...
首页> 外文期刊>Journal of network and systems management >COVE: Co-operative Virtual Network Embedding for Network Virtualization
【24h】

COVE: Co-operative Virtual Network Embedding for Network Virtualization

机译:COVE:用于网络虚拟化的协作虚拟网络嵌入

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Network virtualization provides a promising solution for next-generation network management by allowing multiple isolated and heterogeneous virtual networks to coexist and run on a shared substrate network. A long-standing challenge in network virtualization is how to effectively and efficiently map these virtual nodes and links of heterogeneous virtual networks onto specific nodes and links of the shared substrate network, known as the Virtual Network Embedding (VNE) problem. Existing centralized VNE algorithms and distributed VNE algorithms both have advantages and disadvantages. In this paper, a novel cooperative VNE algorithm is proposed to coordinate centralized and distributed algorithms and unite their respective advantages and specialties. By leveraging the learning technology and topology decomposition, autonomous substrate nodes entrusted with detailed mapping solutions cooperate closely with the central controller with a global view and in charge of general management to achieve a successful embedding process. Besides a topology-aware resource evaluation mechanism and customized mapping management policies, Bloom filter is elaborately introduced to synchronize the mapping information within the substrate network, instead of flooding which generates massive communication overhead. Extensive simulations demonstrate that the proposed cooperative algorithm has acceptable and even better performance in terms of long-term average revenue and acceptance ratio than previous algorithms.
机译:通过允许多个隔离的异构虚拟网络共存并在共享的基础网络上运行,网络虚拟化为下一代网络管理提供了有希望的解决方案。网络虚拟化中的一个长期挑战是如何有效地将这些虚拟节点和异构虚拟网络的链接映射到共享基板网络的特定节点和链接上,这被称为虚拟网络嵌入(VNE)问题。现有的集中式VNE算法和分布式VNE算法都各有利弊。本文提出了一种新型的协同VNE算法,以协调集中式和分布式算法,并结合各自的优势和特色。通过利用学习技术和拓扑分解,委托了详细的制图解决方案的自治基板节点与具有全局视野的中央控制器紧密协作,并负责总体管理,以实现成功的嵌入过程。除了具有拓扑感知的资源评估机制和自定义的映射管理策略外,还精心引入了Bloom过滤器,以同步基板网络中的映射信息,而不是泛洪,后者会产生大量的通信开销。大量的仿真表明,与以前的算法相比,该算法在长期平均收益和接受率方面具有可接受的甚至更好的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号