[e2e] Why do we need congestion control?

Jon Crowcroft Jon.Crowcroft at cl.cam.ac.uk
Wed Mar 6 07:02:43 PST 2013


ok - i see your point - this is true if your sources have a peak rate they can send at 

this could be the line rate of their uplink  - 
that would be embarrasingly bad
(see keshav's followup on escalating costs of coding)
or the rate they can get data off disk (which could be as bad, but might be lower)
or an application specific rate (e.g. streamed video) for which you're suggestion is
quite reasonable....

but for data sources which are greedy 
(TCP with arbitrarily large files)
you need a way to tell sources a non wasteful way of sending - 

and what is more
there isn't just one set of sources in one location 
and a set of sinks in one other location
so the system of senders sending at 
unconstrainted rates on a finite speed net with high speed edges,
would create multiple bottlenecks,
which would exponentiate the problem

coding isn't magic - its info theory - if you lose info
you must add redundency - coding does it pre-emptively
rather than post-hoc the way ARQ/Retransmit does,
which saves you time, but in the end, can't defer the inevitable

if you look at digital fountin systems for video
they pick a likely loss rate, pick a tolerable picture degradation rate
and use those to derive/choose a code 

the assumption is that the losses are capped because most other systems 
are backing off just like TCP - if you break that assumption,
you'll break the coding parameter choice

anyhow, roll out ECN - much betterer technology:)
congestion avoidance without keeping queues filled everywhere...



In missive <CANZhn5E3jQcm9SD-avgVB1kE+wNRLcUM_tCVBV1FcYN+Q-rdfQ at mail.gmail.com>, shun cai typed:

 >>--e89a8ff1c4e2529bed04d742b110
 >>Content-Type: text/plain; charset=ISO-8859-1
 >>
 >>1. With fountain codes, for k original packets, infinite number of encoded
 >>packets can be generated and the receiver can recover the k packets with
 >>any k(1+ e) coded packets.
 >>
 >>2. Suppose all flows are coded, and  the short term packet arrival rate of
 >>some flows  exceeds  the service rate of the network.  Overflow and packet
 >>loss could happen wheather the packet coded or not.
 >>
 >> My point is, I do not think the effective throughput will plunge  with
 >>coded flows , although the buffers are full. The network is in full swing
 >>and the worst delay of a flow is  the sum of the  maximum queue time of the
 >>routers along the path.
 >>
 >>I think there will not be a cliff in the throughput-load figure, insdead,
 >>the curve will go beyond the Knee and reach a constant throughput.
 >>
 >>
 >>
 >>
 >>
 >>
 >>
 >>
 >>2013/3/6 Jon Crowcroft <Jon.Crowcroft at cl.cam.ac.uk>
 >>
 >>> there's no free lunch - if the queue keeps being filled, you'll get
 >>> increasing
 >>> packet loss - to cover the loss, you'll need more redundency in your
 >>> erasure
 >>> coding - this will cost you more delay at source (in constructing more
 >>> redundency) and more overhead in the net, which is a positive feedback
 >>> loop,
 >>> just like retransmitting a whole window into a congested queue/path - a
 >>> "vicious cycle" as opposed to a virtuous one...
 >>>
 >>> so all that erasure codes buy you is delaying the point when you go over
 >>> the
 >>> clif
 >>>
 >>> In missive <
 >>> CANZhn5Gqyw6-XpaB2-XKmbahKidOap+ZDqGAJ2NqdMBxmYAP-w at mail.gmail.com>, shun
 >>> cai
 >>>  typed:
 >>>
 >>>  >>--f46d0444e84964e1a304d740bdcd
 >>>  >>Content-Type: text/plain; charset=ISO-8859-1
 >>>  >>
 >>>  >>As discussed in chapter 1 of your PhD thesis,  when network is
 >>> congested,
 >>>  >>retransmission dominate the traffic and effective throughput diminshes
 >>>  >>rapidly, leading to a deteriorating situation. This can be illustrated
 >>> in
 >>>  >>the well known figure with two turning points Knee and Cliff.
 >>>  >>
 >>>  >>
 >>>  >>     I wonder, however, does the situation the same if rateless erasure
 >>>  >>code (say fountain codes) is used?  As with erasure code, no ACK and
 >>>  >>retransmission is needed except when the whole file is completed. So
 >>> even
 >>>  >>heavy loaded, the network is still busy with effective data packet,
 >>> right?
 >>>  >>Although queueing delay will increase, I believe that  the network
 >>>  >>throughput  will not  suffer the plunge as un-coded network.
