Congestion Pricing Overlaid on Edge-to-Edge Congestion Control
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Transcript of Congestion Pricing Overlaid on Edge-to-Edge Congestion Control
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Congestion Pricing Overlaid on Edge-to-Edge Congestion
Control
Murat Yuksel, Shivkumar Kalyanaraman and Anuj Goel
Rensselaer Polytechnic Institute, Troy, NY
{yuksem, shivkuma} @ecse.rpi.edu, [email protected]
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Outline
Literature development : congestion-sensitive pricing
DCC -- an edge-to-edge pricing framework
Pricing Over Congestion Control (POCC)
Edge-to-edge congestion control Simulation experiments Summary
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Congestion-Sensitive Pricing
Increase the price when congestion, decrease when no congestion.
A way of controlling user’s traffic demand and hence, a way of controlling network congestion
Better resource (bandwidth) allocation Fairness Problems:
Users don’t like price fluctuations! Each price change must be fed back to the
user before it could be applied, i.e. hard to implement in a wide area network.
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Traditional Pricing Schemes Proposed
congestion pricing schemes have used network interior, which is hard to implement
Kelly’s, Low’s, Varian’s, etc.
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DCC Framework
Stations of the providerimplement pricing strategiesfor the short-term contracts
Customers
Network Core(Accessed only by contracts)
EdgeRouter
EdgeRouter
EdgeRouter
EdgeRouter
EdgeRouter
EdgeRouter
EdgeStrategy
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DCC Framework (cont’d) Users negotiate with the provider at
ingress points The provider estimates user’s
incentives by observing user’s traffic at different prices
A simple way of representing user’s incentive is his/her budget
Budget estimation:ijijij pxb ˆ
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DCC Framework (cont’d) The provider offers short-term contracts:
is price per unit volume Vmax is maximum volume user can contract for T is contract length
Pv is formulated by a “pricing scheme” at the ingress, e.g. Price Discovery [Arora’02]
Vmax is a parameter to be set by soft admission control
),,( max TVpfContract vvp
TmaxV
vp
maxV
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DCC Framework (cont’d)
No per-packet accounting Updates to edges only Enables congestion pricing by edge-to-edge congestion
detection techniques Deployable on diff-serv architecture of the Internet
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POCC
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POCC (cont’d)
Problems: Parameter mapping – need to map
parameters of the overlay pricing protocol with the parameters of the underlying edge-to-edge congestion control scheme
Edge queues – need to manage the edge queues so that they are bounded
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An Example Edge-to-Edge Congestion Control Scheme: Riviera
Accumulation-based congestion control mechanism At the egress nodes, estimates edge-to-edge flow’s
accumulation a by monitoring packet delay If a < min_thresh, the edge-to-edge flow is not
congested. If a > max_thresh, the edge-to-edge flow is
congested. Egress informs ingress about the congestion state,
along with an average output rate of the flow. Ingress applies an AIMD-like algorithm with increase
parameter and decrease parameter to set sending rate.
More is available at: D. Harrison, S. Kalyanaraman and S. Ramakrishnan, “Overlay
bandwidth services: Basic framework and edge-to-edge closed-loop building block”, Poster in SIGCOMM 2001.
Y. Xia, D. Harrison, S. Kalyanaraman, “An Accumulation-based Congestion Control Model”, ICC 2003, NGI 8, Tuesday 15:30.
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POCC (cont’d)
Solutions when Riviera is the underlying edge-to-edge congestion control scheme: Parameter mapping:
Let be the fraction of capacity that must be given to .
Set Riviera’s parameters as:
Ccijij /ijf
ijijij
ijijij
ijijij
threshthresh
threshthresh
min_min_
max_max_
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POCC (cont’d) Edge queues:
Subtract necessary capacity from in order to drain the edge queue headed on .
Alternatively (or simultaneously), mark packets at the edge when the edge queue exceeds a threshold. This will indirectly reduce the estimated capacity .
ijc
ijfijc
TQcc ijijij /
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Simulation Experiments
Average packet size is 1000bytes. Propagation delay is 5ms an all links. The buffer sizes are assumed to be
infinite, no drops are allowed. User utility is concave: u(x) = b
log(x) Users have a budget b and maximize
their surplus by sending at a rate b/p.
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Simulation Experiments (cont’d)
15Mb
15Mb
10Mb
0
1
15Mb
15Mb 1
2
flow 2
15Mb
0
15Mb
2
A B
flow 1flow 0
Single-Bottleneck
3 user flows with budgets 30, 20 and 10 $/Mb respectively for flows 0, 1, 2.
Total simulation time is 15,000s. At every 5,000s, one of the user flows gets
active, starting from flow 0 up to 2.
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Simulation Experiments (cont’d)
Pricing w/o edge-to-edge congestion control POCC
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Simulation Experiments (cont’d)
Pricing w/o edge-to-edge congestion control POCC
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Simulation Experiments (cont’d)
POCC
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Summary Control of congestion requires small
time-scale price updates Users want less frequent price updates POCC overlays large time-scale pricing
on top of small time-scale congestion control
Problems: Parameter mapping Edge queues
Solutions are proposed
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Questions, Ideas?
THANK YOU!