Paper Info
Title
MiceTrap: Scalable traffic engineering of datacenter mice flows using OpenFlow.
Abstract
Datacenter network topologies are inherently built with enough redundancy to offer multiple paths between pairs of end hosts for increased flexibility and resilience. On top, traffic engineering (TE) methods are needed to utilize the abundance of bisection bandwidth efficiently. Previously proposed TE approaches differentiate between long-lived flows (elephant flows) and short-lived flows (mice flows), using dedicated traffic management techniques to handle elephant flows, while treating mice flows with baseline routing methods. We show through an example that such an approach can cause congestion to short-lived (but not necessarily less critical) flows. To overcome this, we propose MiceTrap, an OpenFlow-based TE approach targeting datacenter mice flows. MiceTrap employs scalability against the number of mice flows through flow aggregation, together with a software-configurable weighted routing algorithm that offers improved load balancing for mice flows.
Year
Venue
Keywords
2013
IM
IP networks,computer centres,resource allocation,telecommunication network routing,telecommunication network topology,telecommunication traffic,MiceTrap framework,OpenFlow-based TE approach,bisection bandwidth,data center network topologies,datacenter mice flow congestion,flow aggregation,load balancing improvement,long-lived elephant flows,scalable traffic engineering,short-lived mice flows,software-configurable weighted routing algorithm,Datacenter Networks,OpenFlow,Routing,Software-defined Networks,Traffic Engineering
Field
DocType
Citations 
Traffic generation model,Load balancing (computing),Computer science,Computer network,Network topology,Bisection bandwidth,Redundancy (engineering),OpenFlow,Traffic engineering,Distributed computing,Scalability
Conference
2
PageRank 
References 
Authors
0.40
0
3
Name
Order
Citations
PageRank
Ramona Trestian131929.51
Gabriel-Miro Muntean21880143.82
Kostas Katrinis310219.41