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111/06/27 1 Kun-chan Lan Department of Computer Science and Information Engineering [email protected] Network Measurements, Modeling and Simulations

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Page 1: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

112/04/18 1

Kun-chan Lan

Department of Computer Science and Information Engineering

[email protected]

Network Measurements, Modeling and Simulations

Page 2: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Some Admin stuff

Paper review list due next weekThe references for homework is post

on the course webpageWe will have a guest speaker on

3/18 to talk about how to do game measurements (related to your homework 2) – No class lecture

Page 3: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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A quick survey…

Why do you come to this class? What do you want to get out of this course?

Page 4: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

1. Learn about ns-2?2. Learn how to measure traffic?3. Learn how to use emulator?4. Somebody suggested you to try it

out?5. None of the above (you have no

idea why you came here!)

112/04/18 4

Page 5: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Outline

• Model and simulate Internet traffic• It’s hard to model and simulate Internet

• Use measurement to improve the realism of your model

• We advocate trace-driven simulation

• Internet and wireless measurements

Page 6: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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The challenges in modeling and simulating Internet traffic

Page 7: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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What is a model?

• Abstraction of real world• Base of a network simulation

• Topology model• e.g. “a dumbbell topology”

• Traffic model• “80% TCP + 20% UDP”

• Queuing model• e.g. “FIFO”, “Fair queuing”, etc.

• …..

Page 8: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Role of simulation• Based on some particular models

• Topology: e.g. dumbell vs. tree• Traffic: e.g. TCP vs. UDP• …

• Widely used by researcher to study Internet• Millions of hosts in different administrative domains

• Simulation vs. experiment (Why simulation?)• Repeatability• Configurability• Scalability• Explore complicated scenarios• Study “future” application/prtotocol/network

Page 9: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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What simulation does’t do

• Realism • Details of simulation matters!• It’s your responsibility to know what level of

details you need to capture in the simulation

• Prove correctness of the model• Only for validation!• The value of simulation relies on a good

model

Page 10: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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It’s hard to simulate Internet

• Network heterogeneity• Rapid and unpredictable change

Page 11: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Network heterogeneity

• Topology• Link properties• Protocol • traffic

• All the above matter when you do the simulation

Page 12: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Difficulty in modeling topology

• Constantly changing• Routing change• Link/node up and down

• ISPs typically do not make topological information available

• There is no “typical” topology • Depends on what are you simulating

Page 13: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Difficulty in modeling links

• large diversities • Speed: e.g. modem vs. fiber optic link• Loss: e.g. cooper wire vs. 802.11• Transmission: point-to-point vs. broadcast• Latency: DSL vs. satellite links

• Routing-dependent• Asymmetry

Page 14: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Difficulty in modeling protocol

• Differences in implementations • 400 different TCP implementations

• Different applications and different traffic mix

Page 15: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Difficulty in modeling traffic

• Traffic is different everywhere• Effect of background traffic

• Queuing, congestion

• Some application are adaptive to network conditions

Page 16: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Rapid and unpredictable changes

• Change in TCP: Reno -> NewReno/SACK• Change in devices: PC->handheld• Change in web: caching -> CDN• Change in killer applicaton:

• web->p2p->VoIP?

• Change in physical layer: wired -> wireless

Page 17: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Coping strategy

• OK, so it’s hard to simulate Internet, but can we do something about it?

• Yes• Systematically explore important

parameters• Searching for invariants

Page 18: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Network behavior as a function

• Explore network behavior as a function of changing parameters• <observed traffic> = f(x1,x2,x3,…..)

• Impossible to explore the whole set of parameters• Challenge: identify important parameters• Example parameters to which a simulation

might be sensitive• Congestion• Topology• Router mechanism (routing, scheduling, etc.)

Page 19: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Search for Invariants

• Invariant: behavior that holds in a very wide range of environment

• Examples• Diurnal patterns• Self-similarity• Poisson session arrival• Heavy-tailed distribution• Geographical topology

• Extract invariants from real world data• Extensive measurements!

Page 20: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Question?

Page 21: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Outline

• Model and simulate Internet traffic• It’s hard to model and simulate Internet• Internet and wireless measurements• Case study: modeling heavy-hitter

traffic

Page 22: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Why measuring?

• To tell us what are the invariants, and what are just artifacts of the system• A base for realistic modeling and

simulation

• A common practice in other science disciplines (physics, biology, etc)

Page 23: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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A measurement plan

What questions you want to answer?Testbed setupHow to collect the traces? And for

how long? What to collect? (what is your

performance metrics)Data analysis

All of these should be in your project report!

Page 24: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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TCP over GPRS network

How fair is TCP over GPRS?

Page 25: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Things I am going to tell you next

• What can you measure?• Things that you need to know when

you measure• Where can you get Internet traffic

measurements for free?

