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The Evolution of Layered Protocol Stacks Leads to

an Hourglass-Shaped Architecture

Saamer Akhshabi Constantine Dovrolis

Georgia Institute of Technologys.akhshabi,constantine@gatech.edu

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My co-author, Saamer Akhshabi(Very smart 2nd year PhD student,

he could not travel to Toronto)

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Outline

• Motivation• Model description• Results• Concluding remarks

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Why did we write this paper?

Ethernet

Twisted Pair

SMTPHTTP

Thunderbird

Silverlight

Firefox

PPP

Coaxial Cable

IPv4

UDPTCP

RTP

Optical Fiber

MPlayer …

…

…

…

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Why is the Internet protocol stack an hourglass?

Why ?-Random?-Designed?-Emergence?

Ethernet

Twisted Pair

SMTPHTTP

Thunderbird

Silverlight

Firefox

PPP

Coaxial Cable

IPv4

UDPTCP

RTP

Optical Fiber

MPlayer …

…

…

…

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What happens at the “waist” compared to other layers?

Frequent innovations

Frequent innovations

Conserved (“ossified”)

Ethernet

Twisted Pair

SMTPHTTP

Thunderbird

Silverlight

Firefox

PPP

Coaxial Cable

IPv4

UDPTCP

RTP

Optical Fiber

MPlayer …

…

…

…

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How can a new protocol survive at the waist?

X.25SNA

Ethernet

Twisted Pair

SMTPHTTP

Thunderbird

Silverlight

Firefox

PPP

Coaxial Cable

IPv4

UDPTCP

RTP

Optical Fiber

MPlayer …

…

…

…

ATM IPv6

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What about “Future Internet” those architectures?

• Will these architectures also evolve to an hourglass in few years?

• How to make them more “evolvable”?– So that they can better

accommodate innovation?

– So that no single protocol at the waist “kills” all competitors

NDN XIAMpbilityFirst

Nebula

?

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Outline

• Motivation• Model: EvoArch• Results• Conclusions

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Two Disclaimers• EvoArch is only an abstraction of protocol

stacks– EvoArch does not capture many practical aspects

and protocol-specific or layer-specific semantics

• EvoArch is certainly not the only model, or “the correct model”, for the emergence of hourglass-shaped network architectures– Models should be judged based on their

assumptions, parsimony and predictions

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Model description

Protocols as nodes

Protocol dependencies as edges Products: P(u)

Substrates:S(u)

Layer of u: l(u)

Layered acyclic network

u

Every layer provides a service

L

1

…

4

3

2

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The value of a protocol• The value of a protocol depends on the

value of its products• Protocols with valuable products are more

valuable

1 1

5

2

5

3

1 11111

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The generality of a layer

Ethernet

Twisted Pair

SMTPHTTP

Thunderbird

SilverlightFirefox

PPP

Coaxial Cable

IPv4

UDPTCP

RTP

Optical Fiber

MPlayer

As we go higher in the stack:• Protocols become less

general – they offer more specialized services

• The probability that a protocol is used by next-layer’s protocols decreases

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Generality as a probability• We introduce a

parameter called generality vector s

• s(l) : probability that new node at layer l+1 chooses each node at layer l as substrate

• s(l) decreases as we go higher in protocol stack

s(1) = 0.9

s(3) = 0.5

s(L-1) = 0.1

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Competition between protocols

• Two protocols at the same layer compete if they offer similar services– i.e., if they have large overlap in their products

• HTTP competes with FTP due to several overlapping products

• TCP does not compete with UDP because they have minimal service overlap

TCP UDP

HTTP FTP

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Modeling competition

• If c = 3/5• u competes with

q and w• q does not

compete with w

q u w

• Let C(u) be set of competitors of u• Node w competes with u if

• c: competition threshold

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When does a protocol “die”?• Protocols can become extinct due to

competition with other protocols• For example, HTTP services cover the set

of services provided by FTP

• Competition from HTTP has led to FTP’s demise

HTTP FTP

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Modeling protocol deaths• A node u dies if its value is significantly less than the value

of its strongest (i.e., maximum value) competitor.

