the evolution of layered protocol stacks leads to an hourglass-shaped architecture
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The Evolution of Layered Protocol Stacks Leads to an Hourglass-Shaped Architecture. Saamer Akhshabi Constantine Dovrolis Georgia Institute of Technology s.akhshabi,[email protected]. - PowerPoint PPT PresentationTRANSCRIPT
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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,[email protected]
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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
SilverlightFirefox
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
SilverlightFirefox
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
SilverlightFirefox
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
SilverlightFirefox
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
ThunderbirdSilverlightFirefox
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 process
The birth rate at a layer is regulated by the death rate in that layer
Discussed 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
Laye
r 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)
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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)