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Combining multihoming with overlay routing (or, how to be a better ISP without owning a network). Yong Zhu, Constantine Dovrolis, and Mostafa Ammar Georgia Institute of Technology. Speaker: Chen-Hung Yu. Basic form of Internet. Singlehoming. Multihoming & Overlay routing. - PowerPoint PPT Presentation
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Combining multihoming with overlay routing
(or, how to be a better ISP without owning a network)
Yong Zhu, Constantine Dovrolis, and Mostafa Ammar
Georgia Institute of TechnologySpeaker: Chen-Hung Yu
Basic form of Internet
Singlehoming
Multihoming & Overlay routing
OSP – Overlay Service Provider
Operates a Multihomed Overlay Network (MON)
MON node – a multihomed routerAn Internet provider that does not own a
network
MON nodes
If a MON node is multihomed with K ISPs each flow has K direct MON paths
With N MON nodes each flow increases to indirect MON paths 12 NK
Outline
IntroductionModel and Problem FormulationMON design heuristicsEvaluation and DiscussionsConclusions
MON design problem
Where to place MON nodes and how to select upstream ISPs for each nodes.
Objectives Profitable Better performance Less expensive
Revenue, cost, customer subscribe
The problem involves …
ISPsPerformance of the native networkThe location and traffic matrix of potential
customersThe OSP routing strategyPricing functionNode deployment costs
ISPs and the native network
POP p = (l, i) – the access point to ISP i at location l, P denotes the set of all POPs LOC(p) = l; ISP(p) = i We denote Il as the set of all ISPs the can be
connected from location l
Native-layer performance – matrix The entry represents the propagation RTT
from POP p to q
PPT
qp,
Estimate the matrix T
Directly measure – e.g., ping If can’t, try to find the model
Mostly depends on the physical distance between two POPs
Intradomain – “highway driving distance” Interdomain – RTT increases with the
number of AS in the route
Intradomain cases
Driving distance from
p to q
Interdomain cases
A constant depends on the # of AS hops h
MON representation
A MON node is present at POP p if the node is located at LOC(p) and connected to ISP(p)
POP selection vector
The locations of all MON nodes
Customers and OSP-preferred flows
The workload of customer u is a set of flows F(u)
A flow f = (sf, df, rf, τf)
OSP-preferred flow and OSP-preferred path
Subscribe – At least a fraction H of a customer’s traffic is in OSP-preferred flows
OSP routing strategy
Direct-Routing-First (DRF)
OSP revenues
Let be the OSP pricing functionThe total OSP revenue
Required upstream capacity at POP p
Total capacity cost
The pricing function used by the ISP at
POP p
OSP costs
Required upstream capacity at POP p
Total capacity cost
Total node deployment cost
The pricing function used by the ISP at
POP p
Cost of deploying a MON node at
location l
Problem statement
Inputs: Native network information OSP information Customer information
Determine the POP selection vector MON to maximize the profit:
Problem statement (cont.)
constraints At most N MON nodes Maximum multihoming degree
NP-hardness Reduction from the set covering problem
MON design heuristics
Two major tasks: Select up to N locations for placing MON nodes Select up to K upstream ISPs for each
deployed MON node
Present four heuristics differ in terms of their inputs
Four Heuristics
RAND CUST –
places N MON nodes at the locations with the maximum number of customers
Each selected l then selects the locally present ISPs with the maximum coverage
TRFC – uses the aggregated traffic rate that originates from all potential customers Places MON nodes at locations where “traffic heavy” customers
are located Select ISPs that receive the maximum traffic rate from
customers PERF
Performance-driven (PERF)
If there are OSP-preferred direct paths, then CUST and TRFC perform quite well.
However, when many customer flows only have indirect OSP-preferred paths, they will fail.
Associate
Evaluation
Compare the MON design heuristicsOSP profitability and performance
Depending on # of MON nodes, degree of multihoming, node deployment cost, OSP/ISP pricing ratio
Examine various OSP routing strategies
Simulation setup
Customer CUST-POPUL, CUST-UNFRM
Flow RATE-GRVTY, RATE-UNFRM
Pricing
)()(
^
rPrPR
pp
Effect of number of MON nodes
Effect of OSP routing strategy
Effect of pricing ratio
Effect of maximum multihoming degree
conclusions
Examine multihoming + overlay routing from the pragmatic perspective of an OSP
Meet the objectives – profitable 、 better performance 、 less expensive Use a performance-aware MON design heuristic Deploy nodes at “key” locations Connect each MON node to ISPs that can directly reach
traffic-heavy destination POPs Direct path > indirect path Charge less than competing native ISPs Determine good trade-off between the # of MON nodes
and multihoming degree based on the d(l)