DeViNE：一种去中心化虚拟网络嵌入算法
DeViNE: A Decentralized Virtual Network Embedding Algorithm
AI总结：
本文提出去中心化虚拟网络嵌入算法DeViNE，通过多领导者本地嵌入与领导者选举机制解决集中式VNE的可扩展性、单点故障和DoS攻击问题，在接受率和收益成本比上均优于现有方法。
摘要：
虚拟网络嵌入（VNE）是一种将虚拟网络映射到物理网络基础设施上的技术，使多个虚拟网络能够共存于共享的物理网络上。以往的工作主要集中于实现集中式VNE算法，这些算法存在可扩展性不足和鲁棒性较差的问题。本项目旨在实现一种去中心化的虚拟网络嵌入算法，以应对网络虚拟化中的挑战，例如可扩展性、单点故障和DoS攻击。所提出的方法包括从物理节点中选出L个领导者，并在每个领导者的本地网络中使用诸如BFS之类的简单算法嵌入虚拟网络请求（VNR）。然后，该算法使用领导者选举机制来确定成本最低且收益最高的节点，并将嵌入结果传播给其他领导者。通过利用去中心化，我们提高了解决方案的可扩展性和鲁棒性。此外，我们通过将我们的完全去中心化算法与现有方法进行比较来评估其有效性。我们的算法在接受率方面比对比方法高出12%，并将收益成本比提高了约21%。
英文摘要：
Virtual Network Embedding (VNE) is a technique for mapping virtual networks onto a physical network infrastructure, enabling multiple virtual networks to coexist on a shared physical network. Previous works focused on implementing centralized VNE algorithms, which suffer from lack of scalability and robustness. This project aims to implement a decentralized virtual network embedding algorithm that addresses the challenges of network virtualization, such as scalability, single point of failure, and DoS attacks. The proposed approach involves selecting L leaders from the physical nodes and embedding a virtual network request (VNR) in the local network of each leader using a simple algorithm like BFS. The algorithm then uses a leader-election mechanism for determining the node with the lowest cost and highest revenue and propagates the embedding to other leaders. By utilizing decentralization, we improve the scalability and robustness of the solution. Additionally, we evaluate the effectiveness of our fully decentralized algorithm by comparing it with existing approaches. Our algorithm performs $12\%$ better in terms of acceptance rate and improves the revenue-to-cost ratio by roughly $21\%$ to compared approaches.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