Page 26: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Measure the Internet

• What can you measure• Traffic• Routing• Topology• Performance• Multicast• Wireless/Mobility

Page 27: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Tool for measuring traffic

• Tcpdump/etherreal (libpcap)• Netflow• NetTrMet/RTG (SNMP)

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tcpdump/Ethereal

• tcpdump • Most commonly used packet collector• based on libpcap API• Output can be easily analyzed using awk/perl scripts

• Ethereal • GUI-based• Support various trace formats, including tcpdump, snoop,

etc.• Support various link-layer headers, including 802.11, ATM,

etc.• tcpdpriv

• A commonly used packet anonymizer (to share traces with the others)

• Libpcap-based• Link-level headers are passed through unchanged.

Page 29: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Usage of tcpdump

tcpdump [ -adeflnNOpqStvx ] [ -c count ] [ -F file ]   [ -i interface ] [ -r file ] [ -s

snaplen ] [ -T type ] [ -w file ] [expression ]

Must run as root or have sudo permission

Page 30: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<option>

-i Listen on interface. If unspecified, tcpdump searches the system interface list for the lowest numbered, configured up interface (excluding loopback)

-n Don't convert addresses (i.e., host addresses, port numbers, etc.) to names

Page 31: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<option>

-p Don't put the interface into promiscuous mode.

-q Quick (quiet?) output. Print less protocol information so output lines are shorter.

-r Read packets from file (which was created with the -w option). Standard input is used if file is ``-''.

Page 32: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<option>

-w Write the raw packets to file rather than parsing and printing them out. They can later be printed with the -r option. Standard output is used if file is ``-''.

-r Read packets from file (which was created with the -w option). Standard input is used if file is ``-''.

-S Print absolute, rather than relative, TCP sequence numbers

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<option>-s snarf snaplen bytes of data from each packet rather than

the default of 68. 68 bytes is adequate for IP, ICMP, TCP and UDP but may truncate protocol information from name server and NFS packets. Packets truncated because of a limited snapshot are indicated in the output with ``[|proto]'', where proto is the name of the protocol level at which the truncation has occurred.

Taking larger snapshots both increases the amount of time it takes to process packets and, effectively, decreases the amount of packet buffering. This may cause packets to be lost. - Limit snaplen to the smallest number that will capture the protocol information you're interested in.

Page 34: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<option>

-t Don't print a timestamp on each dump line. -tt Print an unformatted timestamp on each

dump line. -v (Slightly more) verbose output. For example,

the time to live and type of service information in an IP packet is printed.

-vv Even more verbose output. For example, additional fields are printed from NFS reply packets.

-x Print each packet in hex.

Page 35: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<expression>

selects which packets will be dumped. If no expression is given, all packets will be dumped. Otherwise, only packets for which expression is `true' will be dumped.

The expression consists of one or more primitives. Primitives usually consist of an id (name or number) preceded by one or more qualifiers.

There are three different kinds of qualifier. <type> <dir> <proto>

Page 36: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<qualifier>

<type>what kind of thing the id name or number refers to

Possible types are host, net and port

E.g., `host csie.ncku.edu.tw', `net 146.132', `port 20'

If there is no type qualifier, host is assumed.

Page 37: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<qualifier>

<dir> specify a particular transfer direction

to and/or from id. Possible directions are src, dst, src or dst and src and dst.

E.g., `src csie.ncku.edu.tw', `dst net 146.132', `src or dst port ftp-data'.

If there is no dir qualifier, src or dst is assumed

Page 38: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<qualifier>

<proto> restrict the match to a particular protocol. Possible protos are: ether, fddi, ip, arp, rarp,

decnet, lat, sca, moprc, mopdl, tcp and udp. E.g., `ether src server1.ncku.edu.tw', `arp net

128.3', `tcp port 21'. If there is no proto qualifier, all protocols

consistent with the type are assumed. E.g., `src mail.ncku.edu.tw' means `(ip or arp or rarp) src mail.ncku.edu.tw'

Page 39: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Complex expression

complex filter expressions are built up by using the words and, or and not to combine primitives.

E.g., `host csie.ncku.edu.tw and not port ftp and not port ftp-data'.

Iidentical qualifier lists can be omitted. E.g., `tcp dst port ftp or ftp-data

or domain' == `tcp dst port ftp or tcp dst port ftp-data or tcp dst port domain'.

Page 40: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Allowable primitives

dst host host src host host host host ether dst ehost ether src ehost ether host ehost gateway host

Page 41: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Allowable primitives

dst net net src net net net net net net mask mask net net/len

True if the IP address matches net a netmask len bits wide. May be qualified with src or dst.

dst port port src port port

port port

Page 42: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Allowable primitives less length

True if the packet has a length less than or equal to length. This is equivalent to: len <= length.

greater length ip proto protocol

True if the packet is an ip packet of protocol type protocol. Protocol can be a number or one of the names icmp, igrp, udp, nd, or tcp. Note that the identifiers tcp, udp, and icmp are also keywords and must be escaped via backslash (\)

ether broadcast ip broadcast

Page 43: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Allowable primitives

ether multicast ip multicast

ip, arp, rarp, decnet short for: ether proto p where p is one

of the above protocols. tcp, udp, icmp

short for: ip proto p

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Relation operator

expr relop expr relop is one of >, <, >=, <=, =, != expr is an arithmetic expression composed of integer

constants, the normal binary operators [+, -, *, /, &, |], a length operator, and special packet data accessors.