 >>>  >>
 >>>  >>
 >>>  >>
 >>>  >>Kara
 >>>  >>
 >>>  >>
 >>>  >>
 >>>  >>
 >>>  >>
 >>>  >>
 >>>  >>2013/3/5 Srinivasan Keshav <keshav at uwaterloo.ca>
 >>>  >>
 >>>  >>> To answer this question, I put together some slides for a
 >>> presentation at
 >>>  >>> the IRTF ICCRG Workshop in 2007 [1]. In a nutshell, to save costs, we
 >>>  >>> always size a shared resource (such as a link or a router) smaller
 >>> than the
 >>>  >>> sum of peak demands. This can result in transient or persistent
 >>> overloads,
 >>>  >>> reducing user-perceived performance. Transient overloads are easily
 >>>  >>> relieved by a buffer, but persistent overload requires reductions of
 >>> source
 >>>  >>> loads, which is the role of congestion control. Lacking congestion
 >>> control,
 >>>  >>> or worse, with an inappropriate response to a performance problem
 >>> (such as
 >>>  >>> by increasing the load), shared network resources are always
 >>> overloaded
 >>>  >>> leading to delays, losses, and eventually collapse, where every
 >>> packet that
 >>>  >>> is sent is a retransmission and no source makes progress. A more
 >>> detailed
 >>>  >>> description can also be found in chapter 1 of my PhD thesis [2].
 >>>  >>>
 >>>  >>> Incidentally, the distributed optimization approach that Jon
 >>> mentioned is
 >>>  >>> described beautifully in [3].
 >>>  >>>
 >>>  >>> hope this helps,
 >>>  >>> keshav
 >>>  >>>
 >>>  >>> [1] Congestion and Congestion Control, Presentation at IRTF ICCRG
 >>>  >>> Workshop, PFLDnet, 2007, Los Angeles (California), USA, February 2007.
 >>>  >>>
 >>> http://blizzard.cs.uwaterloo.ca/keshav/home/Papers/data/07/congestion.pdf
 >>>  >>>
 >>>  >>> [2] S. Keshav, Congestion Control in Computer Networks PhD Thesis,
 >>>  >>> published as UC Berkeley TR-654, September 1991
 >>>  >>>
 >>> http://blizzard.cs.uwaterloo.ca/keshav/home/Papers/data/91/thesis/ch1.pdf
 >>>  >>>
 >>>  >>> [3] Palomar, Daniel P., and Mung Chiang. "A tutorial on decomposition
 >>>  >>> methods for network utility maximization." Selected Areas in
 >>>  >>> Communications, IEEE Journal on 24.8 (2006): 1439-1451.
 >>>  >>> http://www.princeton.edu/~chiangm/decomptutorial.pdf
 >>>  >>>
 >>>  >>>
 >>>  >>>
 >>>  >>
 >>>  >>--f46d0444e84964e1a304d740bdcd
 >>>  >>Content-Type: text/html; charset=ISO-8859-1
 >>>  >>Content-Transfer-Encoding: quoted-printable
 >>>  >>
 >>>  >>As discussed in chapter 1 of your PhD thesis,=A0 when network is
 >>> congested,=
 >>>  >> retransmission dominate the traffic and effective throughput diminshes
 >>> rap=
 >>>  >>idly, leading to a deteriorating situation. This can be illustrated in
 >>> the =
 >>>  >>well known figure with two turning points Knee and Cliff. <br>
 >>>  >><img
 >>> src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAOUAAAFECAIAAABXn=
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 >>>
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 >>>
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 >>>  >>u27fv9OnT5eXlrU9oC5BwpdForq6u48ePX7BgwcuXL8XG90P6a2VlpYWFRWRkJMqg0XsUWaj6Q3=
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 >>>
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 >>>
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 >>>  >>u3ff/8tLCwEn/L4CQSCly9fbtiwYdmyZTdu3KDT6UTHxCG0D1y/fh3erfc4C4iW+bMgh9TV1Z8/=
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 >>>
