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[MUSIC].Good day viewers, in this segment we'regoing to talk about the uses of networks.And that because it's important for us tounderstand how the network is used, ifwe're going to be able to designeffective networks in the first place.Okay, so as you know we use networks inmany different ways in pretty much allthe places we go.We use networks at work for differentkinds of email, and file sharing, andprinting.At home for different kinds ofentertainment, listening to songs,watching movies, reading the news, aswell as messaging and shopping over theinternet.And we use it when we're on the go toonot just for calls and text, or playinggames, but also for accessing differentkinds of information services, watchingvideos consulting where we are on the map

and so forth.So, there are many different uses ofnetworks and you are familiar with mostof them.But our point here is really not to focuson individuals uses of networks but tryand understand what these particular useslike YouTube and so forth, tell us aboutwhy it is we build networks.Because that's going to help us buildmore effective networks in the future,when we know what networks were trying toaccomplish.

Well, I can give you several reasons whywe build networks, and we're going to nowgo through them in some of the followingslides.One of the first uses that might come tomind, is simply for communication betweenusers.This is a traditional usage of computernetworks, really from the get go.really from the telephone onwards.You might think of using voiceover IPs,sending telephone calls over the network.These days we video conference as well as

instant message and connect people viasocial networks.But it's all about user communication.The point here is that the computernetwork is enabling remote communication,and a particular aspect of the network wewould need to think about to provideremote communication is low latency.If you really want interactivecommunication between people, you need a

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fairly low latency network for thatcommunication to be effective.Another important reason that we buildcomputer networks is for resourcesharing.That is, to allow many different users toaccess the same underlying resource.Now the, the, the classic resource whichwas shared was a, a printer.Imagine in a company network, instead ofgiving everyone an individual printer,you put one on the network and everyoneaccesses it.They're sharing this resource.That's wonderful today, maybe you're notsharing a printer so much, but there areother resources which you're stillsharing.maybe it's a 3D printer today, maybewe're all sharing Google search index.Or even, with sharing machines which arein the cloud, being used.The idea here is that by performing thisresource sharing, we are providing a more

effective, a cost effective way, toaccess resources, and providing dedicatedresources per user.Just think of that, re printer per userversus one printer per work group.in fact, even the network itself, whichis providing a resource called bandwidth.even the bandwidth of the links in thenetwork are being shared by differentusers over time.And this sharing process is calledstatistical multiplexing is the name forit.

And I'll go over that next.Okay, so statistical multiplexing is apretty big fancy name, but all it reallymeans is, sharing of network bandwidth,between different users, according to thestatistics of their demand.multiplexing here is just the fancynetworking word for sharing.So, statistical multiplexing is justsharing bandwidth amongst users.Where the statistics mean just you know,when they choose to access the networkand so forth.

The reason that this is useful, that youwant to do this, is it turns out thatusers of the network are mostly idle.Most of the time you are actually notusing the network in your devices and notusing the network.And when you do use the network, yourtraffic tends to be bursty.So, it's occurring in just these littlespurts of traffic.

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So, this means that we can combine thetraffic of different users, and in thatway we'll get something which is usingthe network really more of the time, mostof the time.And we'll use that resource inside thenetworks such as network bandwidth moreeffectively.At least that's the theory, and the keyquestion for us is, how does it help ifwe statistically multiplex userstogether?So, let's just think about that, and whatI'll do is I'll go over a a simpleexample.This is you know, a little bit artificialbut, but it's mostly to convey the point,so don't take this quite literally justtake the big point out of it.Let's consider for a moment users in anISP netwrok.Here's the ISP network here.This network has 100 megabits per secondof bandwidth to the rest of the network,

the internet we haven't gone overmegabits per second, but just think ofthat as units of bandwidth so, 100 unitsof bandwidth.Now each of the users here wants tosubscribe to 5 megabits per second,that's how much bandwidth maybe you wantat home to ensure that you can watch yourvideos.But the statistical multiplexing bit ofit, is that each user is active only 50%of the time.Actually, that's quite high, many users

might not be active that often, but let'sjust say 50% of the time, at most that'swhen they're active.Well, let's think about different ways todesign this network.Assume that we dedicate bandwidth to eachuser.If we do that, then each user is alwaysgoing to have 5 megabits per second oftheir own throughout, the, that ISP, sothey'll always have it when they need it.How many users can we then support?Well we can support 100 megabits per

second divided by 5 megabits per secondper user, that's 20 users.Okay.But if we think about this case, wherethere are 20 users, let's ask, for thesake of argument, what's the probabilitythat all the bandwidth within the ISP isbeing used?Now the kicker here is we're going toassume that all of the users are

