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TCP - PowerPoint

VIEWS: 44 PAGES: 62

									   Computer Networks
                                 Lecture 2: Protocols and Layering


                            Prof. Younghee Lee




* Some part of this teaching materials are prepared referencing the
  lecture note made by F. Kurose, Keith W. Ross(U. of Massachusetts)



                                                                   1   1
                               Prof. Younghee Lee
   Protocol
 Diplomats  use rules, called protocols, as guides to
  formal interactions
 Communication Protocols: a set of rules that specify
  the format and meaning of messages exchanged
  between computers across a network
  – Format is sometimes called syntax
  – Meaning is sometimes called semantics
  – Timing : sequence, speed matching




                                                 2   2
                        Prof. Younghee Lee
      Layering
   Layering model is a solution to the problem of complexity in
    network protocols
   Model suggests dividing the network protocol into layers,
    each of which solves part of the network communication
    problem
   These layers have several constraints, which ease the
    design problem
    – The software for each layer depends only on the services of the
      software provided by lower layers
    – The software at layer n at the destination receives exactly the same
      protocol message sent by layer n at the sender
   Good for open system

                                                                      3      3
                                  Prof. Younghee Lee
      Layering
   Layering
    – A technique to organize a network system into a
      succession of logically distinct entities, such that the
      service provided by one entity is solely based on the
      service provided by the previous (lower level) entity
    – Use abstractions to hide complexity
    – Can have alternative abstractions at each layer
    – Advantages
        »   Simple and easy to understand
        »   Easy to modify and/or adapt to new situations/technologies
        »   Allow for different solution for different situations
        »   Vendor competition: => open system ( <=> close system)
        »   Sharing, multiplexing, bypassing
        »   Easy to test & analysis
    – Disadvantages




                                                                         4   4
                                            Prof. Younghee Lee
      The need for a Protocol Architecture
   Protocol
    – Service – says what a layer does
    – Interface – says how to access the service
    – Protocol – says how is the service implemented
        » a set of rules and formats that govern the communication between two peers
    – Building blocks of a network architecture
    – Each protocol object has two different interfaces
        » service interface: defines operations on this protocol
        » peer-to-peer interface: defines messages exchanged with peer




                                                                                       Key feature
                                                                                       - Syntax
                                                                                       - Semantics
                                                                                       - Timing
                                                                                          5          5
                                            Prof. Younghee Lee
     The TCP/IP Protocol Architecture
   Internet Architecture
    - Internet Engineering Task Force (IETF)

                                                          • Application layer
                                                          • Host-to-Host, or
                                                          Transport layer
                                                          • Internet layer
                                                          • Network access
                                                          layer
     – Application vs Application Protocol (FTP, HTTP)
     – Features                                           • Physical layer
         » does not imply strict layering
         » hourglass shape
         » design and implementation go hand-in-hand



                                                                    6        6
                                     Prof. Younghee Lee
The TCP/IP Protocol Architecture




                                   7   7
              Prof. Younghee Lee
     Layering: logical communication
                          data
E.g.: transport          application
   take data from app   transport
                         transport
   add addressing,       network
    reliability check       link
                          physical
    info to form
    “datagram”                                     ack      network
                         application                          link
   send datagram to     transport           data           physical
    peer                  network
    wait for peer to        link
                                                                       data
    ack receipt           physical
                                                   application     application
   analogy: post                                  transport       transport
                                                                   transport
    office                                          network         network
                                                      link            link
                                                    physical        physical

                                                                       8         8
                              Prof. Younghee Lee
Layering: physical communication
          data
     application
     transport
      network
        link
      physical
                                   network
     application                     link
     transport                     physical
      network
        link
      physical                                data
                         application      application
                         transport        transport
                          network          network
                            link             link
                          physical         physical

                                                        9   9
                   Prof. Younghee Lee
    Protocol layering and data

   Each layer takes data from above
    adds header information to create new data unit
    passes new data unit to layer below

               source          destination
        M    application       application            M   message
     Ht M    transport         transport        Ht    M   segment
   Hn Ht M    network           network       Hn Ht   M   datagram
Hl Hn Ht M      link              link     Hl Hn Ht   M   frame
              physical          physical


                                                          10   10
                           Prof. Younghee Lee
    The TCP/IP Protocol Architecture
   Operation of TCP/IP




                                               11   11
                          Prof. Younghee Lee
The OSI Protocol Architecture