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 >>>
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 >>>
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 >>>  >>T1+/PjAgQNJJBKJRFq/fn1ubi7RLdlPIQAAZDI5ODg4Jyen6yr6fXEgPQdKCgBAQkLCypUrpaSk=
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 >>>  >>AzXVTDPTV1dHYfDgf923Xvbw/gKAflaVFSUl5dna2u7efPmhIQEFovFZrO7OTyKx+Pl5uZWVFTg=
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 >>>  >>du3Ghubg5Sb+ACn3wcx0F2o+7ubhBwi2HY4OAgi8ViMpnAVAwfNTg4yOFwCgoKfv31V2NjY3BG/=
 >>>
 >>>  >>V+LrwdcNLY9XKHmLnMz4UZyTSqHxxm5xAO/EdsdWrEFZBKXyyWRSOvXr798+TKTycQEbmU4jnd1=
 >>>
 >>>  >>dcXGxjo6OlpYWMTGxrJYLA6Hk5+f7+3t7eXlRSKRSkpKQGbP1tbW6Ohof3//u3fvrlmzxtDQEDz=
 >>>
 >>>  >>qfdEHJoxhfN3lo3wywtgi1dog3Ngjw4Mz0E8QBB/j83g8Aifa+lohg8Unwvu9AKqYDg0NBQUFbd=
 >>>
 >>>  >>iwAfAVfE4QBJPJdHV1NTY2trW11dHROXDgQGpqalFR0alTp/bs2WNnZ3fhwoVHjx61t7fTaDQ7O=
 >>>
 >>>  >>7vjx4/b2NhoamouWLDAyMiIyWTifzX5KvVw7Q7Xnb/aqyhaKxk9PRucF+yX5xeSExL3Ku485bwB=
 >>>
 >>>  >>5UxuU25Ja0lgbiCNRfugKrwRoPDj8XhBQUE///yzmZlZd3c3+KS2tjYsLExBQeHEiRNdXV3FxcU=
 >>>
 >>>  >>HDhzw9vYuKirS1tbesWPHkydPzp8/b2ho2NzcTKVSt2zZYmhoWF9f7+bmtnz5cgMDA2Dt/4vwtb=
 >>>
 >>>  >>OzkyAIieW6P/x87me563K/Wu6Su75d2kpG3VXd0Nto1ZVVP9/ZcDfynonPeRWbXbee3UorTetid=
 >>>
 >>>  >>b3ryr9PgOv6oaGh4OBgIF8ZDAZBEHQ63cHB4dChQ4sWLdLW1gaB0SYmJiB34oULFzZv3nz58mUT=
 >>>
 >>>  >>ExPA18DAwNWrV3t7exMEUVhYqKysbGJiAlXhPzeG8bX3UW/8xdgw05D0W6mvbr2IOR3tfsr9H6f=
 >>>
 >>>  >>++dP51ZZ+Vrstdi+98I9dzr+c8TYwDzRv6Gr8K3TQxDBtNOCC8+eDgoLWrl1rbm7OYDAwDKNSqa=
 >>>
 >>>  >>qqqvv37//hhx8OHTrU0dHBYDCMjIx8fHxCQkLWrFmjpKQUExMDNvErKytBcJ+dnV1vb29CQsKWL=
 >>>
 >>>  >>VuMjY3huYp/Mgj1oYSEhJyc3H/5mmSWXGBcWGpcVnulufZiE9WQWmNZuezC94ccj/x45cdvb3+1=
 >>>
 >>>  >>1nb5kivffn/pB5MnZ/OrcvmYuOePf1cYSdaPPvoI2F8HBgbc3Nx+/PFHXV3d58+f5+fnm5mZ/fT=
 >>>
 >>>  >>TT46OjsePH1dUVAwKCgoICDhy5Eh4eLibm9v8+fMVFRXDw8PPnDmzbds2X1/ftLQ0FRUVVVVVNz=
 >>>
 >>>  >>c3dXX1L7/8Ultbu7VVHANC3x5j8dXvelTy40qyZf6NQ8GUa3lUqwJ/3bDtt2XXXF0u6/rTmofLF=
 >>>
 >>>  >>9/7f98/+oes2w/HQn5zfm7f9cFA+xq8jq84jvf29j59+lRHR+fSpUve3t6urq4GBgba2tpZWVkx=
 >>>
 >>>  >>MTFHjx49ffr0+fPnr1+/XlZWlpqaqqqqKi0tbWxsfPr0aQUFBVNT05KSkidPngCvKGVl5dWrV1+=
 >>>
 >>>  >>+fLmuru5dN1okGIuvVY6VbZG0ZI9c4+N3oq0LHl5Lengj8ICx4qnr23dd3SizZ/6JaysCXtmmNc=
 >>>
 >>>  >>QlVcfGlyW0Mzs+8HVUjCTr9OnTcRwH8rWmpqawsLCoqKi0tLSoqOjVq1elpaU9PT0sFqugoCAiI=
 >>>
 >>>  >>iI1NbW2tra/v5/BYKSlpXl4eISFhRUUFCQmJsbGxnZ3d3d1dcXHx5NIpOjo6KCgoIKCAqBavOt2=
 >>>
 >>>  >>Tz5G5SuNRiMIQoLtymE95rHd+ZU2FfGGidQjRUUmHZsfrF5z96elt/653Giu6v01mqS9ak9+0/c=
 >>>
 >>>  >>7Hfo8lMakfTDEjorXyVeIkYZtsKFFEATwBCAEJ3kQBDE4OAgj+IaGhnDkVFscx9Go1D8fZV/H1+=
 >>>
 >>>  >>vXr0s0OPVUWHMa7g22W7bmnKO6aTxOOZquFrxLyn3z7JuzFjz4xx6yhpyH/GG/ww6JDuXN5aN2+=
 >>>
 >>>  >>gcQBCExGsbzQ/z17nyvY/mfGyO7cdu2bf+Vr+XW9PbHPfUOtBdWNbV3mAnGKZrr95NKSWH1Ida5=
 >>>
 >>>  >>9w6Faxgnnfg1UMkixSqrPquzv/Ndt0V8MWG+foAQRnbj5s2b/8vXZF963n1esX1/jkN/qOVQ1G3=
 >>>
 >>>  >>89u9P5n7xxZGNR112hz+7kRF7vSTfpSnc4nkqOSOFkuLzxMdrBLw/4ANej5GEGSMmGUYmA7i7u7=
 >>>
 >>>  >>u6uoaFhbW0tBCjxsd+wAeILT7w9QPeJ3zg6we8T/jA1w94n/D/AWQx0gRPTdK4AAAAAElFTkSuQ=
 >>>  >>mCC" alt=3D""><br>
 >>>  >><br>=A0=A0=A0=A0 I wonder, however, does the situation the same if
 >>> rateless=
 >>>  >> erasure code (say fountain codes) is used?=A0 As with erasure code, no
 >>> ACK=
 >>>  >> and retransmission is needed except when the whole file is completed.