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independent.That's a little bit unrealistic, but it'sgood for thinking about this.So, let's just assuming that all of theusers are independent.this is a probability calculation, someof you may not be familiar with it.Don't worry about it too much.So, there are 20 users.What's the probability that the firstuser is using their 5 megabits persecond?That's a half, what's the probabilitythat the second user is using their 5megabits per second?That's another half, and so on up to the20th user, a half.If you multiply all these together youget a half to the 20th power, and that'sjust a little less than 1 on a million.Wow, so there's only a 1 in a millionchance that all the users are going to beusing there the there bandwidth, so thatthe ISP bandwidth will be used.

So, actually a lot of the time bandwidthinside this ISP will be wasted, can we dobetter by using a little bit of statisticmultiplexing.Well, yes, and that's the point of thisexample.Just imagine now, that I'm changing thenumber of users that same ISP is serving,and it's going to sign up 30 differentusers.They're all going to act independently.What's going to happen?Well, this picture here, this binomial

calculation, shows you the, what islikely to happen if all of the users areindependent.And this graph here is showing you.This is the number of users on the xaxis, the probability that, there acertain number of users will be using thenetwork on the y axis.Now it turns out that according to this,there is only a 2% chance that you'llhave more than 20 users.So, that's this tail here, more than 20,this 2% chance.

That's not very much, actually you cansee the most likely situation is wherewe'll have 15 users using the network,that's the highest probability.this, makes sense because for 30 users,and the probability for each of the usersusing the network is a half, half of 30is 15.That's why 15 is the most likely case.You can see the chance of using all 30

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users, is very, very low.Boy this a this is 2 to the minus 30,this is like one in a billion.Now many of you may not be familiar withthe binomial calculations here, if you'reinterested to learn more you can look upbinomial probabilities on the web andlearn about it.The point here is by going throughcalculations like this, which I wouldneed to use a calculator to use.We can see that if you have 30 users,it's quite likely the number of userswithin the network will be somewherebetween 10 and 20.Well, if we are willing to go with that2% chance that most of the time it willbe okay, then we reach this conclusionhere.We are able to serve more users with thesame sized network, and those users aremany of them are likely to be just ashappy, or almost as happy.This gives us a gain, because now we're

serving 30 users in a network which if wedivided it up for our users individuallywe could only fit 20.And this is sometimes described as astatistical multiplexing gain here, andthe game is 1.5.So we're we're 50% better off by doingthis, and we're able to provide networkservice more cheaply, that's why youwould want to do this.Now of course, the danger here is thatdepending on your model here, we couldget unlucky.

Actually, it's possible that more than 20users would want to use the network.Some of you may realize this, this isquite similar to airline overbooking.Airlines often sell more seats then thehave actually inside their plane, becausethey know that not everyone is likely toshow up.So, if they sell more seats, well, thatwill make their service more costeffective, but every now and again,someone gets a little bit of anunfortunate surprise and they try and

ship people to other flights.Now, here, if we get unlucky and morethan 20 users want to use the network.Maybe the users will have slightlydegraded service, and I'll get 4 megabitsper second instead of 5.And this might be okay sometimes.So, you can see the attraction of thisidea that statistical multiplex on thisresource sharing, isn't as important in

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the design of networks to make them costeffective.Even though my example was a littlesimplistic.Okay, forging ahead, another reason thatwe like to use computer networks is forcontent delivery.Now particularly with the emergence ofthe web you realize that the same contentis now delivered to many users.this used to be web page, now a days thisis videos, so these are actually reallyquite large objects, a large amount ofcontent, the same, exactly the samecontent is delivered to many users.And we find that with computer networks,we can deliver the same information tomore users more efficiently than sendinga separate copy of that information toeach user.We can do this by using what are calledreplicas inside the network.Let me show you how.Okay, so here's a content delivery

scenario, let's just imagine that wedon't use replicas first.So, we have our four users here over onthe right hand side, and we have oursource, this is maybe this is where thevideo is, and we want to say that to allof the users.And as a measure of work we're going touse network hops.sending the video across each individualhop of the network.Well, first of all, the source sendsinformation to the first user, so 1 hop,

2 hop, 3 hops, and we get it there.Now the source sends the same video tothe second user, the third user, you cansee where I'm going here.And the fourth user, and the total numberof network hops we've used, or work we'vedone is 4 by 3.That's 12 network hops in this example.Well now, let's use let's send thecontent by these replicas.Here's a replica node here, so the sourceis the same node here.This is where the video starts off.

