Flow-based programmable networks must continuously monitor performance metrics, such as link utilization, in order to quickly adapt forwarding rules in response to changes in workload. However, existing monitoring solutions either require special instrumentation of the network or impose significant measurement overhead.
In this paper, we propose a push-based approach to performance monitoring in flow-based networks, where we let the network inform us of performance changes, rather than query it ourselves on demand. Our key insight is that control messages sent by switches to the controller carry information that allows us to estimate performance. In OpenFlow networks, PacketIn and FlowRemoved messages--sent by switches to the controller upon the arrival of a new flow or upon the expiration of a flow entry, respectively--enable us to compute the utilization of links between switches. We conduct a) experiments on a real testbed, and b) simulations with real enterprise traces, to show accuracy, and that it can refresh utilization information frequently (e.g., at most every few seconds) given a constant stream of control messages. Since the number of control messages may be limited by the properties of traffic (e.g., long flows trigger sparse FlowRemoved's) or by the choices made by operators (e.g., proactive or wildcard rules eliminate or limit PacketIn's), we discuss how our proposed passive approach can be combined with active approaches with low overhead.
[1]
Rob Sherwood,et al.
Can the Production Network Be the Testbed?
,
2010,
OSDI.
[2]
Minlan Yu,et al.
Online Measurement of Large Traffic Aggregates on Commodity Switches
,
2011,
Hot-ICE.
[3]
Aditya Akella,et al.
Extensible and Scalable Network Monitoring Using OpenSAFE
,
2010,
INM/WREN.
[4]
Nick McKeown,et al.
OpenFlow: enabling innovation in campus networks
,
2008,
CCRV.
[5]
Jia Wang,et al.
Scalable flow-based networking with DIFANE
,
2010,
SIGCOMM '10.
[6]
Monia Ghobadi,et al.
OpenTM: Traffic Matrix Estimator for OpenFlow Networks
,
2010,
PAM.
[7]
David A. Maltz,et al.
Network traffic characteristics of data centers in the wild
,
2010,
IMC '10.
[8]
Alan L. Cox,et al.
Maestro: A System for Scalable OpenFlow Control
,
2010
.