Problem
Research questions and friction points this paper is trying to address.
online virtual network embedding
resource fragmentation
multi-dimensional complementary relationship
Pattern-Aware Virtual Network Embedding Optimization for Cloud Data Centers
🤖 AI Summary
本文针对云数据中心虚拟网络请求资源分配问题，提出基于模式匹配的在线虚拟网络嵌入方法，通过构建匹配规则最大化资源利用。
📝 Abstract
The network virtualization (NV) technology has enabled the sharing of multiple resources among virtual networks (VNs) in cloud data centers. One of the key challenges is to allocate resources in real-time for virtual network request (VNR), which is known as online virtual network embedding (VNE). However, the existing online VNE methods do not exploit the multi-dimensional complementary relationship among diverse VNRs, resulting in the fragmentation and waste of substrate resources. In this paper, we propose the pattern matching based online VNE approach by constructing appropriate matching rules among observed patterns to maximize resources utilization. We devise the clustering based VNRs quantization method and conduct rigorous study on the pattern combination filtering problem. Then, we utilize the column generation to solve it and construct the pattern matching rules. Based on the rules, we propose an online pattern matching VNE algorithm with linear worst-case complexity. Evaluation on a 106-server testbed using Alibaba production cluster trace dataset shows that our algorithm achieves close-to-offline performance and more accepted workloads that outperforms traditional designs by 25%-30%.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Pattern Matching
Online VNE
Clustering-based Quantization
Column Generation
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