To access data inside the packet, use the following syntax: proto [ expr : size ] Proto is one of ether, fddi, ip, arp, rarp, tcp, udp, or icmp. E.g. tcp[0] means the first byte of the TCP header

For example, `ether[0] & 1 != 0' catches all multicast traffic. The expression `ip[0] & 0xf != 5' catches all IP packets with options.

Page 45: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Combining primitives Primitives may be combined using:

Negation (`!' or `not'). Concatenation (`&&' or `and'). Alternation (`||' or `or').

Negation has highest precedence. Alternation and concatenation have equal precedence and associate left to right..

If an identifier is given without a keyword, the most recent keyword is assumed. E.g., not host vs and ace is short for not host vs

and host ace, which should not be confused with not ( host vs or ace )

Page 46: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Netflow

• Built-in service for most Cisco router/switch that runs Cisco IOS

• Provide flow-level information • First packet in a flow is used to build an

entry in the cache• Per-interface basis• Useful for accounting/billing, traffic

monitoring, user profiling, data mining, etc.

Page 47: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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More on Netflow

• Typical cache size: 4K-128K (typical DRAM size: 2M-8M)• Need to use the cache efficiently

• When to expire netflow cache entries• Idle time > t• Long-lived flows (duration > 30min)• TCP connections with FIN or RST• when cache becomes full (applying some

heuristics to age flows)

Page 48: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Management of Netflow

• Netflow FlowCollector• can collect flow info from multiple NetFlow-enabled devices • data volume reduction through selective filtering and

aggregation • store flow information for off-line analysis

• Netflow FlowAnalyzer• data visualization: graphical data display• data export to external applications (such as Excel)

• Netflow Server• collect flow statistics from multiple FlowCollector• further summarize NetFlow statistics by enabling bi-directional

consolidation• store NetFlow statistics in a common commercial RDBMS (can

be queried via SQL later)• encrypt and compress NetFlow statistics

Page 49: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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NetTrMet

• Collect flow data via SNMP• builds up packet and byte counts for

traffic flows • Flows are defined by their end-point

addresses • Address can be ethernet addresses, IP address

or the combination of both

• Can specify a set of rules to filter the flows of interest

• Run under dos or Unix

Page 50: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RTG

• A SNMP statistics monitoring system • Commonly used by ISPs• collect time-series SNMP data from a large

number of interfaces• Run as a daemon• All collected data is inserted into a relational

database where complex queries and reports may be generated via SQL

• can poll at sub-one-minute intervals • utilities are included to generate traffic reports,

95th percentile reports and graphical data plots

Page 51: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Tool for measuring routing

• Traceroute• tracert command for Windows

• RouteView

Page 52: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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traceroute

• Trace the path from a source to a destination • Show how many hops a packet required to reach

the destination and how long each hop takes. • Utilize IP Time-to-Live (TTL) field• TTL value specifies how many hops a packet is

allowed to travel (decremented by 1 at each hop). An ICMP TIME_EXCEEDED response is returned to the source once TTL reaches 0.

• Send a series of packets and incrementing the TTL value with each successive packet.

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Page 54: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RouteView

• A large collection of BGP routing tables from several backbones (from 60 vantage points and 400+ AS)

• Aim to provide network operators the information about the global routing system from various locations around the Internet

Page 55: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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BGP basics• BGP: an inter-gateway protocol to route

packets between Autonomous System (AS)• AS: a group of networks that is controlled by

a common network administrator on behalf of a single administrative entity. Each AS is assigned a globally unique number

• Convey information about AS path topology• Run on top of TCP (port 179) • A path vector protocol

Page 56: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Path vector protocol

AS100: 180.10.0.0/16 100

AS200: 180.10.0.0/16 200 100

AS300: 180.10.0.0/16 300 200 100 time

Page 57: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Tool for measuring topology

•traceroute-based•Skitter•Rocketfuel

Page 58: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Skitter

• effort of CAIDA• ICMP-based: similar to traceroute• probing the paths from a source to

many destinations IP addresses spread throughout the IPv4 address space

• RTT and forward paths are collected

Page 59: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Rocketfuel

• Input• traceroute (utilizing public available

tracroute servers)• BGP• DNS

• Output (per ISP)• Backbone• POP• Peer links

Page 60: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Path discovery• Use 750 public available traceroute sources• Merge traceroute paths from multiple sources to

multiple destinations to obtain network map• Brute-force (all src × all dest) approach does not work