                                   12   12
              Prof. Younghee Lee
The OSI Protocol Architecture




                                   13   13
              Prof. Younghee Lee
     Comparison of OSI and TCP/IP
 OSI                                 TCP/IP
  – Clean, thought out, explicit OO     – Dirty afterthought to
    design                                already developed
  – Not biased towards any protocol       protocol
  – Good for discussion but bad for     – Lower layers unspecified
    implementation(too many layers,     – Sloppy but practical
    options)                            – unnecessarily complex
  – mature and well tested at a time        » (IP is too simple)
    when similar OSI protocols were
    in the development stage

   – Esperanto                             – English
   – Pascal                                – C
   – Mackintosh                            – MSDOS
                                                                14   14
                               Prof. Younghee Lee
The OSI Protocol Architecture




                                   15   15
              Prof. Younghee Lee
Internetworking




                                  16   16
             Prof. Younghee Lee
A closer look at network structure:
   network edge: applications
    and hosts
   network core:
    – routers
    – network of networks
   access networks, physical
    media: communication links




                                                 17   17
                            Prof. Younghee Lee
 Network Core: Circuit Switching

network resources (e.g.,             dividing link bandwidth
  bandwidth) divided                  into “pieces”
  into “pieces”                        – frequency division
   pieces allocated to calls          – time division
   resource piece idle if not
    used by owning call (no
    sharing)




                                                            18   18
                           Prof. Younghee Lee
 Circuit Switching: FDM and TDM
                                  Example:
FDM
                                  4 users

      frequency

                           time
TDM


      frequency

                           time              19   19
                  Prof. Younghee Lee
Numerical example
   How long does it take to send a file of 640,000
    bits from host A to host B over a circuit-switched
    network?
    – All links are 1.536 Mbps
    – Each link uses TDM with 24 slots/sec
    – 500 msec to establish end-to-end circuit


Let’s work it out!



                                                 20      20
                        Prof. Younghee Lee
 Another numerical example

   How long does it take to send a file of 640,000
    bits from host A to host B over a circuit-
    switched network?
    – All links are 1.536 Mbps
    – Each link uses FDM with 24 channels/frequencies
    – 500 msec to establish end-to-end circuit


Let’s work it out!


                                                    21   21
                        Prof. Younghee Lee
 Network Core: Packet Switching
each end-end data stream                resource contention:
  divided into packets                   aggregate resource
 user A, B packets share                 demand can exceed
  network resources                       amount available
 each packet uses full link             congestion: packets
  bandwidth                               queue, wait for link use
 resources used as needed               store and forward:
                                          packets move one hop
                                          at a time
Bandwidth division into “pieces”             – Node receives complete
    Dedicated allocation                       packet before forwarding
    Resource reservation

                                                                   22     22
                            Prof. Younghee Lee
Packet Switching: Statistical Multiplexing

        10 Mb/s
A       Ethernet     statistical multiplexing       C

                          1.5 Mb/s
    B
          queue of packets
          waiting for output
                 link


                          D                         E
Sequence of A & B packets does not have fixed pattern,
  shared on demand  statistical multiplexing.
  Advantages, Disadvantages?
TDM: each host gets same slot in revolving TDM frame.
                                                        23   23
                               Prof. Younghee Lee
Packet switching versus circuit switching

Packet switching allows more users to use network!
   1 Mb/s link
   each user:
    – 100 kb/s when “active”
    – active 10% of time
                                N users
   circuit-switching:                                     1 Mbps link
    – 10 users
   packet switching:
    – with 35 users,
                                      Q: how did we get value 0.0004?
      probability > 10 active
      less than .0004
                                                                 24     24
                                Prof. Younghee Lee
    Packet switching versus circuit switching
 Is packet switching a “slam dunk winner?”
  Great for bursty data
     – resource sharing
     – simpler, no call setup
  Excessive congestion: packet delay and loss
     – protocols needed for reliable data transfer,
       congestion control
  Q: How to provide circuit-like behavior?
     – bandwidth guarantees needed for audio/video apps
     – still an unsolved problem (chapter 7)
Q: human analogies of reserved resources (circuit switching)
versus on-demand allocation (packet-switching)?
A: office: working desk
                                                               25   25
                                Prof. Younghee Lee
    Packet-switching: store-and-forward
                  L
                      R       R            R
                                      Example:
   Takes L/R seconds to               L = 7.5 Mbits
    transmit (push out)                R = 1.5 Mbps
    packet of L bits on to link
    or R bps                           delay = 15 sec

