Download Traffic Engineering

Traffic Engineering
By
Kavitha Ganapa
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Introduction
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Traffic engineering is concerned with
the issue of performance evaluation and
optimization of operational IP networks
Through carefully managing the traffic
distribution inside a network
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Congestion hot spots can be reduced
Resource utilization can be improved
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Need for Traffic engineering
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Need for service providers to efficiently
provide and manage network resources
to accommodate resource commitments
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To meet customer’s expectation of
guaranteed and differentiated services
To reduce cost of provisioning the services
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Fish problem
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Leads to extremely unbalanced traffic
Poor utilization of network resources
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Fish problem in IP routing
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Fish problem is caused by primarily two
properties
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IP routing is destination-based, all packets
whose destination addresses share the
same prefix have the same next hop
Decision making in current routing is based
on local optimization
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Traffic engineering solutions
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Fish problem is solved by going beyond
current destination based routing and
by providing mechanisms to explicitly
manage the traffic inside network
Overlay Model
Peer Model
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Overlay Model
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Calculates the routes for traffic
demands for edge nodes
Service providers then set up MPLS
explicit routes between edge routes and
match traffic demands over them,
creating a full-mesh network
Suffers from N-square problem,
problems with scalability
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Peer Model
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Achieves balanced traffic distribution by
manipulating link weights in the OSPF routing
protocol
More scalable than Overlay Model
Packets are forwarded based on longestprefix match
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Eliminates N-square problem and reduces
Reduces messaging overheads in setting up
explicit routes
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Optimization objectives
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Minimizing congestion and packet losses in
the network
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Network congestion is caused by
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Inadequate network resources (can be solved by new
capacity or reduce demands)
Unbalanced traffic distribution (can be addressed by
better management of the resources in the network)
Improving link Utilization
Minimizing the total delay experienced by
packets
Increasing the number of customers with the
current assets
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One objective
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To minimize the maximum of link utilization
Why?
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Hot spots are the points with the highest link
utilization
Queuing delay increases nonlinearly as link
utilization becomes higher
By minimizing the maximum of link utilization
traffic is spread and the resources are efficiently
used
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Advantages of the Objective
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Reduces the total delay experienced by the
packets
Moves the traffic away from congested hot
spots to less utilized parts of the network
thus balanced traffic distribution
Leaves more space for future traffic growth,
the percentage of residual bandwidth is
maximized by the minimizing the maximum
link utilization
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Building blocks
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Data repository
Topology and state discovery
Traffic demand estimation
Route computation (constraint-based routing)
Network interface
Graphic user interface
Topology and state discovery and constraint
based routing are two critical components of
traffic engineering
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Topology and state discovery
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OSPF-based scheme
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Because OSPF is widely deployed
Has the necessary mechanisms for distributing link
status and constructing a topology database
Extended link state information for traffic
engineering
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Local and remote interface IP addresses
Traffic engineering metric
Maximum bandwidth
Maximum reservable bandwidth
Unreserved bandwidth
Resource class
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Constraint-based routing
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Shortest path
Minimum hop
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Shortest widest path
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Minimize the total resource consumption per route
Avoids overloading by maximizing the residual
capacity across the network
Hybrid algorithm
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Combination of Shortest path/Minimum hop and
shortest widest path
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Multipath load sharing
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Hashing based traffic splitting schemes
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Direct hashing
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Can split a load only into equal amounts
Table-based hashing
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Can distribute the traffic as required
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Summary
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Traffic engineering is concerned with
performance optimization of operational
networks
Provides a set of tools for efficiently
provisioning and managing backbone
networks
Used to reduce congestion hot spots, improve
overall utilization of networks and reduce the
cost for meeting resource commitments to
their customers
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Research work
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Our work includes the investigation of
the QoS-based routing problem under
two different frameworks:
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the traditionally used SPC-QRF
The newly proposed SPD-QRF
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Acknowledgments
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The slides are prepared based on the
information from Architectures and
Mechanisms for Quality of Service by
Zheng Wang
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