Back to Search Start Over

Adaptive Open-Shop Scheduling for Optical Interconnection Networks

Authors :
Van, Dung Pham
Fiorani, Matteo
Wosinska, Lena
Chen, Jiajia
Van, Dung Pham
Fiorani, Matteo
Wosinska, Lena
Chen, Jiajia
Publication Year :
2017

Abstract

This paper deals with resource management in optical interconnection networks. It first proposes an optical resource management framework as a platform to develop and evaluate efficient solutions for multipoint-to-multipoint optical communication systems with a centralized controller. The paper then focuses on studying the optical resource scheduling (ORS) problem as a core element in the framework by applying the classical open-shop scheduling theory. The ORS problem can therefore be solved by adopting the existing preemptive and nonpreemptive open-shop scheduling algorithms. In an optical network with nonnegligible reconfiguration delay, a preemptive algorithm may incur high reconfiguration overhead resulting in worse performance compared to the nonpreemptive strategy. Motivated by this fact, this paper proposes an adaptive open-shop scheduling (AOS) algorithm that dynamically decides the optimal scheduling strategy according to traffic condition and system parameters, such as reconfiguration delay, nonpreemptive approximation ratio, and number of involved optical interfaces. The solution is assessed by means of an analytical model that allows to quantify the network performance in terms of packet delay and potential energy savings obtained by the sleep mode operation. As a possible application scenario, the inter- and intrarack optical interconnection networks in data centres are considered. Analytical results demonstrate how the proposed AOS outperforms the nonpreemptive and preemptive scheduling strategies for typical configurations used in data center networks. In addition, the reconfiguration delay and wake-up time of optical devices are identified as performance-determining factors.<br />QC 20170620

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1234929527
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1109.JLT.2017.2695078