Site Search
Computer Science

Photos

Dr. Scott GoodwinDr. Scott Goodwin
Dr. Scott Goodwin
Christie Ezeife, Ph.D.Dr. Christie Ezeife
Dr. Christie Ezeife
Dr. Ziad Kobti lecturingDr. Ziad Kobti
Dr. Ziad Kobti
Jessica Chen, Ph.D.Dr. Jessica Chen
Dr. Jessica Chen
Windsor WaterfrontWindsor Waterfront Park
Windsor Waterfront Park
Dr. Luis RuedaDr. Luis Rueda
Dr. Luis Rueda
Arunita Jaekel, Ph.D.Dr. Arunita Jaekel
Dr. Arunita Jaekel
Dr. Robert KentDr. Robert Kent
Dr. Robert Kent
Alioune Ngom, Ph.D.Dr. Alioune Ngom
Dr. Alioune Ngom
Xiaobu Yuan, Ph.D.Dr. Xiaobu Yuan
Dr. Xiaobu Yuan
Imran Ahmad, Ph.D.Dr. Imran Ahmad
Dr. Imran Ahmad
Lambton TowerLambton Tower
Lambton Tower
Robin Gras, Ph.D.Dr. Robin Gras
Dr. Robin Gras

Real-Time Energy Pirce-Aware Anycast RWA for Scheduled Lightpath Demands in Optical Data Center Networks

Add this event into your calendar using the iCAL format
  • Tue, 09/19/2017 - 8:30am - 9:30am




Real-Time Energy Price-Aware Anycast RWA for Scheduled Lightpath Demands in Optical Data Center Networks

MSc Thesis Defense by:

Karan Neginhal

Date:  Tuesday, September 19, 2017
Time:  8:30 am – 9:30 am
Location: 3105, Lambton Tower

Abstract: The energy consumption of the data center networks and the power consumption associated with transporting data to the users is considerably large, and it constitutes a significant portion of their costs. Hence, development of energy efficient schemes is very crucial to address this problem. Our research considers the fixed window traffic allocation model and the anycast routing scheme to select the best option for the destination node. Proper routing schemes and appropriate combination of the replicas can take care of the issue for energy utilization and at the same time help diminish costs for the data centers. We have also considered the real-time pricing model (which considers price changes every hour) to select routes for the lightpaths. Hence, we propose an ILP to handle the energy-aware routing and wavelength assignment (RWA) problem for fixed window scheduled traffic model, with an objective to minimize the overall electricity costs of a datacenter network by reducing the actual power consumption, and using low-cost resources whenever possible.

Thesis Committee:

Internal Reader:  Dr. Stephanos Mavromoustakos
External Reader:  Dr. Animesh Sarker
Advisor:              Dr. Arunita Jaekel
Chair:                 Dr. Dan Wu



csgradinfo@uwindsor.ca
(519)253-3000


See More: