Tabu Search
Fast accurate computation of large-scale IP traffic matrices from link loads
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Constraint-Based Local Search
Traffic Engineering for Metro Ethernet Based on Multiple Spanning Trees
ICNICONSMCL '06 Proceedings of the International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies
Principles of Constraint Programming
Principles of Constraint Programming
LS(graph & tree): a local search framework for constraint optimization on graphs and trees
Proceedings of the 2009 ACM symposium on Applied Computing
VL2: a scalable and flexible data center network
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Understanding data center traffic characteristics
Proceedings of the 1st ACM workshop on Research on enterprise networking
The nature of data center traffic: measurements & analysis
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Traffic engineering of multiple spanning tree routing networks: the load balancing case
NGI'09 Proceedings of the 5th Euro-NGI conference on Next Generation Internet networks
Best Multiple Spanning Tree in Metro Ethernet Networks
ICCEE '09 Proceedings of the 2009 Second International Conference on Computer and Electrical Engineering - Volume 02
Network traffic characteristics of data centers in the wild
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
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The size of the capacity of data centers have been growing significantly during the last years. Most data centers rely on switched Ethernet networks. A drawback of the Ethernet technology is that it relies on the spanning tree protocol (or variants of it) to select the links that are used to forward packets inside the data center. In this paper we propose a Constrained-Based Local Search optimization scheme that is able to efficiently compute the optimum spanning tree in large data center networks. Our technique exploits the division of the data center network in VLANs. We evaluate its performance based on traffic matrices collected in data center networks and show good improvements compared to the standard spanning tree protocol with up to 16 VLANs.