 >>> So e=
 >>>  >>ven heavy loaded, the network is still busy with effective data packet,
 >>> rig=
 >>>  >>ht?=A0 Although queueing delay will increase, I believe that=A0 the
 >>> network=
 >>>  >> throughput=A0 will not=A0 suffer the plunge as un-coded network. <br>
 >>>  >><br>=A0<br><br>Kara<br><br><br><br><br><br><br><div
 >>> class=3D"gmail_quote">2=
 >>>  >>013/3/5 Srinivasan Keshav <span dir=3D"ltr">&lt;<a href=3D"mailto:
 >>> keshav at uw=
 >>>  >>aterloo.ca" target=3D"_blank">keshav at uwaterloo.ca
 >>> </a>&gt;</span><br><blockq=
 >>>  >>uote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1px
 >>> #ccc =
 >>>  >>solid;padding-left:1ex">
 >>>  >>
 >>>  >>To answer this question, I put together some slides for a presentation
 >>> at t=
 >>>  >>he IRTF ICCRG Workshop in 2007 [1]. In a nutshell, to save costs, we
 >>> always=
 >>>  >> size a shared resource (such as a link or a router) smaller than the
 >>> sum o=
 >>>  >>f peak demands. This can result in transient or persistent overloads,
 >>> reduc=
 >>>  >>ing user-perceived performance. Transient overloads are easily relieved
 >>> by =
 >>>  >>a buffer, but persistent overload requires reductions of source loads,
 >>> whic=
 >>>  >>h is the role of congestion control. Lacking congestion control, or
 >>> worse, =
 >>>  >>with an inappropriate response to a performance problem (such as by
 >>> increas=
 >>>  >>ing the load), shared network resources are always overloaded leading
 >>> to de=
 >>>  >>lays, losses, and eventually collapse, where every packet that is sent
 >>> is a=
 >>>  >> retransmission and no source makes progress. A more detailed
 >>> description c=
 >>>  >>an also be found in chapter 1 of my PhD thesis [2].<br>
 >>>  >>
 >>>  >>
 >>>  >><br>
 >>>  >>Incidentally, the distributed optimization approach that Jon mentioned
 >>> is d=
 >>>  >>escribed beautifully in [3].<br>
 >>>  >><br>
 >>>  >>hope this helps,<br>
 >>>  >>keshav<br>
 >>>  >><br>
 >>>  >>[1] Congestion and Congestion Control, Presentation at IRTF ICCRG
 >>> Workshop,=
 >>>  >> PFLDnet, 2007, Los Angeles (California), USA, February 2007.<br>
 >>>  >><a href=3D"
 >>> http://blizzard.cs.uwaterloo.ca/keshav/home/Papers/data/07/conge=
 >>>  >>stion.pdf" target=3D"_blank">
 >>> http://blizzard.cs.uwaterloo.ca/keshav/home/Pa=
 >>>  >>pers/data/07/congestion.pdf</a><br>
 >>>  >><br>
 >>>  >>[2] S. Keshav, Congestion Control in Computer Networks PhD Thesis,
 >>> publishe=
 >>>  >>d as UC Berkeley TR-654, September 1991<br>
 >>>  >><a href=3D"
 >>> http://blizzard.cs.uwaterloo.ca/keshav/home/Papers/data/91/thesi=
 >>>  >>s/ch1.pdf" target=3D"_blank">
 >>> http://blizzard.cs.uwaterloo.ca/keshav/home/Pa=
 >>>  >>pers/data/91/thesis/ch1.pdf</a><br>
 >>>  >><br>
 >>>  >>[3] Palomar, Daniel P., and Mung Chiang. &quot;A tutorial on
 >>> decomposition =
 >>>  >>methods for network utility maximization.&quot; Selected Areas in
 >>> Communica=
 >>>  >>tions, IEEE Journal on 24.8 (2006): 1439-1451.<br>
 >>>  >><a href=3D"http://www.princeton.edu/~chiangm/decomptutorial.pdf"
 >>> target=3D"=
 >>>  >>_blank">http://www.princeton.edu/~chiangm/decomptutorial.pdf</a><br>
 >>>  >><br>
 >>>  >><br>
 >>>  >></blockquote></div><br>
 >>>  >>
 >>>  >>--f46d0444e84964e1a304d740bdcd--
 >>>
 >>>  cheers
 >>>
 >>>    jon
 >>>
 >>>
 >>
 >>--e89a8ff1c4e2529bed04d742b110
 >>Content-Type: text/html; charset=ISO-8859-1
 >>Content-Transfer-Encoding: quoted-printable
