ISP and Egress Path Selection

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ISP and Egress Path Selection for Multihomed
Networks Amogh Dhamdhere, Constantine
Dovrolis Networking and Telecommunications
Group Georgia Institute of Technology
Presented by Karl Deng
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Problem Definition
Provision the multihoming configuration of a
source network S.
Inputs S D Di (i 1 .. M) R ri K
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Two Phases
Phase I - ISP Selection Select K ISPs that S will
subscribe to. Objectives Optimize monetary cost
and availability.
Phase II - Egress Path Selection Determine the
ISP that should be used to reach each of the M
major destinations. Objectives Select
congestion-free paths and minimize cost. (Avoid
long-term congestion.)
Phase-I can be repeated in long time scales, from
weeks to months, while Phase-II can be repeated
whenever there is a major change in the egress
traffic distribution.
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Phase I - ISP Selection
possible selections ?
Exhaustive search
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Exhaustive search
- the set of all possible combinations of K ISPs
from the set
- optimal combination
- total cost by taking into account of all three
factors
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Calculate the cost for each combination
- total cost
- monetary cost
- cost associated with the AS-level path length
- cost associated with path diversity
-- normalization factors
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Monetary cost
Constraint Tj lt A
- pricing function of ISP j
G - a mapping between ISP and destination e.g., j
G(i), map destination i to ISP j Tj depends on G
NP-hard and KM possible ways of mapping ?
Heuristic (FFD-like algorithm)
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Algorithm-1 a FFD-like algorithm
FFD - First Fit Decreasing
Basic idea Start with the largest destination,
in terms of traffic rate, and route it through
the lowest-cost ISP.
It is possible that Algorithm 1 will fail to find
a feasible mapping (due to the capacity
constraint).
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Cost associated with the path length
Constraint Tj lt A
pj(i) - AS-level path length to reach a
destination i through ISP j.
Similar to the monetary cost problem, also use
Algorithm-1.
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Cost associated with the path diversity
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Looking Glass Servers (LGS)
LGSs are routers inside an ISP that report
AS-level paths to given destination
networks. Most ISPs maintain public Looking
Glass Servers
We assume that each ISP in has a LGS from
which S can determine the AS-level paths to
destinations in D.
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Phase II - Egress Path Selection
Given the K ISPs selected by Phase I, determine
an optimal destination-ISP mapping.
Constraint None of the paths to the destinations
in D is congested.
Difficulty Available bandwidth of the upstream
network paths is generally unknown. ? We cannot
know a priori whether a given mapping will be
congestion-free or not ? Iterative routing
approach
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Iterative Routing Approach
S routes its egress traffic based on a certain
mapping for some time while measuring the loss
rate in the corresponding paths.
If any of these paths is congested the traffic is
rerouted based on a different mapping.
We allow a certain cost increase while trying to
keep the amount of rerouted and dropped traffic
as low as possible.
A two-step algorithm.
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A Two-step Algorithm

• 1. Initial mapping
• Assume that bottlenecks of all paths locate at
  the K access links.
• Calculate the minimum-cost mapping ? Algorithm-1
• 2. Stochastic search
• Find a congestion-free mapping in the vicinity of
  the minimum-cost mapping
• Simulated annealing

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Algorithm-2 Simulated Annealing
Starts with an initial mapping G and an initial
temperature T. Route traffic as in mapping
G. ccurr cost(G) repeat if ccurr 0
then return G congestion-free solution
else Generate new mapping Gnew Route traffic as
in mapping Gnew cnew cost(Gnew) if cnew ccurr
then Accept Gnew (i.e., G Gnew,
currcnew) else Accept Gnew with probability
e-(cnew-ccurr)/T end if T ?T cooling
rate end if until T 0
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Summary

• Phase I - ISP Selection
• Select K ISPs.
• To minimize
• Monetary cost - Algorithm 1 (FFD-like heuristic)
• Cost associated with AS-level path length -
  Algorithm 1
• Cost associated with Path diversity

• Phase II - Egress Path Selection
• Determine the destination-ISP mapping.
• Two-step Algorithm
• Initial mapping - Algorithm 1
• Stochastic search - Algorithm 2 (Simulated
  Annealing)