A scalable traffic engineering technique in an SDN‐based data center network
A scalable traffic engineering technique in an SDN‐based data center network
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DOI：
10.1002/ett.3268
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发表时间：
2018-02
影响因子：
3.6
通讯作者：
M. Bastam;M. Sabaei;Ruhollah Yousefpour
中科院分区：
文献类型：
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作者：
M. Bastam;M. Sabaei;Ruhollah Yousefpour
数据中心最近已成为一种公共基础设施，其中包括大量服务器和托管各种应用程序和基于云的服务。本文提出了一种软件定义的数据中心网络流量工程的动态方法，该方法有助于在计算复杂度可容忍的情况下设计最优的需求路径映射。为了达到本研究的目的，我们使用线性规划来定义问题陈述，然后将问题建模为基于路径的多商品流。为了降低时间复杂度，首先使用分解技术将问题模型分解为较小的子问题，然后应用并行化技术(即多核计算和OpenMP)同时求解。然后，利用合适的迭代算法快速收敛子问题的解，从而得到主问题的答案。仿真结果表明，与已有的一些方案相比，该方案的求解时间有了很大的提高。此外，串联实现该方法可以得到一个最优解，该最优解比一般(未分解的LP模型)方法所需的时间要短得多。
Data center has recently emerged as a common infrastructure that includes numerous servers and host diversity of applications and cloud‐based services. In this paper, a dynamic method is proposed for traffic engineering in software‐defined data center networks helping to design an optimal demand‐path mapping with a tolerable computational complexity. To achieve the aim of this study, we used a linear programming to define the problem statement and then modeled the problem as a Path‐based multicommodity flow. To reduce time complexity, first, a decomposition technique is used to divide the problem model into smaller subproblems, which are then solved simultaneously by applying parallelizing techniques (ie, multiple‐core computing and OpenMP). Next, a suitable iterative algorithm is utilized to quickly converge subproblem solutions leading to an answer to the master problem. Simulation results show that solving time is considerably improved compared with a number of reported schemes devoted to this topic. In addition, implementing the proposed method serially yields an optimum solution, which takes significantly shorter time to reach than that of the generic (the LP model that is not decomposed) approach.