 >>
 >>1. With fountain codes, for k original packets, infinite number of encoded =
 >>packets can be generated and the receiver can recover the k packets with an=
 >>y k(1+ e) coded packets.<br><br>2. Suppose all flows are coded, and=A0 the =
 >>short term packet arrival rate of some flows=A0 exceeds=A0 the service rate=
 >> of the network.=A0 Overflow and packet loss could happen wheather the pack=
 >>et coded or not. <br>
 >><br>=A0My point is, I do not think the effective throughput will plunge=A0 =
 >>with coded flows , although the buffers are full. The network is in full sw=
 >>ing and the worst delay of a flow is=A0 the sum of the=A0 maximum queue tim=
 >>e of the routers along the path.=A0 <br>
 >><br>I think there will not be a cliff in the throughput-load figure, insdea=
 >>d, the curve will go beyond the Knee and reach a constant throughput. <br><=
 >>br>=A0<br>=A0=A0 <br><br>=A0=A0 <br><br><br><br><div class=3D"gmail_quote">=
 >>2013/3/6 Jon Crowcroft <span dir=3D"ltr">&lt;<a href=3D"mailto:Jon.Crowcrof=
 >>t at cl.cam.ac.uk" target=3D"_blank">Jon.Crowcroft at cl.cam.ac.uk</a>&gt;</span>=
 >><br>
 >><blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex">there&#39;s no free lunch - if the queue kee=
 >>ps being filled, you&#39;ll get increasing<br>
 >>packet loss - to cover the loss, you&#39;ll need more redundency in your er=
 >>asure<br>
 >>coding - this will cost you more delay at source (in constructing more<br>
 >>redundency) and more overhead in the net, which is a positive feedback loop=
 >>,<br>
 >>just like retransmitting a whole window into a congested queue/path - a<br>
 >>&quot;vicious cycle&quot; as opposed to a virtuous one...<br>
 >><br>
 >>so all that erasure codes buy you is delaying the point when you go over th=
 >>e<br>
 >>clif<br>
 >><br>
 >>In missive &lt;<a href=3D"mailto:CANZhn5Gqyw6-XpaB2-XKmbahKidOap%2BZDqGAJ2N=
 >>qdMBxmYAP-w at mail.gmail.com">CANZhn5Gqyw6-XpaB2-XKmbahKidOap+ZDqGAJ2NqdMBxmY=
 >>AP-w at mail.gmail.com</a>&gt;, shun cai<br>
 >>=A0typed:<br>
 >><br>
 >>=A0&gt;&gt;--f46d0444e84964e1a304d740bdcd<br>
 >>=A0&gt;&gt;Content-Type: text/plain; charset=3DISO-8859-1<br>
 >><div class=3D"im">=A0&gt;&gt;<br>
 >>=A0&gt;&gt;As discussed in chapter 1 of your PhD thesis, =A0when network is=
 >> congested,<br>
 >>=A0&gt;&gt;retransmission dominate the traffic and effective throughput dim=
 >>inshes<br>
 >>=A0&gt;&gt;rapidly, leading to a deteriorating situation. This can be illus=
 >>trated in<br>
 >>=A0&gt;&gt;the well known figure with two turning points Knee and Cliff.<br=
 >>>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >></div><div><div class=3D"h5">=A0&gt;&gt; =A0 =A0 I wonder, however, does th=
 >>e situation the same if rateless erasure<br>
 >>=A0&gt;&gt;code (say fountain codes) is used? =A0As with erasure code, no A=
 >>CK and<br>
 >>=A0&gt;&gt;retransmission is needed except when the whole file is completed=
 >>. So even<br>
 >>=A0&gt;&gt;heavy loaded, the network is still busy with effective data pack=
 >>et, right?<br>
 >>=A0&gt;&gt;Although queueing delay will increase, I believe that =A0the net=
 >>work<br>
 >>=A0&gt;&gt;throughput =A0will not =A0suffer the plunge as un-coded network.=
 >><br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;Kara<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;2013/3/5 Srinivasan Keshav &lt;<a href=3D"mailto:keshav at uwaterlo=
