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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=654428
• 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.

由于互联网的快速增长，光网络正在发生重大变化。下一代光网基础架构将需要更具自定义性，并响应用户/应用程序要求。关键光学传输技术的最新进展，例如灵活波长多路复用（WDM）网格，对流量异质性的支持以及软件定义光学（SDO）的出现，可以使用来应对许多这些挑战。将来，软件将在控制网络组件和基于广泛参数（例如带宽，传输质量（QOT），能耗以及不同应用程序的可靠性和安全需求）的广泛参数中发挥越来越重要的作用。这将产生巨大的需求，以开发复杂和自适应的资源分配策略和可靠的控制机制，这些机制可以部署在下一代光学网络基础结构的控制和管理平面中。我们将应用新颖的操作研究（OR）技术来利用某些设计问题的固有结构来获得最佳或近乎最佳的解决方案。该领域的最新工作为网络优化带来了令人鼓舞的结果。但是，应用此类方法的全部潜力尚未得到适当研究。除了优化传统的网络资源（例如节点的计算/处理能力以及链接的容量/带宽）外，还将开发专门的算法来满足以下设计目标。*** 1。能源有效的光网络设计的智能调度技术。 *** 2。路由和波长分配策略最大程度地减少了由于信号干扰和恶意攻击而导致的服务中断的风险。 *** 3。在光网格中可靠通信的可靠通信的增强的容错性和生存率方案。 *** 4。混合线速率（MLR）网络的优化能量和带宽分配。