基于遗传算法的资源感知虚拟网络并行嵌入

Zibo Zhou, Xiaolin Chang, Yang Yang, Lin Li
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引用次数: 9

摘要

在底层物理基础设施中嵌入虚拟网络请求,即所谓的虚拟网络嵌入(VNE)问题,已经引起了广泛的研究兴趣。一个现实的场景可能需要嵌入同时到达的多个VN请求(MVNE)(批到达)。现有的启发式MVNE方法既没有考虑多个VNR嵌入之间的协调,也没有考虑到可用的物理资源同时嵌入所有到达的VNR。本文考虑了可用物理资源可能不足以满足批处理中所有vnr物理资源需求的情况下的MVNE问题。我们探索应用遗传算法(GA)来处理MVNE问题。我们提出了一种算法来决定哪些vnr可以被映射到一起。进行了大量的模拟,以评估所提出的算法在VN接受率和服务提供商的长期收入方面的性能。
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Resource-Aware Virtual Network Parallel Embedding Based on Genetic Algorithm
Embedding virtual network requests in an underlying physical infrastructure, the so-called virtual network embedding (VNE) problem, has attracted significant research interests already. A realistic scenario might entail embedding multiple VN requests (MVNE) that arrive simultaneously (batch arrivals). The existing heuristic MVNE approaches neither consider the coordination among multiple VNR embeddings nor embed all the arriving VNRs simultaneously considering the available physical resources. This paper considers the MVNE problem in the scenario where the available physical resources may not be sufficient to satisfy the physical resource demands of all the VNRs in the batch. We explore applying genetic algorithm (GA) to handle the MVNE problem. We propose an algorithm to decide which VNRs could be mapped together. Extensive simulations are carried out to evaluate the performance of the proposed algorithms in terms of the VN acceptance ratio and the long-term revenue of the service provider.
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