软件定义网络的流量演进

IF 4.4 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Networks Pub Date : 2024-10-24 DOI:10.1016/j.comnet.2024.110852

Usman Ashraf , Adnan Ahmed , Stefano Avallone , Pasquale Imputato

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引用次数: 0

摘要

软件定义网络（SDN）通过优化集中决策，提供了前所未有的流量工程可能性。然而，网络流量会随着时间的推移而变化，并改变基础优化问题。频繁应用模型来反映流量演变会导致控制信息泛滥、流量重新路由和同步问题。本文探讨了在 SDN（软件定义网络）中最大限度地减少规则安装和修改、优化最大链路利用率（MLU）最小化和最大交换表空间利用率（MSTU）最小化这两个全局目标的优美流量演进问题。该问题使用混合整数线性规划（MILP）进行多目标优化。我们提供了 NP-Hardness（NP-Hardness）证明。然后，我们将问题重新表述为单目标问题，并提出了两种解决单目标问题的贪婪算法，即 MIRA-Im 和 MIRA-Im with Conflict Detection。仿真结果表明，与 MIRA-Im 和文献中的其他算法相比，带冲突检测的 MIRA-Im 有明显改善，特别是在已安装规则的数量（流量最多时可提高 80%）和流量表空间利用率（流量最多时可提高 55%）方面，而其他指标基本保持稳定。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Traffic evolution in Software Defined Networks

Software Defined Networking (SDN) offers unprecedented traffic engineering possibilities due to optimal centralized decision making. However, network traffic evolves over time and changes the underlying optimization problem. Frequent application of the model to reflect traffic evolution causes flooding of control messages, traffic re-routing and synchronization problems. This paper addresses the problem of graceful traffic evolution in SDNs (Software Defined Networks) minimizing rule installations and modifications, optimizing the global objectives of minimization of Maximum Link Utilization (MLU) and minimization of the Maximum Switch Table Space Utilization (MSTU). The problem is formulated as multi-objective optimization using Mixed Integer Linear Programming (MILP). Proof of NP-Hardness is provided. Then, we re-formulate the problem as a single-objective problem and propose two greedy algorithms to solve the single-objective problem, namely MIRA-Im and MIRA-Im with Conflict Detection, and experiments are performed to show the effectiveness of the algorithms in comparison to previous state of the art proposals. Simulation results show significant improvements of MIRA-Im with Conflict Detection, especially in terms of number of installed rules (with a gain till 80% with the highest number of flows) and flow table space utilization (with a gain till 55% with the highest number of flows), compared to MIRA-Im and other algorithms available in the literature, while the other metrics are essentially stable.

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来源期刊

Computer Networks 工程技术-电信学

CiteScore

10.80

自引率

3.60%

发文量

434

审稿时长

8.6 months

期刊介绍： Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.