1/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
2/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Interior Gateway Protocol (IGP)
Metric Based Traffic Engineering
Visa Holopainen, visa@netlab.tkk.fi
Supervisor: Prof. Raimo Kantola
Instructor: Lic. Tech. Marko Luoma
Networking laboratory
3/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Contents
Concept of Traffic Engineering (TE)...…………………..4
Requirements for TE: Policy System……………………8
TE method classification………………………………….9
TE method 1: ECMP TE……………….........................10
TE method 2: MPLS TE…………………………………12
TE method 3: IGP Metric Based TE….........................13
Own contribution: Testing Strategic IGP Metric-Based
TE in real networks……………………………………17
Summary/Conclusions…….…………………………….18
4/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Concept of Traffic Engineering (TE)
• Traffic Engineering (TE) is a field of
communications engineering that tries to
make network operations more effective
and reliable while at the same time
optimizing resource utilization
• “Application of technology and scientific
principles to the measurement,
characterization, modeling, and control of
Internet traffic”
5/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Some problems that TE tries to solve
(Concept contd.)
• Effective bandwidth utilization within
an Autonomous System
• Optimal policy usage between
Autonomous Systems (BGP TE)
• Fast connectivity restoration after a
component breakdown (IGP Fast
Convergence, MPLS Fast Re-Route, etc.)
6/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Some TE goals illustrated (1): Better
throughput (Concept contd.)
Without TE
With TE
90
70
60
70
60
Src-Dst 1
50
Src-Dst 2
40
Src-Dst 3
Average
30
20
Throughput (Mbit/s)
Throughput (Mbit/s)
80
50
Src-Dst 1
40
Src-Dst 2
Src-Dst 3
30
Average
20
10
10
0
0
10
20
30
40
50
Time (min)
60
10
20
30
40
50
Time (min)
60
7/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Some TE goals illustrated (2):
More equal link utilization (Concept contd.)
Without TE
With TE
90
70
80
60
60
Link 1
50
Link 2
40
Link 3
30
Utilization (%)
Utilization (%)
70
50
40
Link 1
Link 2
30
Link 3
20
20
10
10
0
0
10
20
30
40
Time (min)
50
60
10
20
30
40
Time (min)
50
60
8/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Requirements for TE: Policy System
• TE systems consist of a set of rules
(Policy) that are propagated to
enforcement points
• Hierarchical policy systems possible
– Business policy:
f(High responsiveness) ->Response time must be
< 2s
– Utility function policy:
f(Response time must be < 2s) -> condition C
– Action policy:
if condition C then do action A
9/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
TE method classification
• TE methods can be classified in many
ways:
– Short term vs. Long term TE
– Intra-domain vs.Inter-domain TE
– Centralized vs. Distributed TE
– On-line vs. Off-line TE
– Perfomance optimizing vs. Availability
maximizing TE
– Host-based vs. Network-based TE
–…
10/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
TE method 1: ECMP TE
• Equal Cost Multipath (ECMP) balances load for all
equal cost paths towards a destination
• Every router performs a hash on received packets to
determine which one of the paths should be used for
the packet
• The hash may be a function of source address,
destination address, source port, destination port
etc. and can be static or dynamic
• The hashing can be performed separately for each
packet or based on flows
• Medium term, Intra-domain, Distributed, (Off-line),
Network-based, Availability maximizing
11/18
HELSINKI UNIVERSITY OF TECHNOLOGY
ECMP TE (continued)
• ECMP is often
considered to be
sufficient TE method
if both topology and
traffic demands are
symmetrical like in
the figure
• Often not enough for
complicated
networks
Visa Holopainen
12/18
HELSINKI UNIVERSITY OF TECHNOLOGY
TE method 2: MPLS TE
• MPLS TE enables explicit
(source) routing, which is
quite significant, since it
makes unequal-cost load
sharing possible
• In the figure, traffic load is
divided evenly to
unequal-cost router-paths
x->y->z and x->k->v->z
• MPLS TE is somewhat
complicated to deploy
but when correctly
configured, it is very
effective
Visa Holopainen
13/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
TE method 3: IGP Metric Based TE
• Tactical IGP Metric Based TE tries to alter link
costs in some specific points of congestion
– Often only shifts the point of congestion
14/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
IGP Metric Based TE (continued)
• Strategic IGP Metric-Based TE tries to find an
optimal link weight setting for the network (using
some optimization goal(s))
15/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
IGP Metric Based TE (continued)
• The main idea in strategic
IGP Metric Based TE is to
1) obtain topology and
traffic information from the
network, 2) feed this data
to an optimization
algorithm, and 3) send the
optimal link weights back to
the network
• The routers calculate
routes based on the
optimal weights and traffic
gets forwarded to optimal
paths
16/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Optimization tool (IGP-WO)
• Tries to find a link (interface) cost
setting that balances load in the network
• Uses iterative search and a utility
function to discover near-optimal
interface costs for SPF routing
• Iterative search methods have the risk
of visiting old solutions again (cycling)
• Tabu-search meta-heuristic used to
prevent this
17/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Own contribution: Testing Strategic IGP
Metric-Based TE in real networks
• TE-server uses IGP-WO to
determine near-optimal
interface costs dynamically
based on topology
discovery and measured
traffic matrix
• TE algorithm assumes that
routers aren’t the bottleneck
(-> not so useful if they are)
• Network’s throughput
improved about 15%
18/18
HELSINKI UNIVERSITY OF TECHNOLOGY
Visa Holopainen
Summary/Conclusions
• Traffic Engineering (TE) methods try to
make network operations more effective
and reliable while at the same time
optimizing resource utilization
• Our measurements show that Strategic
IGP Metric-Based TE improves throughput
of real networks under certain conditions
• Future work: making the optimal cost
discovery faster by using a mapping
system