1. A day in the life: scenario
browser
DNS server
Comcast network
/13
school network
/24
web page
web server
Google’s network
/19
Link Layer and LANs

2. A day in the life… connecting to the Internet
DHCP
UDP IP
Eth
Phy
DHCP
DHCP
connecting laptop needs to get its own IP address, addr of first-hop router, addr of DNS server: use DHCP
router
(runs DHCP)
DHCP
DHCP request encapsulated in UDP, encapsulated in IP, encapsulated in Ethernet
DHCP
DHCP
UDP IP
Eth
Phy
DHCP
Ethernet frame broadcast (dest: FFFFFFFFFFFF) on LAN, received at router running DHCP server
Ethernet demuxed to IP demuxed, UDP demuxed to DHCP
Link Layer and LANs

3. A day in the life… connecting to the Internet
DHCP
DHCP
UDP IP
Eth
Phy
DHCP server formulates DHCP ACK containing client’s IP address, IP address of first-hop router for client, name & IP address of DNS server
router
(runs DHCP)
encapsulation at DHCP server, frame forwarded (switch learning) through LAN, demultiplexing at client
DHCP
UDP IP
Eth
Phy
DHCP
DHCP
DHCP client receives DHCP ACK reply
DHCP
Client now has IP address, knows name & addr of DNS
server, IP address of its first-hop router
Link Layer and LANs

4. A day in the life… ARP (before DNS, before HTTP)
before sending HTTP request, need IP address of DNS
DNS
UDP IP
Eth
Phy
DNS
router
(runs DHCP)
ARP
ARP query
DNS query created, encapsulated in UDP, encapsulated in IP, encapsulated in Eth. To send frame to router, need MAC address of router interface: ARP
Eth
Phy
ARP
ARP reply
ARP query broadcast, received by router, which replies with ARP reply giving MAC address of router interface
client now knows MAC address of first hop router, so can now send frame containing DNS query
Link Layer and LANs

5. A day in the life… using DNS
UDP IP
Eth
Phy
DNS
DNS server
DNS
UDP IP
Eth
Phy
DNS
router
(runs DHCP)
DNS
DNS
DNS
DNS
Comcast network
/13
IP datagram forwarded from campus network into Comcast network, routed (tables created by RIP, OSPF, IS-IS and/or BGP routing protocols) to DNS server
IP datagram containing DNS query forwarded via LAN switch from client to 1st hop router
demuxed to DNS server
DNS server replies to client with IP address of
Link Layer and LANs

6. A day in the life…TCP connection carrying HTTPIP
Eth
Phy
router
(runs DHCP)
SYN
SYNACK
SYN
to send HTTP request, client first opens TCP socket to web server
TCP IP
Eth
Phy
TCP SYN segment (step 1 in 3-way handshake) inter-domain routed to web server
SYNACK
SYN
SYNACK
web server responds with TCP SYNACK (step 2 in 3-way handshake)
web server
TCP connection established!
Link Layer and LANs

7. Three way handshake
Data Link Layer

8. TCP 3-way handshake client state server state LISTEN SYNSENT
SYNbit=1, Seq=x
choose init seq num, x
send TCP SYN msg
SYN RCVD
ESTAB
SYNbit=1, Seq=y
ACKbit=1; ACKnum=x+1
choose init seq num, y
send TCP SYNACK
msg, acking SYN
ACKbit=1, ACKnum=y+1
received SYNACK(x)
indicates server is live;
send ACK for SYNACK;
this segment may contain
client-to-server data
received ACK(y)
indicates client is live
ESTAB
Transport Layer

9. A day in the life… HTTP request/reply
web page finally (!!!) displayed
HTTP
HTTP
HTTP
TCP IP
Eth
Phy
router
(runs DHCP)
HTTP
HTTP
HTTP request sent into TCP socket
IP datagram containing HTTP request routed to
HTTP
TCP IP
Eth
Phy
HTTP
HTTP
web server responds with HTTP reply (containing web page)
web server
IP datagram containing HTTP reply routed back to client
Link Layer and LANs

