Cooperative Data-Optical InterNetworking: Distributed Multi-Layer Optimization

A. Elwalid, D. Mitra, Qiong Wang
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引用次数: 7

Abstract

We present a novel approach for joint optical network provisioning and IP traffic engineering, in which the IP and optical networks collaboratively optimize a combined objective of network performance and lightpath provisioning cost. We develop a framework for distributed multi-layer optimization. Our framework is built upon the IP-over-Optical (IPO) overlay model, where each network domain has a limited view of the other. Our formulation allows the two domains to communicate and coordinate their decisions through minimal information exchange. Our solution is based on a novel application of Generalized Bender’s Decomposition, which divides a difficult global optimization problem into tractable sub-problems, each solved by a different domain. The procedure is iterative and converges to the global optimum. We present case studies to demonstrate the efficiency and applicability of our approach in various networking scenarios. Our work builds a foundation for “multi-layer” grooming, which extends traditional grooming in the optical domain to data networks. The data networks are active participants in the grooming process with intelligent homing of data traffic to optical gateways.
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协同数据光互联网络:分布式多层优化
我们提出了一种联合光网络配置和IP流量工程的新方法,其中IP和光网络协同优化网络性能和光路配置成本的组合目标。我们开发了一个分布式多层优化框架。我们的框架建立在IP-over-Optical (IPO)覆盖模型之上,其中每个网络域对另一个网络域的视图有限。我们的公式允许两个领域通过最小的信息交换进行沟通和协调他们的决策。我们的解决方案是基于广义Bender分解的一种新应用,它将一个困难的全局优化问题划分为可处理的子问题,每个子问题由不同的域解决。该过程是迭代的,收敛于全局最优。我们通过案例研究来展示我们的方法在各种网络场景中的效率和适用性。我们的工作为“多层”梳理奠定了基础,将光学领域的传统梳理扩展到数据网络。数据网络是数据流量智能归巢到光网关的疏导过程的积极参与者。
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