   Entire packet must
    arrive at router before it           If we divide L bits into n x
    can be transmitted on                 Mbits
    next link: store and                   – Delay?
    forward
   delay = 3L/R (assuming          more on delay shortly …
    zero propagation delay)
                                                                26       26
                             Prof. Younghee Lee
Packet-switched networks: forwarding

   Goal: move packets through routers from source to
    destination
    – we’ll study several path selection (i.e. routing) algorithms
      (chapter 4)
   datagram network:
    – destination address in packet determines next hop
    – routes may change during session
    – analogy: driving, asking directions
   virtual circuit network:
    – each packet carries tag (virtual circuit ID), tag determines next
      hop
    – fixed path determined at call setup time, remains fixed thru call
    – routers maintain per-call state


                                                                     27   27
                               Prof. Younghee Lee
Packet-switched networks




                                    28   28
               Prof. Younghee Lee
Network Taxonomy
                    Telecommunication
                        networks



      Circuit-switched                        Packet-switched
          networks                               networks



FDM                                    Networks          Datagram
          TDM      CDM
                                       with VCs          Networks


• Datagram network is not either connection-oriented
or connectionless.
• Internet provides both connection-oriented (TCP) and
connectionless services (UDP) to apps.
                                                                29   29
                         Prof. Younghee Lee
     How do loss and delay occur?
packets queue in router buffers
   packet arrival rate to link exceeds output link capacity
   packets queue, wait for turn


                                 packet being transmitted (delay)



    A


        B
                                packets queueing (delay)
                  free (available) buffers: arriving packets
                  dropped (loss) if no free buffers                 30   30
                               Prof. Younghee Lee
    Four sources of packet delay

   1. nodal processing:              2. queueing
    – check bit errors                  – time waiting at output link
    – determine output link               for transmission
                                        – depends on congestion
                                          level of router


             transmission
A                             propagation


    B
                nodal
              processing    queueing

                                                                   31   31
                              Prof. Younghee Lee
  Delay in packet-switched networks
3. Transmission delay:           4. Propagation delay:
 R=link bandwidth (bps)          d = length of physical link
 L=packet length (bits)          s = propagation speed in
 time to send bits into            medium (~2x108 m/sec)
   link = L/R                     propagation delay = d/s


                                 Note: s and R are very
                                   different quantities!
          transmission
A                          propagation


    B
             nodal
           processing    queueing                          32    32
                           Prof. Younghee Lee
      Caravan analogy
                             100 km                      100 km
       ten-car      toll                          toll
       caravan     booth                         booth
   Cars “propagate” at                 Time to “push” entire
    100 km/hr                            caravan through toll booth
   Toll booth takes 12 sec to           onto highway = 12*10 =
    service a car (transmission          120 sec
    time)                               Time for last car to
   car~bit; caravan ~ packet            propagate from 1st to 2nd
                                         toll both:
   Q: How long until caravan
                                         100km/(100km/hr)= 1 hr
    is lined up before 2nd toll
    booth?                              A: 62 minutes
                                                                  33   33
                            Prof. Younghee Lee
Caravan analogy (more)
                             100 km                      100 km
       ten-car      toll                          toll
       caravan     booth                         booth
                                     Yes! After 7 min, 1st car at
   Cars now “propagate” at           2nd booth and 3 cars still at
    1000 km/hr                        1st booth.
   Toll booth now takes 1           1st bit of packet can arrive
    min to service a car              at 2nd router before packet
   Q: Will cars arrive to 2nd        is fully transmitted at 1st
    booth before all cars             router!
    serviced at 1st booth?             – See Ethernet applet at AWL
                                         Web site

                                                                  34   34
                            Prof. Younghee Lee
Nodal delay
           d nodal  d proc  d queue  d trans  d prop

   dproc = processing delay
    – typically a few microsecs or less
   dqueue = queuing delay
    – depends on congestion
   dtrans = transmission delay
    – = L/R, significant for low-speed links
   dprop = propagation delay
    – a few microsecs to hundreds of msecs



                                                           35   35
                             Prof. Younghee Lee
Queueing delay (revisited)
   R=link bandwidth (bps)
   L=packet length (bits)
   a=average packet arrival
    rate


traffic intensity = La/R

   La/R ~ 0: average queueing delay small
   La/R -> 1: delays become large
   La/R > 1: more “work” arriving than can be
    serviced, average delay infinite!
                                                 36   36
                           Prof. Younghee Lee
“Real” Internet delays and routes
   What do “real” Internet delay & loss look like?
   Traceroute program: provides delay measurement from
    source to router along end-end Internet path towards
    destination. For all i:
    – sends three packets that will reach router i on path towards
      destination
    – router i will return packets to sender
    – sender times interval between transmission and reply.



