涉及国家或国际合作。研究方向分为三个：（i）分解方法和元启发式的理论进展； (ii) 解决通信网络中出现的问题的应用，例如混合线速光网络的设计、通过节能和可生存的逻辑拓扑等进行节能设计和管理、提供多播流量，以及 (iii) 应用在人工智能方面。第一个轴的动机是解决更大的优化问题，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点播应用的使用量的稳定增长有关，这导致通信网络中具有挑战性的优化问题。解决方案始终需要考虑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交换/路由的流量量）。此外，还必须控制能源消耗，以避免未来几年出现不可持续的电力需求。事实上，技术和运营效率的进步速度必须快于流量的增长速度。在运营效率方面，我们建议优化混合线速网络的设计和管理，提高带宽利用率以降低能耗，并优化组播流量的配置和保护。