Bill Krogfoss, Strategy Director, Chief Technology Office Alcatel-Lucent "Internet Economy and Content Peering"

Internet Economy and Content PeeringAlcatel -LucentBell Labs Research Paper

Bill Krogfoss

November 2, 2011

Agenda

1. Status of Peering

2. Internet Economic Model

3. Content Peering

4. Peering Ratios

5. CDN Economics

3 | Presentation Title | Month Year Alcatel-Lucent – Internal

Proprietary – Use pursuant to Company instruction.

Internet Economic Mysteries and Contradictions

“Why should Google or other large CP be allowed to dump all this traffic on my network for free?”

Netflix 10K “We believe our financial responsibility is to bring the traffic to ISP doorstep and the ISPs responsibility is to deliver it”

T2/T3 ISPs are complaining about rising consumer traffic, but T1 ISPs are not complaining

Content Providers and CDNs : “Content Peering is a win-win proposition for us and ISP”

Level3 (CDN) vs. Comcast: “ Why should peering ratios be limited?”



Peering vs. Transit Costs

-

2.00

4.00

6.00

8.00

10.00

12.00

1 2 4 6 8 10

Gbps (inter ISP BW)

$/M

bps

With Colocation No Colocation

Internet Economics for Transit and Peering

No co-location

with co-location

Break-evenTransit rate

No ColocationPeering Costs10G Port 3,500$ 10G Transport 5,000$ Colo 2,000$ Equipment 500$ Total 11,000$

Transit pricing has fallen dramatically, and now competes with peering

Peering break even point is several Gbps and increasing as transit continues to decline (Can transit price drop be a consequence of peering?)

Macro Trend (33K ASN study from 2004-2010) Shows Increased Peering and Transit – vast majority of peering relationships in top 2% (90%)

CDF of AS Peers ('05-'09)

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10Number of Peers

2005 2006 2007 2008 2009 2010

Increased peering

’09-’10 Diminishing Returns?

*source:Drpeering.net

What is impact of peering and transit prices converging?......



0

5

10

15

20

25

30

35

Rou

tes

Google

megaup

load

micros

oftwiki

pedia

Yahoo

Yahoo

JP sina

youtu

bemys

pace

baidu

friend

ster

facebo

okfot

olog

Routes with zero T1 ISPs

Peering for Performance

2007 HP Lab study latency: MSN & Google had 24 ‘degree’ networks, Facebook 3 degree

Internet Impact: 50 global traceroute servers showed 60% of routes to large ASPs avoided T1 ISPs (Internet Backbone)*

Jupiter Research - doubling delay can result in one-quarter fewer customers

Content Peering provides a significant performance advantage

TPG

MSN

NIC

FB

NTT

2914

3914

BT

DT

gblx

BT

MSN RoutesFacebook Routes

ST

Facebook 300ms vs 157ms Yahoo/Youtube

HP Laboratories, May 21, 2008*Content Peering provides a significant performance advantage

Economic Model



Internet Economics Basics

Internet Ecosystem: Shared Infrastructure, Shared Revenue & Expenses

Content Provider Revenue is shared as Transit Revenue to other ISPs

Each ISP fares differently due to its type and routing topology

Majority of Revenue for Internet is CP and Subscriber

However, Subscriber revenue is fixed (doesn’t vary with traffic), CP varies with traffic

ISP A

ISP B

ISP C

ISP D

ISP E

ISP F

ISP G

Shared Revenues

$7

$5

Traffic (Mbps)

$10

$5

$S

ISP B

ISP C

ISP D

ISP E

ISP F

ISP G

ISP A

Generators (K)

Consumers (S)

Internet Ecosystem (Shared Infrastructure)

Content Revenue literally funds the inter domain links (i.e. Internet)

$3

$2

$10

($5)

ISP D

ISP GISP A

ISP BISP F

ISP E ISP C

$ $K S+

No new revenue generated by transit fees(for the Internet Ecosystem)



Internet Economic Model (before Content Peering)

Ecosystem is ‘conservative’ in nature. No new revenue generated through traffic distribution. Traffic generated is traffic consumed proportional to subscribers

Inter-domain Economic Model (focus on transit/peering economics)

Scenario 1 (no content peering): Nominal (T1) Transit $5/Mbps, 5K subs/T2 & T3 ISP, sub revenue $30/mo/sub

ISP E

ISP C

ISP A

ISP D

ISP B

$ sub = s

Internet Income View

Tier 3

Tier 2

Tier 1

ISP Profit, increasing BW per Content Provider

-

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

0 10 20 30 40

(Gbps)

($U

SD)

Subscriber revenue

Profit T3

Profit T2

Profit T1

i iInternet Profit (P) = Content Revenue ( k ) +Subscriber Revenue ( s ) = K + S∑ ∑

