PortLand: a scalable fault-tolerant layer 2 data center network fabric
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
The nature of data center traffic: measurements & analysis
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Proceedings of the ACM SIGCOMM 2010 conference
Hedera: dynamic flow scheduling for data center networks
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
Network traffic characteristics of data centers in the wild
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
ICTCP: Incast Congestion Control for TCP in data center networks
Proceedings of the 6th International COnference
Better never than late: meeting deadlines in datacenter networks
Proceedings of the ACM SIGCOMM 2011 conference
MicroTE: fine grained traffic engineering for data centers
Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
Utility-Based Resource Allocation in Wireless Networks
IEEE Transactions on Wireless Communications
Fundamental design issues for the future Internet
IEEE Journal on Selected Areas in Communications
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In this work we consider a relatively large and highly dynamic data center network in which flows have small interarrival times and different demands for the network resources. Taking into account the properties and specifics of such networks we consider the problem of flow placement, i.e. assignment of an outgoing port for flows at each hop from source to destination. Using the characteristics of modern data centers from previous measurement studies, in this work we first simulate the flow allocation using several algorithms with and without global knowledge. We find that in all settings local forwarding decisions are almost as good as decisions made with global information at hand. This finding enables us to propose a fully distributed mechanism that relies only on local knowledge and allows to achieve fair and demand aware flow allocation in the data center network. The mechanism has low complexity and performs better than naive random flow allocation.