10. Chapter 2 Application Layer
A note on the use of these Powerpoint slides:
We’re making these slides freely available to all (faculty, students, readers). They’re in PowerPoint form so you see the animations; and can add, modify, and delete slides (including this one) and slide content to suit your needs. They obviously represent a lot of work on our part. In return for use, we only ask the following:
Computer Networking: A Top Down Approach
If you use these slides (e.g., in a class) that you mention their source (after all, we’d like people to use our book!)
If you post any slides on a www site, that you note that they are adapted from (or perhaps identical to) our slides, and note our copyright of this material.
Thanks and enjoy! JFK/KWR
All material copyright
J.F Kurose and K.W. Ross, All Rights Reserved
7th edition Jim Kurose, Keith Ross Pearson/Addison Wesley April 2016
Application Layer

11. Chapter 2: outline 2.1 principles of network applications
2.2 Web and HTTP
2.3 electronic mail
SMTP, POP3, IMAP
2.4 DNS
2.5 P2P applications
2.6 video streaming and content distribution networks
2.7 socket programming with UDP and TCP
Application Layer

12. Pure P2P architecture no always-on server
arbitrary end systems directly communicate
peers are intermittently connected and change IP addresses
examples:
file distribution (BitTorrent)
Streaming (KanKan)
VoIP (Skype)
Application Layer

13. File distribution: client-server vs P2P
Question: how much time to distribute file (size F) from one server to N peers?
peer upload/download capacity is limited resource
us: server upload capacity u2 d2 u1 d1
di: peer i download capacity
file, size F us
server di uN
network (with abundant
bandwidth) ui dN
ui: peer i upload capacity
Application Layer

14. File distribution time: client-server
server transmission: must sequentially send (upload) N file copies:
time to send one copy: F/us
time to send N copies: NF/us F us di
network ui
client: each client must download file copy
dmin = min client download rate
min client download time: F/dmin
time to distribute F
to N clients using
client-server approach
Dc-s > max{NF/us,,F/dmin}
increases linearly in N
Application Layer

15. File distribution time: P2P
server transmission: must upload at least one copy
time to send one copy: F/us F us di
client: each client must download file copy
min client download time: F/dmin
network ui
clients: as aggregate must download NF bits
max upload rate (limiting max download rate) is us + Sui
time to distribute F
to N clients using
P2P approach
DP2P > max{F/us,,F/dmin,,NF/(us + Sui)}
increases linearly in N …
… but so does this, as each peer brings service capacity
Application Layer

16. Client-server vs. P2P: example
client upload rate = u, F/u = 1 hour, us = 10u, dmin ≥ us
Application Layer

17. P2P file distribution: BitTorrent
file divided into 256Kb chunks
peers in torrent send/receive file chunks
tracker: tracks peers
participating in torrent
torrent: group of peers exchanging chunks of a file
Alice arrives …
… obtains list
of peers from tracker
… and begins exchanging
file chunks with peers in torrent
Application Layer

18. P2P file distribution: BitTorrent
peer joining torrent:
has no chunks, but will accumulate them over time from other peers
registers with tracker to get list of peers, connects to subset of peers (“neighbors”)
while downloading, peer uploads chunks to other peers
peer may change peers with whom it exchanges chunks
churn: peers may come and go
once peer has entire file, it may (selfishly) leave or (altruistically) remain in torrent
Application Layer

19. BitTorrent: requesting, sending file chunks
requesting chunks:
at any given time, different peers have different subsets of file chunks
periodically, Alice asks each peer for list of chunks that they have
Alice requests missing chunks from peers, rarest first
sending chunks: tit-for-tat
Alice sends chunks to those four peers currently sending her chunks at highest rate
other peers are choked by Alice (do not receive chunks from her)
re-evaluate top 4 every10 secs
every 30 secs: randomly select another peer, starts sending chunks
“optimistically unchoke” this peer
newly chosen peer may join top 4
Application Layer