T1 Transit Rate

$k

$s

$k

$s

$k

$s

CPC CPD

CPB

CPA $kNo Content

Peering

Content Providers and Peering



Internet Profit w/ Increasing Content Peering

-

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

No Peer 1 x CP 2 x CP 3 x CP 4 x CP

Internet Economy with Content Peering

Peering often benefits one ISP at the expense of another

Net effect of increased peering is reduced profit for the system and most ISPs

ISP BISP A

CP ‘B’$$

CP ‘A’$$

T1

Increasing Content peering

Total Ecosystem Profit

T1

T2

T3

ISP E

ISP C

ISP A

ISP D

ISP B

Content Peering View

CP A CP B

CP C CP D

Peering CandidatesFor CP B

Peering CandidatesFor CP C

ISP E

ISP C

ISP A

ISP D

ISP B


CP A CP B

CP C CP D

Peering CandidatesFor CP B

Peering CandidatesFor CP C

Reduced IncomeISP B

CP ‘B’ Reduced OPEXCP BPeer

Reduced ExpenseISP A

$

( ) ( )InternetProfit (P )= ContentRev K Sub Rev S - Peering Costs (C ) P = K S Cp p+ ⇒ + −

(1 )i i i p i ii i

Internet Profit (P) r t s C rtη= − + −∑ ∑



Ultimate loss in Ecosystem with increasing peering

0%

50%

100%

150%

200%

250%

300%

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

amount peered away

Prof

it Lo

ss in

Eco

syst

em

Cp=η/4 Cp=η/3 Cp=η/2 Cp=η/1.2

( )t →∞

Internet Economy with Content Peering

What is the ultimate impact on the Ecosystem as Traffic gets very large?

Profit of Internet with Increased Peering and Increased Traffic

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

No Peer 1 x CP 2 x CP 3 x CP 4 x CP

Mill

ions

USD

Increasing Peering

T 40% CAGR

np p

np

P Ppercentage loss in ecosystem =

P−

( )lim lim

lim( ) (1 )( )

p p

t t

p p p

t

K S K S C CK S K S

t c rcr t S rηβ ηβ

→∞ →∞

→∞

+ − + −= =

+ +

=+ −

Cp-> η

Profit becomes loss

0;

(1 )( ) 0

;

p

p

p p

p

K S C condition for profitability

t r S trc

S tr if t is large than rtc t c

as c , r 0.5

η

η ηη η

η

+ − ≥

− + − ≥

+≤ ≤

+ +

→ ≤

Transit cost

Peering Cost and Transit Cost Converge



What about increasing Peering Ratios?

Today’s Internet is made up of many Content Heavy Networks and Eyeball Heavy Networks (access networks)

Peering between ISPs and Content Networks reduces the ability for the Internet to profit from transit income

Traffic grows at rate proportional to transit cost ( ), but when a gets very large it grows at a rate of ( ) . Recall that peering and transit costs are converging!

T2

To aTo

a:1

T1

P (peer)

txt

CDN

What happens as ‘a’ gets large?

;;

t p o

t

p

P k T S k aT

k unit cost of transitk unit cost of peering

= + −

T

t pk k−tk

With increasing asymmetry there is no margins in selling transit ( )t pk k⎯⎯→

Internet Profit Ecosystem with increasing asymmetric peering ratios

-

100

200

300

400

500

600

20 40 60 80 100

Gbps

($M

USD)

Increasing asymmetrya=2

a=20

a=40

a=100profit

tk

a=100, kt ->kp

(T - aTo)



( (1 ) )i i ii ii n i

ik h s hP P P = ( ) t = K+S; εη β ε− + +∑ ∑= + =∑

Internet Economics: Content Delivery Networks

Scenario: Impact of Content Delivery Networks CDNs look to ISPs as large Content Providers, economically

Do CDNs bring new revenue into Ecosystem?

ISP E

ISP C

ISP A

ISP D

ISP B


CP A CP B

CP C

CP D

CDNCP A

CP nT/P

T/P

))

)

CDN creates new Revenue:if CDN rate > CP Transit Rate ( CDN shares in Existing Revenue:if CDN rate ~ CP Transit Rate (CDN degenerates Revenue:if CDN rate < CP Transit Rate (

ε βε β

ε β

>≅

<

Look at impact of CDNs on ISPs with and without Content peering



Impact of CDNs on ISP Economy (CDN rate = Transit)

-

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

10 20 30 40 50Gbps

CDN Conclusions

Scenarios 1: CDN Rate ~ CP Transit Rate (with and w/o CDN Peering)

Scenario 2: CDN Rate > CP Transit Rate (no CDN peering)

Cache Hit Rate (50%), With and Without CDN Peering

CDN Peering Impact

Profit: CDN

Profit: CDN Peering

CDN Impact

ISP Impact with Increasing CDN Value

-

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

10 20 30 40 50Gbps

CDN Increasing Value (CDN Rate >> Transit)

CDN Impact

Total ISP Profit

CDN rate(ε) > Transit Rate (β)

( 1.4)ε =

( 1.6)ε =



Conclusions

By its very structure the Internet profit is inequitably divided between the infrastructure providers

Originally Peering provided a method to combat high Transit Costs

Today Peering is primarily a performance tool rather than an economic tool –content providers that peer have a significant performance advantage

The consequences of content peering is a real economic loss – difficult to quantify in a highly complex ecosystem, but as peering and transit prices converge it becomes worse

Increasing Asymmetry for peering only exacerbates the economic impact of content peering

CDNs postively contribute to Internet Ecosystem only if they are able to show value beyond just transit replacement

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