Dimensioning of the Store-and-Transfer WDM Network With Limited Node Storage Under the Sliding Scheduled Traffic Model
Dimensioning of the Store-and-Transfer WDM Network With Limited Node Storage Under the Sliding Scheduled Traffic Model
复制标题
滑动调度流量模型下有限节点存储存储转发WDM网络的规模划分
DOI：
10.1364/jocn.9.000275
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发表时间：
2017
影响因子：
5
通讯作者：
Hu Weisheng
中科院分区：
文献类型：
--
作者：
Feng Da;Sun Weiqiang;Zhang Xiaojian;Hu Weisheng
所谓的存储传输WDM网络(STWN)可以将数据存储在源存储中，并在波长没有冲突的最佳时间提供光路。因此，可以减少请求的阻塞，并且可以提高网络的资源利用率。在这项工作中，我们研究了STWN的规模，并提出了一种两步法来联合确定满足需求所需的波长数量和存储大小，该方法以具有截止日期、阻塞率和波长利用率的负载矩阵的形式给出。该方法将STWN建模为TDM网络，首先通过最大化每个周期的固定时隙数来获得所需的存储大小，然后根据所述时隙数计算所需的波长数。数值结果表明：远距离源节点和目的节点之间的高负载对所需的波长和存储空间有显著影响。例如，在24节点拓扑中，满足偏置负载矩阵所需的波长和存储可能比随机生成的负载矩阵多20%。在计算所需的波长数目时，我们的方法比传统的路由和波长分配(RWA)方法更好，因为基于TDM的模型支持分数负载。在24节点拓扑中，RWA可能比我们的方法多需要18%的波长。通过设置适中的存储容量，可以有效地提高波长利用率。当波长数和存储大小分别为29和274时，在24节点拓扑中，利用率可以达到0.9。我们还发现，在STWN的容量方面，波长与存储容量是等价的。例如，在24节点拓扑中，当波长数目和存储大小等于114和131时，阻塞率与波长数目和存储大小等于29和270的情况相同。
The so-called store-and-transfer WDM network (STWN) can store data in source storage and provision lightpaths at an optimal time when wavelengths are clear of conflicts. Consequently, blocking of requests can be reduced and resource utilization of the network can be improved. In this work, we investigate dimensioning of STWN and propose a two-step method to jointly determine the number of wavelengths and storage size required to satisfy the demand, which is given as a load matrix with a deadline, blocking rate, and wavelength utilization. The method models the STWN as a TDM network and first obtains the required storage size by maximizing the number of fixed time slots in each period, then calculates the required number of wavelengths with the number of time slots. Numerical results show the following: high load between far apart source and destination nodes has significant impact on the required wavelengths and storage. For instance, in a 24-node topology, 20% more wavelengths and storage may be required to satisfy a biased load matrix than a randomly generated one. When calculating the required number of wavelengths, ourmethod outperforms traditional routing and wavelength assignment (RWA), because the TDM-based model supports fractional load. In the 24-node topology, 18% more wavelengths may be required byRWA than by our method. By installing amoderate amount of storage,wavelength utilization can be effectively improved. With number of wavelengths and storage size equaling 29 and 274, in the 24-node topology, utilization can reach 0.9. We also find wavelength is equivalent with storage regarding capacity of a STWN. For instance, with number of wavelengths and storage size equaling 114 and 131, in the 24-node topology, the blocking rate is the same as with number of wavelengths and storage size equaling 29 and 270.