• Too many addresses to probe (150M!)• Too much load for the traceroute server• Too much traffic for the network

• Approach• Only probe the paths which are most “relevant”

• Paths that transit the targeted ISP• Omit redundant paths

• Other challenges• Alias: one router might have multiple IP addresses, one for

each of its interfaces• Geographical location of the router

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Selected measurements

• per-ISP map• Only choose traceroutes that are expected

to transit the ISP (direct probing)• Use BGP routing tables• Data: from RouteView

• Path reduction• Some probes might have identical paths inside

the ISP

Page 62: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Use BGP to choose traceroute

1.2.3.0/24 8 11 4 2 5

destination AS path

closer to destination

traceroutes that are likely to traverse AS 2• from servers in AS 8, 11, 4, 6 to prefix 1.2.3.0/24 • If ALL paths to 1.2.3.0/24 includes AS 2

• from anywhere to 1.2.3.0/24• from 1.2.3.0/24 to anywhere

6 2 5 9 5

2 54

6

118

Page 63: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Path reduction

• Skip repeated traces of the same path• Same destination, same ingress point• Same ingress point, same egress point

Page 64: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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effectiveness of selected measurements

• Brute-force (all servers to all BGP prefix)• 150 million traceroutes required

• Direct probing• 15 million traceroutes required

• Direct probing + path reduction• 300 thousand traceroutes required

Page 65: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Alias resolution

• Alias: traceroute reports the IP address of the interface on the router (not the router!)

• The router might have multiple interfaces• Router’s interfaces may be numbered from

entirely different IP prefixes

• Need to know interface 1 and 2 are on the same router

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Alias probe

• If you send an UDP packet to interface A of a router and address to a non-existing port

• By default, the router will return a ICMP “port unreachable” response back to you

• The source address of ICMP packet will be the outgoing interface for the unicast route to you (interface B)

• if we probe interface X and Y and the resulting ICMP packets have the same source address Z, then we know X and Y are on the same router

Page 67: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Other tricks for resolving alias

1. Compare TTL2. Compare IP identifier (ID)

• Packets sent consecutively will have consecutive IP identifier

• Send probe packets to two potential aliases

• Send another packet to the address that responded first

• Aliases: if x < y < z, and z – x is small

Page 68: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Identify router location

• Utilize DNS names• ISP typically use certain naming

convention to name their routers• s1-bb11-nyc-3-0.sprintlink.net

• A Sprint backbone router (bb11) in New York city (nyc)

• p4-0-0-0.r01.miamfl01.us.bb.verio.net• A Verio backbone router (bb) in Miami, Florida

• s1-neighborname.sprintlink.net• A neighboring router of Sprint

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A typical POP structure• POP (Point Of Presence)

• Consist of a set of backbone and access routers• Backbone routers

• connect to other ISPs• typically fully connected within the POP

• Access routers• Connect to customers

• Connect to routers from the neighboring domains• Connect to two backbone routers for redundancy

POP

Page 70: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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ISP peering structure

• Using BGP table• AS level: whether two ASes peer with

each other

• Using Rocketfuel• Router level: where and how many

places these two ASes exchange traffic

• Skewed distribution• ISP typically peer in a lot of places with

a small number of other ISPs, and peer in only a few places with the most of other ISPs

Page 71: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Tool for measuring performance

• Throughput • iperf

• Bottleneck link Bandwidth• Pathchar• Packet Pair (Bprobe/Nettimer)

• Latency• Ping

• One second resolution• Hping3 can provide a higher resolution

• traceroute

• Loss• tcpdump

Page 72: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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iperf

Need to setup a client and a server Iperf -s | -c <hostname>

Page 73: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Bottleneck Link Bandwidth Estimation

• RTT variation• Dispersion of packet pairs/trains

Page 74: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RTT variation

s: data packet sizeste: ICMP packet sizebi: available bandwidthc: light speedfi: process packet

Page 75: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Pathchar

Utilize RTT variation• increase the packet size and repeat

(1) again• Estimate the link bandwidth by solving

the linear equations obtained from (1)(2)

• Repeat (1)-(3) for each link on the path• Find the minimum of (4)

Page 76: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Packet Pair (ideal)

•send a sequence of TCP probe packets•packets are queued before entering the bottleneck•a gap Pr=Pb is created by the bottleneck link•bottleneck link bandwidth = packet size / As

Page 77: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Life is not perfect• Lots of noise will affect the estimated

bandwidth!• Effect of cross traffic

• Packets are not queued before the bottleneck (case B)• Packets are queued again after the bottleneck (case C)

• Packets arrive out-of-order• Packets traverse different path

• Bottleneck changes over the course of connection• Router does not use a FIFO queue• Clock resolution2 1 2 1 2 1

2 1 2 1

2 1 2 1

2 1

2 1 2 1

A)

B)

C)

Page 78: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Filter the noise

• Assumption: correct estimate will appear more frequent than incorrect ones• Choose the one has higher density

