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Price Discovery at Network Edges. G. S. Arora, M. Yuksel, S. Kalyanaraman, T. Ravichandran and A. Gupta Rensselaer Polytechnic Institute, Troy, NY. Overview. Motivation Edge-to-Edge Concepts Price Discovery Framework Pricing Schemes Simulations Summary. Motivation. - PowerPoint PPT Presentation
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Price Discovery at Network Edges
G. S. Arora, M. Yuksel, S. Kalyanaraman,
T. Ravichandran and A. Gupta
Rensselaer Polytechnic Institute, Troy, NY
SPECTS 2002
Overview Motivation Edge-to-Edge Concepts Price Discovery Framework Pricing Schemes Simulations Summary
SPECTS 2002
Motivation Need for new economic models Adaptive, particularly congestion, pricing is
necessary Implementation problems need to be
solved: Upgrades should be limited Administrative access is necessary
Can we do it only at network edges?
SPECTS 2002
Edge-to-Edge Concepts
A generic view and the trend for the Internet. Administrative access is available at edges. So, possible to coordinate ingress and egress edge
stations. A more complex version of Clark’s Edge Pricing is
possible..
SPECTS 2002
Price Discovery Framework Given edge-to-edge coordination, estimate
edge-to-edge capacity . Congestion pricing Pricing of edge
queue . Severity of congestion is the ratio . Is this ratio really a good parameter?
Formulate objective function Regression analysis for unknown variables of
the objective function
iC
1iq
ii Cq /1
SPECTS 2002
Price Discovery Framework (cont’d) Let there be k observations in a contract period. User adaptation:
Actual spent budget for user with reservation price :p̂
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Price Discovery Framework (cont’d) Objective: Minimize non-utilized capacity while
keeping edge queue less than a pre-defined value .
Formulation:
subject to
maxq
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Price Discovery Framework (cont’d) Other than Bk everything else is known.
For k=1000, qmax=50, Ck ~ N(98,2) truncated in the range [96,100]: Regression analysis for Bk ~ U(20,50) and Bk ~
U(30,150) verified that qi/Ci,mean is strongly associated with optimal price pi
*.
So, we can use the predictor qi/Ci,mean to determine pi in adaptive pricing at the edge.
SPECTS 2002
Pricing Schemes Assuming that ISP wants to keep edge queue in the
range [ql, qh]. Proportional Increase Proportional Decrease (PIPD):
Proportional Increase Additive Decrease (PIAD):
SPECTS 2002
Pricing Schemes (cont’d) Additive Increase Additive Decrease (AIAD):
Additive Increase Proportional Decrease (AIPD):
SPECTS 2002
Simulations
Define user demand according to reservation price and :
Initial parameters: Step increase in demand: In times (50, 100), i.e.
SPECTS 2002
Simulations (cont’d)
SPECTS 2002
Simulations (cont’d)
SPECTS 2002
Simulations (cont’d)
PIPD and PIAD performs significantly better than AIPD and AIAD.
Compared to PIPD, PIAD has less variation in price but utilization is slightly less too.
So, the best one is either PIAD or PIPD, depending on value of utilization.
SPECTS 2002
Simulations (cont’d) Investigated effect of several parameters
on PIAD performance.
We run two users with different and reservation prices:
=
SPECTS 2002
Simulations (cont’d)
SPECTS 2002
Summary Adaptive (particularly congestion) pricing
is necessary for enabling better economic models.
Price Discovery: Deployable over diff-serv Possible to implement congestion pricing at
edges Possible to develop variety of pricing
schemes: PIPD, PIAD, AIPD, AIAD.