Intelligent Resource Allocation Strategies for Next Generation Optical Networks

下一代光网络的智能资源分配策略

• 批准号: RGPIN-2015-05641
• 负责人: Jaekel, Arunita
• 金额: $ 1.75万
• 依托单位: University of Windsor
• 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=613665
• 关键词: Intelligent; Resource; Allocation; Strategies; Next

Optical networks are undergoing significant changes, fueled by the rapid growth of the internet. The next generation optical network infrastructure will need to be made more customizable and responsive to user/application requirements. Recent advances in key optical transport technologies such as flexible wavelength division multiplexing (WDM) grid, support for traffic heterogeneity, as well as the emergence of software defined optics (SDO) can be used to address many of these challenges. In the future, software will play an increasingly important role in controlling network components and allocating resources based on a wide range of parameters such as bandwidth, quality of transmission (QoT), energy consumption, as well as reliability and security needs of different applications. This will give rise to a tremendous need for developing sophisticated and adaptive resource allocation strategies and robust control mechanisms that can be deployed in the control and management plane of next generation optical network infrastructure. This research will focus on the development of innovative mechanisms for customizable resource allocation, and recovery from component failures as well as protecting data from malicious attacks. We will apply novel Operations Research (OR) techniques that exploit the inherent special structure of certain design problems to obtain optimal or near-optimal solutions. Recent work in this area has yielded promising results for network optimization; however, the full potential for the application of such methodologies is yet to be investigated properly. In addition to optimizing traditional network resources such as computing/processing power of nodes and capacity/bandwidth of the links, specialized algorithms to meet the following design objectives will be developed. 1. Intelligent scheduling techniques for energy efficient optical network design. 2. Routing and wavelength allocation strategies that minimize the risk of service disruption due to signal interference and malicious attacks. 3. Enhanced fault tolerance and survivability schemes for reliable communication in optical grids. 4. Optimized energy and bandwidth allocation for mixed line rate (MLR) networks.

在互联网快速发展的推动下，光网络正在经历重大变革。下一代光网络基础设施将需要更加可定制，并对用户/应用需求做出更好的响应。关键光传输技术的最新进展，如灵活的波分复用（WDM）网格，支持流量异构性，以及软件定义光学（SDO）的出现，可以用来解决这些挑战中的许多。未来，软件将在控制网络组件和基于各种参数分配资源方面发挥越来越重要的作用，这些参数包括带宽、传输质量（QoT）、能耗以及不同应用的可靠性和安全性需求。这将引起对开发可以部署在下一代光网络基础设施的控制和管理平面中的复杂的和自适应的资源分配策略和鲁棒的控制机制的巨大需求。 这项研究将侧重于开发可定制资源分配的创新机制，从组件故障中恢复，以及保护数据免受恶意攻击。我们将应用新的运筹学（OR）技术，利用某些设计问题的固有特殊结构，以获得最佳或接近最佳的解决方案。最近在这一领域的工作取得了可喜的成果，网络优化，但是，这种方法的应用的全部潜力还有待适当的调查。除了优化传统的网络资源，如节点的计算/处理能力和链路的容量/带宽外，还将开发满足以下设计目标的专门算法。 1.用于节能光网络设计的智能调度技术。 2.路由和波长分配策略，最大限度地降低由于信号干扰和恶意攻击而导致的服务中断风险。 3.光网格中可靠通信的增强容错和生存性方案。 4.混合线速（MLR）网络的优化能量和带宽分配。