• histogram (bprobe)• kernel density estimator (nettimer)

BW

Page 79: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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bprobe

Page 80: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Tool for measuring multicast

• Mtrace (IGMP)• mHealth (RTCP + Mtrace)• Mlisten (RTP/RTCP)• RTPmon/RTPtools• Mantra

Page 81: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Mtrace

• Multicast version of traceroute• Show the route from a receiver to the source• Traceroute

• Based on increasing ICMP TTL • Does not work for multicast

• ICMP TIME_EXCEED is typically disabled by multicast router

• Use IGMP (Internet Group Management Protocol)• Multicast router keeps the state of incoming/outgoing

interfaces of (S,G)• Reverse path lookup

• Start at the receiver and trace back toward the source

• Allow 3rd-party mtrace

Page 82: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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IGMP

Page 83: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Reverse Path Lookup

• Multicast IGMP Query packet on ALL-ROUTERS multicast address (224.0.0.2)

• The last hop router of the receiver begins a mtrace after receiving the Query packet

• The last hop router appends its info and change the packet type from Query to Request

• The last hop router forward the packet via unicast to the previous router, the incoming interface of (S,G)

• Same process is repeated until the source is reached• The router that connects to the source appends its info

and change packet type from Request to Response• Response packet is then sent to the mtrace initiator

Page 84: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RTP/RTCP

• RTP (Real Time Protocol)• TCP does not work for real time multicast

• ACK implosion and timing requirements• Application Layer Framing (ALF): between Transport and Application

• Commonly used in Mbone and streaming tools• Payload type ID, sequence numbering, timestamping• Consist of a data channel and a control channel (RTCP)

• RTCP• A control protocol of RTP• Function

• Deliver quality• Canonical name: synchronize data from multiple tools (audio/video)• Estimate group size• Distribution of group membership info

• Packet format• Sender report• Receiver report• Source description

• Canonical name• BYE

Page 85: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Mhealth

• A graphical multicast monitor tool• Collect data of a MBone session

• listen RTCP traffic to obtain group information and deliver quality

• Use Mtrace to trace the hops from each receiver to the source

Page 86: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Mlisten

• A tool for collecting info when members join and leave a multicast group

• Continuously monitor well-known multicast address used to advertise Mbone session

• For each session, Mlisten join the audio and video groups and collect control and data packets

• For each packet received, Mlisten record • Sender• Session name• Time received

• At periodic interval, Mlisten identify any session or group members who has no activity for a threshold of period (session: 2hr, member: 2 min) and record them

Page 87: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RTPMon

• A tool that display the statistics of a RTP session by passively monitoring the RTCP traffic

• Startup time• Sender• Receivers• Traffic statistics for each

(sender,receiver) pair• Data sent• Loss• jitter

• Route from the sender to a receiver (via Mtrace)

Page 88: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RTPtools

• a number of applications that can be used for processing RTP data

• rtpsend• generate RTP packets from a text file,

generated by hand or rtpdump

• rtpdump• capture and print RTP packets, generating

output files suitable for rtpplay and rtpsend

• rtpplay• play back RTP sessions recorded by

rtpdump

Page 89: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Mantra..

• A tool that collect multicast from multiple multicast-enabled routers• FIXW: the largest multicast exchange point

in west coast of US• STARTAP: a core router between Interenet2

and commodity Internet• DANTE: an exchange point between US and

European research backbone• ORIX• Router View

Page 90: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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..Mantra

• Data collection• MBGP (Multicast Border Gateway Protocol)

• A router exchange protocol that propagate topology information between domains

• DVMRP (Distance Vector Multicast Routing Protocol)

• Within the same domain

• MSDP (Multicast Source Discovery Protocol)• A protocol that propagates info about active

sources

• Router forwarding tables

Page 91: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Tools for measuring wireless

• Prismdump (or newer version of tcpdump)• 802.11

• Ethereal (tcpdump with a GUI)• tethreal

• netstumbler• wireless extension• Snort-wireless

• A wireless intrusion detection system

Page 92: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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netstumbler

• A tool for detecting 802.11 WLAN• Usage

• Verify if the WLAN is setup correctly• Detect other interfering WLANs in your area• Help aim directional antenna for long-haul

WAN link• WarDriving

NetStumbler.exe

Page 93: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Wireless extension

• API that allows a driver to access to the configuration and statistics of WLAN

• Components• User interface and tool• Driver interface

Page 94: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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User interface and tool

• cat /proc/net/wireless

• Iwconfig

• Iwspy• For mobile IP test• Allow driver to add new addresses

Page 95: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Driver interface

• Defined in /usr/include/linux/wireless.h• Example

• get_wireless_stat• ioctl calls: SIOCSIWFREQ

Page 96: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Measuring mobility

• GPS• Association/disassociation patterns from

base stations/access points• Tools: SNMP, Syslog

• Wireless signal strength • infer user location based on analysis of

signal strength • triangulating

Page 97: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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10

triangulating

10

5

1

10

10

5

1

A B

(A:10, B:1) is a different location from (A:1, B:5)

Page 98: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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What is War Driving? One popular wireless measurement activity Record the activities of wireless LANs from place to place

What do you need for War driving a device capable of receiving an 802.11b signal (notebook w/ wireless

card) a device capable of moving around (some transportation) A software that can log data (netstumbler/ethereal/GPS)

Then you just sit back and relax You move these devices from place to place Over time, you build up a database comprised of the network name,

signal strength, location, and ip/namespace in use.