      3 probes        3 probes

           3 probes


                                                                37   37
                             Prof. Younghee Lee
“Real” Internet delays and routes
traceroute: gaia.cs.umass.edu to www.eurecom.fr
                                    Three delay measurements from
                                    gaia.cs.umass.edu to cs-gw.cs.umass.edu
1 cs-gw (128.119.240.254) 1 ms 1 ms 2 ms
2 border1-rt-fa5-1-0.gw.umass.edu (128.119.3.145) 1 ms 1 ms 2 ms
3 cht-vbns.gw.umass.edu (128.119.3.130) 6 ms 5 ms 5 ms
4 jn1-at1-0-0-19.wor.vbns.net (204.147.132.129) 16 ms 11 ms 13 ms
5 jn1-so7-0-0-0.wae.vbns.net (204.147.136.136) 21 ms 18 ms 18 ms
6 abilene-vbns.abilene.ucaid.edu (198.32.11.9) 22 ms 18 ms 22 ms
7 nycm-wash.abilene.ucaid.edu (198.32.8.46) 22 ms 22 ms 22 ms trans-oceanic
                                                                   link
8 62.40.103.253 (62.40.103.253) 104 ms 109 ms 106 ms
9 de2-1.de1.de.geant.net (62.40.96.129) 109 ms 102 ms 104 ms
10 de.fr1.fr.geant.net (62.40.96.50) 113 ms 121 ms 114 ms
11 renater-gw.fr1.fr.geant.net (62.40.103.54) 112 ms 114 ms 112 ms
12 nio-n2.cssi.renater.fr (193.51.206.13) 111 ms 114 ms 116 ms
13 nice.cssi.renater.fr (195.220.98.102) 123 ms 125 ms 124 ms
14 r3t2-nice.cssi.renater.fr (195.220.98.110) 126 ms 126 ms 124 ms
15 eurecom-valbonne.r3t2.ft.net (193.48.50.54) 135 ms 128 ms 133 ms
16 194.214.211.25 (194.214.211.25) 126 ms 128 ms 126 ms
17 * * *
18 * * *              * means no response (probe lost, router not replying)
19 fantasia.eurecom.fr (193.55.113.142) 132 ms 128 ms 136 ms
                                                                  38     38
                             Prof. Younghee Lee
Packet loss
 queue (aka buffer) preceding link in buffer has
  finite capacity
 when packet arrives to full queue, packet is
  dropped (aka lost)
 lost packet may be retransmitted by previous
  node, by source end system, or not
  retransmitted at all




                                              39    39
                     Prof. Younghee Lee
      Important Distribution
   Poisson Distribution
    – Distribution of arrivals
         n(T) = # arrivals in [0,T]

       0                                  h                  T=mh
     P(n(T )  k )  ( k )[h   (h)] [1  h   (h)]m  k
                       m              k


                          m!        T                T
                                 [( ) k   (h)][(1  ) m  k   (h)]
                       (m  k )!k! m                  m
                     (T ) k     T     m!         T
                            (1  ) m k        (1  ) m  k   (h)
                       k!        m m (m  k )!     m
                         (T ) k     T (  )( T )                   T
                                            m
                                                          m!
     lim P(n(T )  k )          (1  ) T                         (1  ) k   (h)
     m - 
     h-  0
                           k!        m               m k (m  k )!     m
                        (T ) k  T ( ) k  
                              e          e      ( when T  1,  becomes mean arrival rate)
                          k!           k!
                                    k 
        P(k : m, p)  Pr[X  k ]  e              0, k  0,1,2....
                                    k!
        E[ X ]  
        Var[ X ]  E[ X 2 ]  2  2    2                                               40   40
                                                     Prof. Younghee Lee
         Important Distribution
   Exponential Distribution
tn : the time of the n th arrival,   theinterval  n  tn 1  tn
                                                             (T ) 0 x
F( x)  P{ n  x}  1  P{ n  x}  1  P{n( x)  0)  1         e  1  e x   x  0 Distribution
                                                               0!
                     d
f(x)  P{ n  x}  P{ n  x}  e x                                             x  0 Density
                    dx
      – mean, standard deviation
                                        1
E( x)   xf ( x)dx  xe x dx    x
         0                0      
      – used to refer to a time interval, service time