• z: mortality parameter

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Cascade deaths

• u is w’s competitor• Suppose that w dies due to competition

with u (r=3/7)

2 1

4

2

7

21

3

1

1 1 1 11 1 1

q u w

If a node w dies, its products also die if their only substrate is w. This can lead to cascade deaths.

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Protocol births• Basic birth process

Number of new nodes at given time is a small fraction of total number of nodes in network at that time.

New nodes assigned randomly to layers

• Death-regulated birth processThe birth rate at a layer is regulated by

the death rate in that layerDiscussed later

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Summary of EvoArch• Discrete-time model– Time advances in rounds

• Each round includesbirth of new nodescompetition among nodes at the same layerpotentially, death of some nodes

• Key parameters– Generality vector s– Competition threshold c– Mortality parameter z

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Outline

• Motivation• Model Description• Results–Emergence of hourglass structures –Controlling the location/width of the

waist–Evolutionary kernels– Protocol differences

• Conclusions

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Hourglass shape

• The network forms an hourglass structure over time

• The waist usually occurs at layer 5 or 6.

L = 10c = 3/5z = 1s(l) = 1-l/L

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Hourglass Resemblance Metric

w(l) : width of layer l Minimum occurs at layer b X = {w(l), l = 1, . . . b} Y = {w(l), l = b, . . .L} Mann-Kendall statistic for

monotonic trend on the sequences X and Y: coefficients τX and τY

H = (τY – τX)/2

• H=1 when widths first decrease and then increase (monotonically)

Width

Layer

num

ber

w(1)w(2)

…

w(b)

w(b+1)

…W(L)

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Robustness

• High hourglass scores under a wide range of parameters

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Why does EvoArch generatehourglass-shaped networks?

Small generality Low competition (local)Low death probability

Large generalityFrequent competitionProtocols have similar substrates & valuesLow death probability

Generality close to 50%Few protocols with many productsMost other protocols die

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How can we get a wider waist?

• As γ increases– Location of the waist

moves to higher layers– Width of waist

increases

• γ is the layer at which the generality is 50%

Layer numberγ

0.5

s(l)

Evolutionary kernels

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How can a kernel die?

• Normalized value of a node: value divided by maximum possible value at that round

• If several nodes appear at the next higher layer, andkernel fails to quickly acquire those new possible products,someone else may do so..

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Death-regulated birth process?

• What if the birth probability in a layer is regulated by the death probability in that layer?

• It becomes practically impossible to replace kernels

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What if protocols differ in term of a “quality factor”?

• The “quality factor” can be interpreted broadly Performance, Extent of deployment, Reliability or security, Incremental improvements, etc

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Effects of quality factor• We still get an hourglass• Lower part of hourglass is smaller in size

– only high quality nodes survive at the lower part

• Kernels are often NOT the highest quality protocols

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Outline

• Motivation• Model Description• Results• Concluding remarks

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What does this mean for the Internet architecture?

• New way to think about (and teach) Internet’s hourglass architecture

• New way to think about “ossification” of protocols at the waist

• Parameterized model for TCP/IP stack: – Two protocols compete when their service

overlap is more than 70%– A protocol survives only if its value is more

than 90% of its strongest competitor’s value– Death-regulated births

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What does this mean for IPv4 vs IPv6?

• IPv6 has same products but lower extent of deployment (i.e., lower “quality factor”)

• IPv6 would find it easier to compete w IPv4 if:– It had some distinct products that IPv4 does

not have– Unfortunately, it only offers more addresses

• IPv6 would face easier adoption if it was not presented as “IPv4 replacement” but as “the second network-layer protocol”

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What does this mean for future Internet architectures?

• Hourglass structures should be expected if these new architectures evolve/compete

• Designers should strive for wider waist– More diverse waist -> more evolvable

architecture

• EvoArch: as the waist moves higher, it also becomes wider– How to push the waist to a higher layer?– See highly relevant paper:

• L. Popa, A. Ghodsi, and I. Stoica. HTTP as the Narrow Waist of the Future Internet. In ACM SIGCOMM HotNets, 2010

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From Networking to Network Science

• Hourglass effect in development of embryos

• Hourglass effect in organization structures• Hourglass effect in innate immune system

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Thanks to

Todd Streelman (School of Biology, Georgia Tech)

Soojin Yi (School of Biology, Georgia Tech)

National Science Foundation (NSF)