The users are over here on the right, butwe've also added this replica node righthere.So, the way we're now going to send thesame video to all of these users is tosend it from the source, once to thereplica that's nearby.And then from the replica, which isdeliberately placed close to the users,will send one copy, a copy to each of the

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users.And guess what, now we're going to take,1, 2, 3, 4 here to the individual usersplus 2 hops here and here, that's a totalof 6 network hops.So, we've done half the work by arrangingthe design of our content distribution.and yet we still go the same video to allof the users.So, with clever designs, we can providemore efficient content distribution innetworks.Another reason for building computernetworks is to let, not peoplecommunicate with one another, but to letcomputers communicate with computers, tointeract with them in different ways.Actually we do this all of the time, whenyou're making buying something on theinternet using e-commerce or making areservation and so forth.You might think of these as very humandriven operations, but once you give thego ahead on your computer, a remote

computer are interacting to perform atransaction.You want to take the human out of theloop a little bit, consider things likehigh frequency trading, where computersare buying and selling many differentstocks, very quickly over time.These kind of operations are becomingmore common, where computers areinteracting across a network.And then the inter, internet, thenetwork, computer network in this case.Is enabling automated information

processing across a range of differentparties.They're all coming together via thenetwork.And yet another interesting use ofcomputer networks is for connectingcomputers to the physical world.We can gather sensor data that computersthat are scattered around the network,and then use the network to send thatinformation to other places.Or we can send commands across theinternet to cause actuators to affect the

real world.So, this is really what's going on withuses such as webcams when you'reobserving, gathering video about theinternet.mobile phones here, are all aboutsensing, where you might gather data suchas location and combine that with dataacross the internet to provide maps ofwhere you are.

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Yet another example, in this case foractuation is something like a door lock,where you can remotely send commands tothe door lock on your front door of yourhouse, so you'd open it up if a friend isvisiting and you're not there.This example is a, a use of computernetworks is an example of a rich,emerging usage.It's starting now and we should see a lotmore of it over time.Okay.Well there are the different uses ofcomputer networks.And to round out this segment, I want totalk about the value of connectivity.And there's an interesting notion here,which is that the, that large networksare more valuable, relatively morevaluable, than smaller ones.So, we have an int, impetus to combinesmall networks together into large ones.So, that's really what brings ussomething like the internet.

This argument for the, the value that'sinherent in connectivity was put forth byBob Metcalfe, shown on the right here.Metcalfe is one of the pioneers ofcomputer networks.he invented something called ethernetthat we'll get to later, one of the mostsuccessful local area networks of alltime.Metcalfe posed this law around 1980.And he posited that the value of anetwork if you have N nodes in it, that'sthe size of the network is proportional

to N squared.The implication of this statement is thatlarger networks are a lot more valuablethan are smaller networks with the samenumber of nodes.And so, we're more likely to want toconnect networks together to realize thatvalue.Let me give you a sense of the intuitionfor where this comes from.You may be wondering what this N squaredhas to do with anything.But imagine here in both of these

pictures, on the left hand side and theright hand side, I have 12 nodes in anetwork.Now on the left hand side I have a largernetwork that has more connectivity, it'smore valuable.This network here is what's called amesh, actually, it's a full mesh.There are 12 nodes here, and each node isconnected to all of the other nodes.

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We think about the number of connectionsin it, well, from each node, here, thereare 12 of them, we can connect to, up to11 other nodes.Here's one connection, here.This is like a unidirectional connectionfrom one node to another.If we consider that, then we have 12times 11, that's 132 differentconnections on the left hand side.On the right hand side, we have two sixnode networks.So inside one of these networks, we have6x5 unidirectional connections, that's30.Plus another 30, that's 60, oops, that's60.So, you can see, that for 12 nodes herewe have a lot more connectivity,potential connections, from one node toanother node in the larger network on theleft hand side than on the right handside.And that's why larger networks are more

valuable.Okay.