 >>o.ca">keshav at uwaterloo.ca</a>&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;&gt; To answer this question, I put together some slides for a p=
 >>resentation at<br>
 >>=A0&gt;&gt;&gt; the IRTF ICCRG Workshop in 2007 [1]. In a nutshell, to save=
 >> costs, we<br>
 >>=A0&gt;&gt;&gt; always size a shared resource (such as a link or a router) =
 >>smaller than the<br>
 >>=A0&gt;&gt;&gt; sum of peak demands. This can result in transient or persis=
 >>tent overloads,<br>
 >>=A0&gt;&gt;&gt; reducing user-perceived performance. Transient overloads ar=
 >>e easily<br>
 >>=A0&gt;&gt;&gt; relieved by a buffer, but persistent overload requires redu=
 >>ctions of source<br>
 >>=A0&gt;&gt;&gt; loads, which is the role of congestion control. Lacking con=
 >>gestion control,<br>
 >>=A0&gt;&gt;&gt; or worse, with an inappropriate response to a performance p=
 >>roblem (such as<br>
 >>=A0&gt;&gt;&gt; by increasing the load), shared network resources are alway=
 >>s overloaded<br>
 >>=A0&gt;&gt;&gt; leading to delays, losses, and eventually collapse, where e=
 >>very packet that<br>
 >>=A0&gt;&gt;&gt; is sent is a retransmission and no source makes progress. A=
 >> more detailed<br>
 >>=A0&gt;&gt;&gt; description can also be found in chapter 1 of my PhD thesis=
 >> [2].<br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;&gt; Incidentally, the distributed optimization approach that Jo=
 >>n mentioned is<br>
 >>=A0&gt;&gt;&gt; described beautifully in [3].<br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;&gt; hope this helps,<br>
 >>=A0&gt;&gt;&gt; keshav<br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;&gt; [1] Congestion and Congestion Control, Presentation at IRTF=
 >> ICCRG<br>
 >>=A0&gt;&gt;&gt; Workshop, PFLDnet, 2007, Los Angeles (California), USA, Feb=
 >>ruary 2007.<br>
 >>=A0&gt;&gt;&gt; <a href=3D"http://blizzard.cs.uwaterloo.ca/keshav/home/Pape=
 >>rs/data/07/congestion.pdf" target=3D"_blank">http://blizzard.cs.uwaterloo.c=
 >>a/keshav/home/Papers/data/07/congestion.pdf</a><br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;&gt; [2] S. Keshav, Congestion Control in Computer Networks PhD =
 >>Thesis,<br>
 >>=A0&gt;&gt;&gt; published as UC Berkeley TR-654, September 1991<br>
 >>=A0&gt;&gt;&gt; <a href=3D"http://blizzard.cs.uwaterloo.ca/keshav/home/Pape=
 >>rs/data/91/thesis/ch1.pdf" target=3D"_blank">http://blizzard.cs.uwaterloo.c=
 >>a/keshav/home/Papers/data/91/thesis/ch1.pdf</a><br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;&gt; [3] Palomar, Daniel P., and Mung Chiang. &quot;A tutorial o=
 >>n decomposition<br>
 >>=A0&gt;&gt;&gt; methods for network utility maximization.&quot; Selected Ar=
 >>eas in<br>
 >>=A0&gt;&gt;&gt; Communications, IEEE Journal on 24.8 (2006): 1439-1451.<br>
 >>=A0&gt;&gt;&gt; <a href=3D"http://www.princeton.edu/~chiangm/decomptutorial=
 >>.pdf" target=3D"_blank">http://www.princeton.edu/~chiangm/decomptutorial.pd=
 >>f</a><br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >></div></div>=A0&gt;&gt;--f46d0444e84964e1a304d740bdcd<br>
 >>=A0&gt;&gt;Content-Type: text/html; charset=3DISO-8859-1<br>
 >>=A0&gt;&gt;Content-Transfer-Encoding: quoted-printable<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;As discussed in chapter 1 of your PhD thesis,=3DA0 when network =
 >>is congested,=3D<br>
 >>=A0&gt;&gt; retransmission dominate the traffic and effective throughput di=
 >>minshes rap=3D<br>
 >>=A0&gt;&gt;idly, leading to a deteriorating situation. This can be illustra=