Page 99: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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What is Wireless LAN?

It is a LAN Extension of Wired LAN Use High Frequency Radio Wave (RF) Speed : 2Mbps to 54Mbps Distance 100 feet to 15 miles

Page 100: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Different version of 802.11

802.11 IEEE family of specifications for WLANs 2.4GHz 2Mbps

802.11a 5GHz, 54Mbps

802.11b Often called Wi-Fi, 2.4GHz, 11Mbps

802.11e QoS & Multimedia support to 802.11b & 802.11a

802.11g 2.4GHz, 54Mbps

802.11i An alternative of WEP

802.11n Antenna diversity

Page 101: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Access points

Access Point (AP) A device that serves as a communications "hub" for

wireless clients and provides a connection to a wired LAN

Beacon Message transmitted at regular intervals by the Aps

(100ms by default for many vendors) Used to maintain and optimize communications to

automatically connect to the AP

Page 102: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Ad-hoc mode

Ad Hoc Mode Wireless client-to-client communication, the opposite is Infrastructure

Mode

Page 103: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Infrastructure mode

Infrastructure Mode A client setting providing connectivity to APs As oppose to AdHoc Mode

AP

Page 104: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Basic service set

SSID or BSSID Basic Service Set Identifier

BSSID or SSID(Basic Service Set Identifier)

beacon

beacon

beacon

BSSAn AP forms an association with one or more wireless clients is referred to as a Basic Service Set

Page 105: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Extended service set

ESSID Extended Service Set Identifier

ESSID (Extended Service Set Identifier)

ESSIn order to increase the range and coverage of the wireless network, one needs to add more strategically placed APs to the environment to increase density. This is referred to as an Extended Service Set

Page 106: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Non-overlapping channels

Page 107: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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DSSS Channel

1 2 3 4 5 6 7 8 9 10 11

2.40

0

2.41

2

2.43

7

2.46

2

2.47

4

Frequency (GHz)

Channel 7

Channel 9

Channel 1 Channel 6 Channel 11

Channel 2

Channel 10Channel 5

Channel 4

Channel 3 Channel 8

Page 108: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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The RFMON mode

Like promiscuous mode in wired Listen(Receive) only Also known as “Monitor Mode” You can capture raw 802.11 (such MAC-layer

packets in this mod)

Many drivers now support RFMOD mode Prism2 madwifi

Page 109: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Snort-wireless

Extended from Snort (an IDS for Internet) for wireless

allow one to specify custom rules for detecting specific 802.11 frames, rogue APs, AdHoc networks, and Netstumbler-like behaviour in the vicinity of the Snort-Wireless sensor

Page 110: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Snort format

<action> wifi <mac> <direction> <mac> (<rule options>)

Use source and destination MAC address instead of IP address

Page 111: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<action>

tells Snort what to do when it finds a packet that matches the rule criteria

alert: generate an alert and then log the packet

Log: log the packet pass: ignore the packet Activate: alert and then turn on another

dynamic rule Dynamic: remain idle until activated by

an activate rule , then act as a log rule

Page 112: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<mac>

Format Single MAC Address

00:DE:AD:BE:EF:00 MAC Address List

[00:DE:AD:BE:EF:00, 00:DE:AD:C0:DE:00, ....]

Page 113: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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<direction>

-> From source to destination

<> Both directions

Page 114: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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What info you can get from wireless packets

timestamp Signal strength SSID Sender/receiver Retransmission Mobility

(association/disassociation)

Page 115: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Received Signal Strength Indication

In arbitrary units (different vendors define it in different ways)

RSSI is typically used to determine when the amount of radio energy in the channel is below a certain threshold at which point the network card is clear to send (CTS).

Page 116: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Noise floor

Typically assumed as a constant the noise power N = kTB

where k is Boltzmann's constant, T is the temperature in Kelvin, B is the system bandwidth

For a 20Mhz OFDM channel we have -174 + 10log10(20x106), or -101.7dBm thermal noise at the antenna. After including an additional 5dBm noise from the amplifier chain, we have -96dBm

RSSI 10: weak, 20: ok, 40: good RSSI changes with time due to

interference, channel fading etc.

Page 117: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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What is signal strength?