                                                                                               41        41
                                                   Prof. Younghee Lee
     Why Queuing Analysis?
   Approaches to evaluate performance
    – Do an after-the-fact analysis based on actual values.
    – Make a simple projection by scaling up from existing experience to the
      expected future environment.
    – Develop an analytic model based on queuing theory.
    – Program and run a simulation model




                                                                          42   42
                                   Prof. Younghee Lee
Queuing Models




                                 43   43
            Prof. Younghee Lee
          Queuing Models
        Little’s Theorem
    t                                                                                    ()
 N( ) d
 0
                                                                              N()
                                                                                          ()
          t
  { ( )   ( )}d 
         0
         (t )              (t )                                  T2
  Ti                     (t  t )                        T1
                                                                                          
                                        i
        i 1               
                     i  ( ( t ) 1)
                                                                         ti          t
                 t

Nt        
             N( ) d
                 0
                       t
                      (t )             (t )


   (t ) i 1
                     T   (t  t )
                              i
                   i  ( ( t ) 1)
                                                i

       
    t              (t )
 tTt
lim N t  lim tTt                 N  T
t                  t 

                                                                                         44      44
                                                    Prof. Younghee Lee
  M/M/1 Queue
1-         1--      1--                            1--    1--    1--


   0              1              2              ...                n-1          n           n+1
                                                                                
                              Discrete-time Markov chain for the M/M/1 system

Service statistics - P{sn  s}  1  e  s : exponential distribution with parameter 
                                            (memoryless)
Markov chain formulation : Pij  P{N k 1  j | N k  i}
P00  1     ( )
Pii  1       ( )           i 1
Pi ,i 1     ( )               i0
Pi ,i 1     ( )               i 1
Pij   ( )                         i and j  i, i  1, i  1
                  pn    ( )  pn 1   ( )
                                                                                            45       45
                                            Prof. Younghee Lee
 M/M/1 Queue
 pn    ( )  pn 1   ( )
                                                 ( )
  0, ;         p n   p n 1            lim        0
                                             0 

                                                        
p n  1  p n                               where 
                                                        
pn 1   n 1 p0 ,                         n  0,1,...
                 
                                p0
1   pn    n p0 
    n 0         n 0          1 
pn   n (1   ),                           n  0,1,...
                                                            
                                                                      n
N  lim E{N t }   npn  n (1   )  (1   ) n   (1   ) (  )
                                        n                          n 1
    t 
                  n0       n0                        n0          n  0
                    1                      1                
    (1   )               (1   )                   
                (1   )              (1   ) 2 (1   )   

                                                                              46   46
                                                  Prof. Younghee Lee
  M/M/1 Queue
     N               1
T                 
      (1   )   
The average waiting time in queue, W , is the average delay T less the
                           1
average service time           , so
                           
                       1    1     
                    W     
                         
The average number of customersin queue is
                                 2
                     N Q  W 
                                1 
 : utilizatio n factor,
                                              
                                                            p0
ρ  1- p0 ,                       (1   pn    n p0         ),   p0 is the probabilit y of
                                      n 0    n 0         1 
having no customersin the system.
                                          1                     1    m
(* Statistical Multiplexi ng : T            , * TDM/FDM : T          )
                                                               
                                                                
                                                               m m
                                                                                                 47   47
                                             Prof. Younghee Lee
      Examples
   DB Server
    – LAN with 100 PC and 1 server that maintains DB for a query application.
    – Average time for the server to respond to a query: 1/=0.6 sec
    – At peak time, the query rate =20packets/min=1/3 packets/sec

                                      N             1
     * The average waiting time T                      0.75 seconds
                                        (1   )   
     *   0.2
     * The average waiting time in queue : 0.15 seconds
     *1.5 second responcetime is the maximum acceptable. what percentile at the max. ?
              m (r )   m (r )
         r    q             q

             p k   (1   )  k  1   q
                                           1 m ( r )
                                                      mq (r ) : the rth percentile
       100 k 0           k 0

        90       1 m ( 90 )          1
            1  q ,          mq (90)  1.5 , 90% of all responcesto be less 1.5 senconds
       100                            