 >>ted in the =3D<br>
 >>=A0&gt;&gt;well known figure with two turning points Knee and Cliff. &lt;br=
 >>&gt;<br>
 >>=A0&gt;&gt;&lt;img src=3D3D&quot;data:image/png;base64,iVBORw0KGgoAAAANSUhE=
 >>UgAAAOUAAAFECAIAAABXn=3D<br>
 >>=A0&gt;&gt;G6+AAAgAElEQVR4nOxdZ1xTydeOFfuqq7uL69rL7uqquy5WXFRELKiAWMDeUFEQU=
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 >>=A0&gt;&gt;Tz5G5SuNRiMIQoLtymE95rHd+ZU2FfGGidQjRUUmHZsfrF5z96elt/653Giu6v01=
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 >>=A0&gt;&gt;7Hfo8lMakfTDEjorXyVeIkYZtsKFFEATwBCAEJ3kQBDE4OAgj+IaGhnDkVFscx9G=
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 >>=A0&gt;&gt;vXr0s0OPVUWHMa7g22W7bmnKO6aTxOOZquFrxLyn3z7JuzFjz4xx6yhpyH/GG/ww=
 >>6JDuXN5aN2+=3D<br>
 >>=A0&gt;&gt;gcQBCExGsbzQ/z17nyvY/mfGyO7cdu2bf+Vr+XW9PbHPfUOtBdWNbV3mAnGKZrr9=
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 >>=A0&gt;&gt;9w6Faxgnnfg1UMkixSqrPquzv/Ndt0V8MWG+foAQRnbj5s2b/8vXZF963n1esX1/=
 >>jkN/qOVQ1G3=3D<br>
 >>=A0&gt;&gt;89u9P5n7xxZGNR112hz+7kRF7vSTfpSnc4nkqOSOFkuLzxMdrBLw/4ANej5GEGSM=
 >>mGUYmA7i7u7=3D<br>
 >>=A0&gt;&gt;u6uoaFhbW0tBCjxsd+wAeILT7w9QPeJ3zg6we8T/jA1w94n/D/AWQx0gRPTdK4AA=
 >>AAAElFTkSuQ=3D<br>
 >>=A0&gt;&gt;mCC&quot; alt=3D3D&quot;&quot;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;=3DA0=3DA0=3DA0=3DA0 I wonder, however, does the situa=
 >>tion the same if rateless=3D<br>
 >>=A0&gt;&gt; erasure code (say fountain codes) is used?=3DA0 As with erasure=
 >> code, no ACK=3D<br>
 >>=A0&gt;&gt; and retransmission is needed except when the whole file is comp=
 >>leted. So e=3D<br>
 >>=A0&gt;&gt;ven heavy loaded, the network is still busy with effective data =
 >>packet, rig=3D<br>
 >>=A0&gt;&gt;ht?=3DA0 Although queueing delay will increase, I believe that=
 >>=3DA0 the network=3D<br>
 >>=A0&gt;&gt; throughput=3DA0 will not=3DA0 suffer the plunge as un-coded net=
 >>work. &lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;=3DA0&lt;br&gt;&lt;br&gt;Kara&lt;br&gt;&lt;br&gt;&lt;b=
 >>r&gt;&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;br&gt;&lt;div class=3D3D&quot;gmail_=
 >>quote&quot;&gt;2=3D<br>
 >>=A0&gt;&gt;013/3/5 Srinivasan Keshav &lt;span dir=3D3D&quot;ltr&quot;&gt;&a=
 >>mp;lt;&lt;a href=3D3D&quot;mailto:<a href=3D"mailto:keshav at uw">keshav at uw</a=
 >>>=3D<br>
 >>=A0&gt;&gt;<a href=3D"http://aterloo.ca" target=3D"_blank">aterloo.ca</a>&q=
 >>uot; target=3D3D&quot;_blank&quot;&gt;<a href=3D"mailto:keshav at uwaterloo.ca=
 >>">keshav at uwaterloo.ca</a>&lt;/a&gt;&amp;gt;&lt;/span&gt;&lt;br&gt;&lt;block=
 >>q=3D<br>
 >>
 >>=A0&gt;&gt;uote class=3D3D&quot;gmail_quote&quot; style=3D3D&quot;margin:0 =
 >>0 0 .8ex;border-left:1px #ccc =3D<br>
 >>=A0&gt;&gt;solid;padding-left:1ex&quot;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;To answer this question, I put together some slides for a presen=
 >>tation at t=3D<br>
 >>=A0&gt;&gt;he IRTF ICCRG Workshop in 2007 [1]. In a nutshell, to save costs=
 >>, we always=3D<br>
 >>=A0&gt;&gt; size a shared resource (such as a link or a router) smaller tha=
 >>n the sum o=3D<br>
 >>=A0&gt;&gt;f peak demands. This can result in transient or persistent overl=
 >>oads, reduc=3D<br>
 >>=A0&gt;&gt;ing user-perceived performance. Transient overloads are easily r=
 >>elieved by =3D<br>
 >>=A0&gt;&gt;a buffer, but persistent overload requires reductions of source =
 >>loads, whic=3D<br>
 >>=A0&gt;&gt;h is the role of congestion control. Lacking congestion control,=