20. BitTorrent: tit-for-tat
(1) Alice “optimistically unchokes” Bob
(2) Alice becomes one of Bob’s top-four providers; Bob reciprocates
(3) Bob becomes one of Alice’s top-four providers
higher upload rate: find better trading partners, get file faster !
Application Layer

21. Overlay Networks And Distributed Hash Tables
Application Layer

22. Distributed Hash Table (DHT)
DHT paradigm
Circular DHT and overlay networks
Peer churn

23. Simple Database Simple database with(key, value) pairs:
key: human name; value: social security #
Key
Value
John Washington
Diana Louise Jones
Xiaoming Liu
Rakesh Gopal
Linda Cohen
…….
………
Lisa Kobayashi
key: movie title; value: IP address

24. Hash Table
More convenient to store and search on numerical representation of key
key = hash(original key)
Original Key
Key
Value
John Washington
Diana Louise Jones
Xiaoming Liu
Rakesh Gopal
Linda Cohen
…….
………
Lisa Kobayashi

25. Distributed Hash Table (DHT)
Distribute (key, value) pairs over millions of peers
pairs are evenly distributed over peers
Any peer can query database with a key
database returns value for the key
To resolve query, small number of messages exchanged among peers
Each peer only knows about a small number of other peers
Robust to peers coming and going (churn)

26. Assign key-value pairs to peers
rule: assign key-value pair to the peer that has the closest ID.
convention: closest is the immediate successor of the key.
e.g., ID space {0,1,2,3,…,63}
suppose 8 peers: 1,12,13,25,32,40,48,60
If key = 51, then assigned to peer 60
If key = 60, then assigned to peer 60
If key = 61, then assigned to peer 1

27. Circular DHT “overlay network”
each peer only aware of immediate successor and predecessor. 1 12 13 25 32 40 48 60

28. Resolving a query 1 value 12 60 13 48 25 O(N) messages
What is the value associated with key 53 ? 1
value 12 60 13 48 25
O(N) messages
on avgerage to resolve
query, when there
are N peers 40 32

29. Circular DHT with shortcuts1 12 13 25 32 40 48 60
What is the value for
key 53
value
each peer keeps track of IP addresses of predecessor, successor, short cuts.
reduced from 6 to 3 messages.
possible to design shortcuts with O(log N) neighbors, O(log N) messages in query

30. Peer churn handling peer churn: example: peer 5 abruptly leaves
peers may come and go (churn)
each peer knows address of its two successors
each peer periodically pings its two successors to check aliveness
if immediate successor leaves, choose next successor as new immediate successor 1 3 4 5 8 10 12 15
example: peer 5 abruptly leaves

31. Peer churn handling peer churn: example: peer 5 abruptly leaves
peers may come and go (churn)
each peer knows address of its two successors
each peer periodically pings its two successors to check aliveness
if immediate successor leaves, choose next successor as new immediate successor 1 3 15 4 12 10 8
example: peer 5 abruptly leaves
peer 4 detects peer 5’s departure; makes 8 its immediate successor
4 asks 8 who its immediate successor is; makes 8’s immediate successor its second successor.

32. Overlay networks Content Distribution Networks
Application Layer

33. Video Streaming and CDNs: context
video traffic: major consumer of Internet bandwidth
Netflix, YouTube: 37%, 16% of downstream residential ISP traffic
~1B YouTube users, ~75M Netflix users
challenge: scale - how to reach ~1B users?
single mega-video server won’t work (why?)
challenge: heterogeneity
different users have different capabilities (e.g., wired versus mobile; bandwidth rich versus bandwidth poor)
solution: distributed, application-level infrastructure
Application Layer