Four common units for measuring RF signal strength

mW dBm RSSI percentage

Page 118: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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mW <-> dBm

dBm = log10(mW) x 10

Example 100mW = log10(100) x 10 = 20 dBm

50mW = log10(50) x 10 = 16.9 dBm

1mW = log10(1) x 10 = 0 dBm

0.5mW = log10(0.5) x 10 = -3.01 dBm

It’s cumbersome to talk about –96 dBm as 0.0000000002511 mW

Page 119: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RSSI 802.11 standard

A mechanism by which RF energy is measured on the circuitry of a wireless NIC

An allowable range from 0 to 255 In reality

No vendor actually measures 256 different signal strength level

Use RSSI_Max Cisco: 100 Symbol: 30 Atheros: 60

Page 120: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Use RSSI Chipset uses RSSI to decide if the channel

clear Clear channel threshold Roaming threshold

RSSI_MAX is different from vendor to vendor

Clear channel/roaming threshold is different from vendor to vendor

Page 121: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Granularity of RSSI RSSI are discrete integer numbers

Can not represent all possible energy levels (mW or dBm)

Many vendors map RSSI to dBm because of the logarithmic nature of dBm

5mW

dBm

Page 122: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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RSSI <-> dBm

Most vendors use a table to map RSSI to dBm

Atheros dBm = RSSI – 95

Cisco RSSI dBM

0 -113

1 -112

… …

100 -10

Page 123: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Receive sensitivity The minimum level of RF energy for the

receiver to extract bit-stream A NIC spec measured in dBm Signal and noise are not distinguishable

below receive sensitivity Very close to RSSI=0

Impossible to measure RSSI=0 Can’t decode a ‘packet’

The higher data rate, the high receive sensitivity required

Page 124: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Percentage metrics

RSSI = RSSI_MAX * percentage E.g. for Atheros card, 50% = 60 * 50% = RSSI 30

Good for site survey

Page 125: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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What is signal quality?

In 802.11b standard PN code correlation strength In the context of DSSS modulation

Symbol Data bits + PN code (called spreading) E.g. At 1Mbps/2Mbps

1 single bit of data XOR’ed 11-bit-long PN code (Barker’s sequence, 101100111000)

Page 126: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Symbol correlation

symbol for ‘1’ 101100111000received symbol 101100111001

symbol for ‘0’ 010011000111received symbol 101100111001

the received symbol is ‘closer’ to 1 than to 0

signal quality == percentage of ‘correct’ bits

== reflect the corruption between AP and client but not necessarily equal to SNR

Page 127: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Question?

Page 128: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Things to know when making measurements

• It’s not just plugging in a box and then start sniffing traffic

• Administrative issue• Privacy and security

• Technical issue• Error and imperfections• Large volume of data• Reproducible results• Making data publicly available

Page 129: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Error and imperfections

• Precision• Limited by the measurement devices• Clock precision• How much details to record

• Accuracy• Packet drops during recording or filtering• Duplicate or re-ordering due to packet filter• Clocks

• Un-synchronized clocks• Buffered packets at NIC

• Effect of middle-box• Trace edge-effect

• Representative data

Page 130: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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precision

Consider a tcpdump record

1092727442.276251 IP 192.168.0.120:22 > 192.168.0.137:9320

How precise is it?

Answer: at most 1 us, but perhaps much less

Page 131: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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How precise is the packet captured by tcpdump?

• Snapshot length limits the total data• filtering

Page 132: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Maintain meta data

• E.g. when, where, how the traces are recorded

• Giving the measurements a context• Meta data is important when the

measurement is used by other people later for different purposes

• Existing tools are weak here• Can be your potential project topic

Page 133: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Accuracy

• An even harder problem than precision• Examples

• Clock• arbitrarily off from true time• Jump forward or backward• Fail to move• Run arbitrarily fast or slow

• Packet filter• Drop packets• Fail to report drops• Report drops that did not occur• Reorder packets• Duplicate packets• Record the wrong packets

Page 134: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Not measuring what you think you’re measuring

• Examples• Measuring TCP packet losses by

counting retransmission• Packets can be replicated by the network

• Counting TCP connection size by counting the difference between SYN and FIN• What if the remote host was down?

Page 135: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Calibration

• Detect problems of precision/accuracy/misconception

• Goal: Fix these problems post facto• Identify and remove faulty

measurements• Find the outliers

• E.g. what are the biggest and smallest RTT in the measurements?