                                                                                         48   48
                                            Prof. Younghee Lee
Examples




                                49   49
           Prof. Younghee Lee
Self-Similarity




                                       50   50
                  Prof. Younghee Lee
Self-Similarity: images




                                   51   51
              Prof. Younghee Lee
      Self-Similar Data Traffic
   A deterministic periodic
    function
    – g(t)=g(t+aT)
       a=0,1 ,2…
   nondeterministic self-
    similarity
    – natural landscape,
      distribution of earthquake,
      ocean waves, turbulent
      flow, fluctuations in stock
      market, pattern of errors,
      data traffic communication
      channel


                                                         52   52
                                    Prof. Younghee Lee
     Examples of Self-similar Data Traffic
   World wide Web Traffic
    – Traffic pattern generated by the browsers -> self-similar
   TCP, FTP, and TELNET Traffic
    – TCP: Poisson models underestimates the burstiness of TCP traffic
    – TELNET:
        » connection arrivals: well modeled as poisson
        » packet arrivals: Poisson model underestimates the burstiness
    – FTP:
        »   session arrivals: well modeled as poisson
        »   data connections: Poisson model underestimates the burstiness
        »   the distribution of the number of bytes in each burst: heavy upper tail
        »   plenty of small files, large files(multimedia files)




                                                                                      53   53
                                         Prof. Younghee Lee
    Performance Implications of Self-Similarity
   Ethernet/ISDN Analysis
    – Poor agreement between actual
      waiting time and the estimated
      one
   Ethernet data
    – The higher the load on the
      Ethernet, the higher the
      estimated H or, higher degree of
      self-similarity
    – traditional queuing models to
      predict performance of ATM
      switch node -> small buffers ->
      cell loss far beyond those
      expected -> applies to ATM, FR,
      100BASE-T, WAN router, LAN,
      statistical Mux.                                54   54
                                 Prof. Younghee Lee
  End-to-End Argument
 Think  twice before implementing a functionality
  that you believe that is useful to an application
  at a lower layer
 If the application can implement a functionality
  correctly, implement it a lower layer only as a
  performance enhancement




                                                 55   55
                       Prof. Younghee Lee
Example: Reliable File Transfer
        Host A                         Host B

          Appl.                          Appl.

             OS     OK                    OS




 Solution 1: make each step reliable, and then
  concatenate them
 Solution 2: end-to-end check and retry


                                                 56   56
                  Prof. Younghee Lee
    Discussion
   Solution 1 not complete
    – What happens if the sender or/and receiver misbehave?
   The receiver has to do the check anyway!
   Thus, full functionality can be entirely implemented at
    application layer; no need for reliability from lower layers
   Is there any need to implement reliability at lower layers?

   Yes, but only to improve performance
   Example:
    – assume a high error rate on communication network
    – then, a reliable communication service at datalink layer might help

                                                                   57       57
                                Prof. Younghee Lee
Trade-offs
   Application has more information about the data and the
    semantic of the service it requires (e.g., can check only
    at the end of each data unit)
   A lower layer has more information about constraints in
    data transmission (e.g., packet size, error rate)
    – Note: these trade-offs are a direct result of layering!


 Rule     of Thumb
    – Implementing a functionality at a lower level
      should have minimum performance impact on
      the application that do not use the
      functionality
                                                                58   58
                              Prof. Younghee Lee
Internet & End-to-End Argument
 At network layer provides one simple service:
  best effort datagram (packet) delivery
 Only one higher level service implemented at
  transport layer: reliable data delivery (TCP)
    – performance enhancement; used by a large variety of
      applications (Telnet, FTP, HTTP)
    – does not impact other applications (can use UDP)
   Everything else implemented at application level



                                                   59   59
                       Prof. Younghee Lee
Key Advantages
 The service can be implemented by a large
  variety of network technologies
 Does not require routers to maintain any fined
  grained state about traffic. Thus, network
  architecture is
    – Robust
    – Scalable




                                              60   60
                    Prof. Younghee Lee
Summary: End-to-End Arguments
   If the application can do it, don’t do it at a lower
    layer -- anyway the application knows the best
    what it needs
    – add functionality in lower layers iff it is (1) used and
      improves performances of a large number of
      applications, and (2) does not hurt other applications
   Success story: Internet




                                                        61       61
                         Prof. Younghee Lee
     Ethereal
   http://www.ethereal.com/
    – To get Ethereal code
    – Packet sniffer
    – network protocol analyzer

   http://www.aw-bc.com/kurose_ross/
    – Ethereal Lab

 Traceroute, Tracert
 Ping


                                           62   62
                      Prof. Younghee Lee

								
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