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首页> 外文期刊>IEEE Transactions on Communications >Design and Provision of Traffic Grooming for Optical Wireless Data Center Networks
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Design and Provision of Traffic Grooming for Optical Wireless Data Center Networks

机译：光学无线数据中心网络的流量梳理的设计和提供

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摘要

Traditional wired data center networks (DCNs) suffer from cabling complexity, lack flexibility, and are limited by the speed of digital switches. In this paper, we alternatively develop a top-down traffic grooming (TG) approach to the design and provisioning of mission-critical optical wireless DCNs. While switches are modeled as hybrid optoelectronic cross-connects, links are modeled as wavelength division multiplexing capable free-space optic channels. Using the standard TG terminology, we formulate the optimal mixed-integer TG problem considering the virtual topology, flow conversation, connection topology, non-bifurcation, and capacity constraints. Thereafter, we develop a fast yet efficient sub-optimal solution, which grooms mice flows (MFs), mission-critical flows (CFs), and forward on predetermined rack-to-rack (R2R) lightpaths. On the other hand, elephant flows (EFs) are forwarded over dedicated server-to-server express lightpaths whose routes and capacity are dynamically determined based on the availability of wavelength and capacity. To prioritize the CFs, we consider low and high-priority queues and analyze the delay characteristics such as waiting times, maximum hop counts, and blocking probability. As a result of grooming, the sub-wavelength traffic and adjusting the wavelength capacities, numerical results show that the proposed solutions can achieve significant performance enhancement by utilizing the bandwidth more efficiently, completing the flows faster than delay sensitivity requirements, and avoiding the traffic congestion by treating EFs and MFs separately.
机译：传统的有线数据中心网络（DCN）布线复杂，缺乏灵活性，并受到数字交换机速度的限制。在本文中，我们可以替代地开发一种自顶向下的流量疏导（TG）方法，以设计和配置关键任务光学无线DCN。交换机被建模为混合光电交叉连接，而链路被建模为具有波分复用能力的自由空间光通道。使用标准TG术语，考虑虚拟拓扑，流对话，连接拓扑，非分叉和容量约束，我们制定了最佳的混合整数TG问题。此后，我们开发了一种快速而有效的次优解决方案，该解决方案可以修饰鼠标流（MF），关键任务流（CF）并在预定的机架到机架（R2R）光路上转发。另一方面，大象流（EF）通过专用的服务器到服务器快速光路径转发，其路径和容量是根据波长和容量的可用性动态确定的。为了确定CF的优先级，我们考虑了低优先级队列和高优先级队列，并分析了延迟特征，例如等待时间，最大跳数和阻塞概率。通过对亚波长流量进行梳理和调整波长容量的结果，数值结果表明，所提出的解决方案可以通过更有效地利用带宽，比延迟灵敏度要求更快地完成流量以及避免流量拥塞来显着提高性能。通过分别处理EF和MF。

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