Dimensioning of the Store-and-Transfer WDM Network With Limited Node Storage Under the Sliding Scheduled Traffic Model

Abstract

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, our method 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 by RWA than by our method. By installing a moderate 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.

A Partial Store-and-Forward Scheduling Method for Inter-Datacenter Bulk Data Transfers

“…To reduce the high-speed read/write burden on the storage systems, the authors in [21] assumed that only sources could store data. Patel et al compared SnF with Advance Reservation (AR) [22], [23].…”