Page 136: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Techniques to detect inaccuracy

• Examine outliers and spikes• Outliers: unusually low or high values• Spikes: values that appear a lot• E.g. extremely small RTT or extremely large

connection

• Consistency check• Compare against normal protocol/traffic behavior

• Comparing multiple measurements• From different time• From different places

• Use synthetic data to verify the correctness of software

Page 137: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Self-consistency check

• Check against the expected protocol behavior

• E.g. if a TCP receiver acknowledged data never sent, something must be wrong• Filter drops the data• Packet took another route• Data was sent before you measured• The TCP receiver is broken

Page 138: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Compare multiple measurements

• Compare packets at both ends• Compare packet headers with payload• Compare measurements collected at

different times

Page 139: 2015/6/161 Kun-chan Lan Department of Computer Science and Information Engineering klan@csie.ncku.edu.tw Network Measurements, Modeling and Simulations

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Large volume of data

• Disk space• Number of files• Process time • Memory usage• Maximum file size

• 2G for older version of Linux• Software limitation

• The number of data points can be input• Statistical limitation

• Large datasets do not have statistically exact description

• Tip: early analysis with a smaller dataset

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Re-producible analysis

A typical scenario• you collected the measurements,

did the analysis and submitted the results to a conference

• Months later, you got a feedback from the reviewer that asks you to re-do the measurements with a tweak

• What would you do?1. Introduce the tweak, re-crunch the numbers, update

the table and then call it done2. Or, you first re-run your scripts to understand how

you got those numbers in the first place

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But…

• For a good-sized measurement study, you often can not re-produce the exact earlier numbers…

• You’ve lost the previous mental context of fudge factors, glitch removals, script inconsistency• Ad hoc notes• Removal of outliers• Random fixes• Different versions of analysis scripts• Rounding the numbers

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Strategies

• One single master that builds all results from raw data

• Keep intermediary form of the data• Maintain a notebook

• What have been done and what happened

• Use version control• Need a way to visualize the changes

after the re-run• Another potential project topic

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Make data publicly available

• Comment details about how measurements were taken• Where and when• Link properties (speed, utilization, loss, etc.)

• Include analysis scripts that were used• Anonymization

• Security, privacy, business sensitivity

• Data-reduction request

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Measurement infrastructure

• Administrative issues• It’s not easy to get fresh data by yourself

• Places where you can get some existing data• NLANR• ITA• MAWI• NIMI• CAIDA• Internet 2

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NLANR

• Passive Measurement Analysis (PMA)

• Active Measurement Project (AMP)

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PMA

• Collect passive IP header trace ranging from OC3 to OC192 links

• Each monitor captures a unique portion of overall network data

• Capture 8 samples per day• 2 minutes per sample• 3.2G data per day• A number of OC48 long, continuous

traces• From 1 hour to 45 days

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AMP

• 150 sites in US and some in other countries• Site to site measurements• Two meshes

• HPC mesh (all in US, ~140 sites)• International mesh

• Data measured• round trip time (RTT)• packet loss • topology• throughput

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Internet Traffic Archive (ITA)

• Founded by Vern Paxson since 1996• Mainly are Web traces (and some wide-area TCP

and traceroute traces)• Most traces are in the format of tcpdump or http

log• Trace duration ranges from 2 hours to 6 months• Related software

• tcpdpriv• Remove private information of tcpdump

• tcp-reduce• a collection of shell scripts for reducing a tcpdump trace file

to a summary of the corresponding TCP connections. • tracelook

• a program for graphically viewing tcpdump traces.

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MAWI (WIDE project)

• Japan research efforts• Traffic from several trans-Pacific T1 lines,

an US-Japan OC-3 line and 6Bone• Daily traces• 2 million packets per hour for trans-pacific

lines• 6Bone traffic is still light (mainly BGP and

ICMPv6)

• Traces are in tcpdump format and anonymized with tcpdpriv

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NIMI (National Internet Measurement Infrastructure )

• A set of measurement servers (probes) running on a set of hosts

• Function• Receive and authenticate request• Execute the request at the appropriate time• Send the result back the requester

• Daemon• nimid: communicate with outside world• scheduled: scheduling, execute measurements and packaging results

• CPOC (Configuration Point Of Contact)• Configure and administer a set of NIMI probes in the same

administration domain• Measurement client (MC)

• A tool that allow end-user to send measurement request to NIMI probe

• Data Analysis Client (DAC)• Where the measurement results are returned• The address of DAC is included in the request sent by MC

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CAIDA (Cooperative Association for Internet Data Analysis )

• Affiliated with UCSD• Provide tools, data and analysis for research

community• Data sources

• Exchange points: e.g. San Diego Network Access Point (SD-NAP)

• Data from FIX-West • routing data from University of Oregon's Route Views

project (www.antc.uoregon.edu/route-views) and Merit's IPMA (www.merit.edu/ipma/)

• active measurement from skitter

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Internet 2

• Goal• A large-scale edge network for research community• Enable revolutionary application• Transfer new application/service to commercial Internet

• Consist of 207 universities connected by 3 networks: Abilene, Quilt, ARENA

• The participants collaborate with each other on studying and identifying, developing, and testing advanced network services, applications and technologies

• Focus on end-to-end performance measurements• Active: routing, delay, loss• Passive: SNMP, Netflow

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Wireless traces

Crawdad (Dartmouth)Mobilib (UFL)Reality Mining (MIT)DiselNet (UMass)