34. Multimedia: video video: sequence of images displayed at constant rate
……………………..
spatial coding example: instead of sending N values of same color (all purple), send only two values: color value (purple) and number of repeated values (N)
……………….…….
frame i
frame i+1
temporal coding example: instead of sending complete frame at i+1, send only differences from frame i
video: sequence of images displayed at constant rate
e.g., 24 images/sec
digital image: array of pixels
each pixel represented by bits
coding: use redundancy within and between images to decrease # bits used to encode image
spatial (within image)
temporal (from one image to next)
Application Layer

35. Multimedia: video CBR: (constant bit rate): video encoding rate fixed
……………………..
spatial coding example: instead of sending N values of same color (all purple), send only two values: color value (purple) and number of repeated values (N)
……………….…….
frame i
frame i+1
temporal coding example: instead of sending complete frame at i+1, send only differences from frame i
CBR: (constant bit rate): video encoding rate fixed
VBR: (variable bit rate): video encoding rate changes as amount of spatial, temporal coding changes
Application Layer

36. Streaming stored video:
simple scenario:
Internet
video server
(stored video)
client
Application Layer

37. Streaming multimedia: DASH
DASH: Dynamic, Adaptive Streaming over HTTP
server:
divides video file into multiple chunks
each chunk stored, encoded at different rates
manifest file: provides URLs for different chunks
client:
periodically measures server-to-client bandwidth
consulting manifest, requests one chunk at a time
chooses maximum coding rate sustainable given current bandwidth
can choose different coding rates at different points in time (depending on available bandwidth at time)
Application Layer

38. Streaming multimedia: DASH
DASH: Dynamic, Adaptive Streaming over HTTP
“intelligence” at client: client determines
when to request chunk (so that buffer starvation, or overflow does not occur)
what encoding rate to request (higher quality when more bandwidth available)
where to request chunk (can request from URL server that is “close” to client or has high available bandwidth)
Application Layer

39. Content distribution networks
challenge: how to stream content (selected from millions of videos) to hundreds of thousands of simultaneous users?
option 1: single, large “mega-server”
single point of failure
point of network congestion
long path to distant clients
multiple copies of video sent over outgoing link
….quite simply: this solution doesn’t scale
Application Layer

40. Content distribution networks
challenge: how to stream content (selected from millions of videos) to hundreds of thousands of simultaneous users?
option 2: store/serve multiple copies of videos at multiple geographically distributed sites (CDN)
enter deep: push CDN servers deep into many access networks
close to users
used by Akamai, 1700 locations
bring home: smaller number (10’s) of larger clusters in POPs (points of presence) near access networks (but not within so not local network cacing)
used by Limelight
Application Layer

41. Content Distribution Networks (CDNs)
CDN: stores copies of content at CDN nodes
e.g. Netflix stores copies of MadMen
subscriber requests content from CDN
directed to nearby copy, retrieves content
may choose different copy if network path congested …
Akamai: 100,000+ servers in clusters in networks in 70+ countries serving trillions of requests a day.
How many people use Netflix?
manifest file
where’s Madmen?
Application Layer 41

42. “over the top” Content Distribution Networks (CDNs) …
Internet host-host communication as a service
peak load: 7million viewers, 2 Tbytes via
OTT challenges: coping with a congested Internet
from which CDN node to retrieve content?
viewer behavior in presence of congestion?
what content to place in which CDN node? 42

43. CDN content access: a closer look
Bob (client) requests video
video stored in CDN at
1. Bob gets URL for video
from netcinema.com web page 1
2. resolve
via Bob’s local DNS 2 5
6. request video from
KINGCDN server,
streamed via HTTP
Bob’s
local DNS
server
netcinema.com
3. netcinema’s DNS returns URL
4&5. Resolve
via KingCDN’s authoritative DNS,
which returns IP address of KingCDN
server with video 4 3
netcinema’s
authoratative DNS
KingCDN.com
KingCDN
authoritative DNS
Application Layer