Traffic Engineering Jennifer Rexford Advanced Computer Networks Tuesdays/Thursdays 1:30pm-2:50pm.
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Transcript of Traffic Engineering Jennifer Rexford Advanced Computer Networks Tuesdays/Thursdays 1:30pm-2:50pm.
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Traffic EngineeringTraffic Engineering
Jennifer RexfordJennifer Rexford
Advanced Computer NetworksAdvanced Computer Networkshttp://www.cs.princeton.edu/courses/archive/fall08/http://www.cs.princeton.edu/courses/archive/fall08/
cos561/cos561/Tuesdays/Thursdays 1:30pm-2:50pmTuesdays/Thursdays 1:30pm-2:50pm
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Do IP Networks Manage Themselves?
• In some sense, yes:– TCP senders send less traffic during congestion– Routing protocols adapt to topology changes
• But, does the network run efficiently?– Congested link when idle paths exist?– High-delay path when a low-delay path exists?
• How should routing adapt to the traffic?– Avoiding congested links in the network– Satisfying application requirements (e.g., delay)
• … essential questions of traffic engineering
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Traffic Engineering
• What is traffic engineering?– Control and optimization of routing, to steer
traffic through the network in the most effective way
• Two main approaches to adaptation– Adaptive routing protocols
• Distribute traffic and performance measurements• Compute paths based on load, and requirements• At packet level or at circuit level
– Adaptive network-management system • Collect measurements of traffic and topology• Optimize the setting of the “static” parameters
• Big debates still today about the right answer
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Load-Sensitive Routing in the Early ARPANET
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Original ARPANET Algorithm (1969)
• Routing algorithm– Shortest-path routing based on link metrics– Instantaneous queue length plus a constant– Distributed shortest-path algorithm (Bellman-
Ford)
32
2
1
13
1
5
20congested link
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Performance of Original ARPANET Algorithm
• Light load– Delay dominated by the constant part
(transmission delay and propagation delay)
• Medium load– Queuing delay is no longer negligible– Moderate traffic shifts to avoid congestion
• Heavy load– Very high metrics on congested links– Busy links look bad to all of the routers– All routers avoid the busy links– Routers may send packets on longer paths
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Second ARPANET Algorithm (1979)
• Averaging of the link metric over time– Old: Instantaneous delay fluctuates a lot– New: Averaging reduces the fluctuations
• Link-state protocol (more in future lecture)– Old: Distributed path computation leads to loops– New: Better to flood metrics and have each
router compute the shortest paths
• Reduce frequency of updates– Old: Sending updates on each change is too
much– New: Send updates if change passes a threshold
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Problem of Long Alternate Paths
• Picking alternate paths– Long path chosen by one router consumes
resource that other packets could have used– Leads other routers to pick other alternate
paths
• Solution: limit path length– Bound the value of the link metric– “This link is busy enough to go two extra hops”
• Extreme case– Limit path selection to the shortest paths– Pick the least-loaded shortest path in the
network
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Problem of Out-of-Date Information
• Routers make decisions based on old information– Propagation delay in flooding link metrics– Thresholds applied to limit number of updates
• Old information leads to bad decisions– All routers avoid the congested links– … leading to congestion on other links– … and the whole things repeats
Lincoln Tunnel
Holland TunnelNJ NYC
“Backup at Lincoln” on radio triggers congestion at Holland
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Avoiding Oscillations From Out-of-Date Info
• Send link metrics more often– But, leads to higher overhead– But, propagation delay is a fundamental limit
• Make the traffic last longer– Circuit switching: phone network
• Average phone call last 3 minutes• Plenty of time for feedback on link loads
– Packet switching: Internet• Data packet is small (e.g., 1500 bytes or less)• But, feedback on link metrics also sent via packets• Better to make decisions on groups of packets?
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Quality-of-Service Routing on Circuits
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Quality-of-Service Routing With Circuit Switching
• Traffic performance requirement– Guaranteed bandwidth b per connection
• Link resource reservation– Reserved bandwidth ri on link I
– Capacity ci on link i
• Signaling: admission control on path P– Reserve bandwidth b on each link i on path P
– Block: if (ri+b>ci) then reject (or try again)
– Accept: else ri = ri + b
• Routing: ingress router selects the path
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Source-Directed QoS Routing
• New connection with b =3– Routing: select path with available resources– Signaling: reserve bandwidth along the path (r = r +3)– Forward data packets along the selected path– Teardown: free the link bandwidth (r =r -3)
r=8, c=10 r=6, c=7b=3
r=1, c=5r=15, c=
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QoS Routing: Path Selection
• Link-state advertisements– Advertise available bandwidth (ci – ri ) on
link i• E.g., every T seconds, independent of changes• E.g., when metric changes beyond threshold
– Each router constructs view of topology• Path computation at each router
– E.g., Shortest widest path• Consider paths with largest value of mini(ci-ri) • Tie-break on smallest number of hops
– E.g., Widest shortest path• Consider only paths with minimum hops• Tie-break on largest value of mini(ci-ri) over paths
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Reducing Overhead and Avoiding Oscillation
• Link state updates– High update rate leads to high overhead– Low update rate leads to oscillation
• Connections are too short– Average Web transfer is just 10 packets– Requires high update rates to ensure stability– … and results in large number of connections
• Instead, connections for traffic aggregates– E.g., all traffic between two address blocks– E.g., all traffic between two edge routers
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Traffic Engineering as a Network-Management Problem
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Measure, Model, and Control
Topology/Configuratio
n
Offeredtraffic
Changes tothe network
Operational network
Network-wideoptimization
measure
control
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Traffic Engineering in an ISP Backbone
• Topology– Connectivity and capacity of routers and links
• Traffic matrix– Offered load between points in the network
• Performance objective– Balanced load, low latency, service level
agreements …
• Question: which routing configuration to use? – Setting link weights (in OSPF), or – Configuring label-switched paths (in MPLS)
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Example Optimization Problem for OSPF
• Input: graph G(R,L)– R is set of routers– L is set of unidirectional links
– cl is capacity of link l
• Input: traffic matrix– Mi,j is traffic load from router i to j
• Output: setting of the link weights– wl is weight on unidirectional link l
– Pi,j,l is fraction of traffic from i to j traversing link l
• Problem: minimize aggregate congestion– Utilization ul on link l: sum (Mi,j * Pi,j,l)/cl over all (i,j)
pairs
– Aggregate congestion: sum f(ul) over all links l
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11 3
1
45
3
ul
f(ul
)
1
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Network Management Solutions
• Side-steps the problem of oscillation– Network-wide view of traffic and topology– Network-wide decisions
• System can incorporate additional information– Avoid load on certain links (e.g., carrying VoIP)– New TE goals (e.g., bound delay, save energy, …)– Account for shared risks (e.g., optical equipment)
• Additional complexity of management system– Collecting the measurement data– Solving the optimization problem– Reconfiguring the network
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Discussion
• Should traffic engineering be done by the network or by the management systems?– Or some hybrid of the two?
• TeXCP paper– Select multiple paths between each pair of nodes– Collect feedback about utilization of the paths– Adapt the fraction of traffic on each path
• What about the interdomain setting?– Scalability challenges?– Deployment challenges?– Trust issues?
• Interaction with congestion control?– Division of labor between end hosts and routers?