 >> or worse, =3D<br>
 >>=A0&gt;&gt;with an inappropriate response to a performance problem (such as=
 >> by increas=3D<br>
 >>=A0&gt;&gt;ing the load), shared network resources are always overloaded le=
 >>ading to de=3D<br>
 >>=A0&gt;&gt;lays, losses, and eventually collapse, where every packet that i=
 >>s sent is a=3D<br>
 >>=A0&gt;&gt; retransmission and no source makes progress. A more detailed de=
 >>scription c=3D<br>
 >>=A0&gt;&gt;an also be found in chapter 1 of my PhD thesis [2].&lt;br&gt;<br=
 >>>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;Incidentally, the distributed optimization approach that Jon men=
 >>tioned is d=3D<br>
 >>=A0&gt;&gt;escribed beautifully in [3].&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;hope this helps,&lt;br&gt;<br>
 >>=A0&gt;&gt;keshav&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;[1] Congestion and Congestion Control, Presentation at IRTF ICCR=
 >>G Workshop,=3D<br>
 >>=A0&gt;&gt; PFLDnet, 2007, Los Angeles (California), USA, February 2007.&lt=
 >>;br&gt;<br>
 >>=A0&gt;&gt;&lt;a href=3D3D&quot;<a href=3D"http://blizzard.cs.uwaterloo.ca/=
 >>keshav/home/Papers/data/07/conge=3D" target=3D"_blank">http://blizzard.cs.u=
 >>waterloo.ca/keshav/home/Papers/data/07/conge=3D</a><br>
 >>=A0&gt;&gt;stion.pdf&quot; target=3D3D&quot;_blank&quot;&gt;<a href=3D"http=
 >>://blizzard.cs.uwaterloo.ca/keshav/home/Pa=3D" target=3D"_blank">http://bli=
 >>zzard.cs.uwaterloo.ca/keshav/home/Pa=3D</a><br>
 >>=A0&gt;&gt;pers/data/07/congestion.pdf&lt;/a&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;[2] S. Keshav, Congestion Control in Computer Networks PhD Thesi=
 >>s, publishe=3D<br>
 >>=A0&gt;&gt;d as UC Berkeley TR-654, September 1991&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;a href=3D3D&quot;<a href=3D"http://blizzard.cs.uwaterloo.ca/=
 >>keshav/home/Papers/data/91/thesi=3D" target=3D"_blank">http://blizzard.cs.u=
 >>waterloo.ca/keshav/home/Papers/data/91/thesi=3D</a><br>
 >>=A0&gt;&gt;s/ch1.pdf&quot; target=3D3D&quot;_blank&quot;&gt;<a href=3D"http=
 >>://blizzard.cs.uwaterloo.ca/keshav/home/Pa=3D" target=3D"_blank">http://bli=
 >>zzard.cs.uwaterloo.ca/keshav/home/Pa=3D</a><br>
 >>=A0&gt;&gt;pers/data/91/thesis/ch1.pdf&lt;/a&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;[3] Palomar, Daniel P., and Mung Chiang. &amp;quot;A tutorial on=
 >> decomposition =3D<br>
 >>=A0&gt;&gt;methods for network utility maximization.&amp;quot; Selected Are=
 >>as in Communica=3D<br>
 >>=A0&gt;&gt;tions, IEEE Journal on 24.8 (2006): 1439-1451.&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;a href=3D3D&quot;<a href=3D"http://www.princeton.edu/~chiang=
 >>m/decomptutorial.pdf" target=3D"_blank">http://www.princeton.edu/~chiangm/d=
 >>ecomptutorial.pdf</a>&quot; target=3D3D&quot;=3D<br>
 >>=A0&gt;&gt;_blank&quot;&gt;<a href=3D"http://www.princeton.edu/~chiangm/dec=
 >>omptutorial.pdf" target=3D"_blank">http://www.princeton.edu/~chiangm/decomp=
 >>tutorial.pdf</a>&lt;/a&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;&lt;/blockquote&gt;&lt;/div&gt;&lt;br&gt;<br>
 >>=A0&gt;&gt;<br>
 >>=A0&gt;&gt;--f46d0444e84964e1a304d740bdcd--<br>
 >><br>
 >>=A0cheers<br>
 >><span class=3D"HOEnZb"><font color=3D"#888888"><br>
 >>=A0 =A0jon<br>
 >><br>
 >></font></span></blockquote></div><br>
 >>
 >>--e89a8ff1c4e2529bed04d742b110--

 cheers

   jon



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