Delay Tolerant Networking - Universitetet i · PDF file1 Delay Tolerant Networking Thomas Plagemann Distributed Multimedia Systems Group Department of Informatics University of Oslo

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Delay Tolerant Networking

Thomas Plagemann Distributed Multimedia Systems Group

Department of Informatics University of Oslo

Outline

•  Background, motivation, overview •  Epidemic routing •  Message ferrying •  Mobility/density space •  Acknowledgement: Many transparencies

are from Mustafar Ammar’s keynote talk at Co-Next 2005

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Traditional Wired Networks

•  separation between endsystems and routers •  routers responsible for finding stable path

router

endsystem (source) endsystem

(destination)

[M. Ammar, Co-Next 2005]

“Traditional” Mobile Ad-hoc Wireless Networks (MANET)

•  no separation between endsystems and routers •  nodes responsible for finding stable path

node (destination)

node = endsystem + router

node (source)


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“Traditional” Mobile Ad-hoc Wireless Networks (MANET)

•  nodes may move •  routing layer responsible for reconstructing (repairing)

stable paths when movement occurs

node (destination)

node (source)


The “Traditional” MANET Wireless Paradigm

•  The Network is “Connected” – There exists a (possibly multi-hop) path from

any source to any destination – The path exists for a long-enough period of

time to allow meaningful communication –  If the path is disrupted it can be repaired in

short order –  “Looks like the Internet” above the network

layer


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The Rise of Sparse Disconnected Networks


Sparse Wireless Networks

•  Disconnected – By Necessity – By Design (e.g. for power considerations)

•  Mobile – With enough mobility to allow for some

connectivity over time – Data paths may not exist at any one point in

time but do exist over time


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Mobility-Assisted Data Delivery: A New Communication Paradigm

•  Mobility used for connectivity •  New Forwarding Paradigm Store Carry for a while forward •  Special nodes: Transport entities that are not

sources or destinations


Data Applications

•  Nicely suitable for Message-Switching •  Delay tolerance … but can work at

multiple time scale (a.k.a. Delay Tolerant Networks )


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Some Delay-Tolerant Systems

•  ZebraNet and SWIM •  Data MULE and Smart-Tags •  Vehicle-to-Vehicle Communication •  DakNet •  Epidemic Routing •  Message Ferrying


SWIM


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Vehicles on Highways Networks

Source Destination



Source Destination


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Source Destination


DakNet (Pentland, Fletcher, and Hasson)


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Epidemic Routing

•  Vahdat and Becker •  Utilize physical motion of devices to transport

data •  Store-carry-forward paradigm

–  Nodes buffer and carry data when disconnected –  Nodes exchange data when met –  data is replicated throughout the network

•  Robust to disconnections •  Scalability and resource usage problems


Epidemic Routing – The Idea


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11


message is delivered…


Epidemic Routing – Basic Elements

•  Each node contains – Message buffer – Hash table – Summary vector – List of last seen nodes

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Epidemic Routing – The Protocol

[Vahdat & Becker, TechReport 200]

Epidemic Routing – Multiple Hops

•  Each message contains: – Unique message ID – Hop count – Ack request (optional)

•  Tradeoff buffer size vs. message delivery

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Epidemic Routing – Evaluation •  Implementation in ns-2

–  50 mobile nodes –  Area 1500m x 300m –  Random waypoint –  Speed 0 – 20 m/s (uniformly distributed) –  Message size 1 KB –  45 message sources/sinks (each sends one message to the

others) –  Each second 1 message

IEEE 802.11 MAC protocol Model of radio propagation

Model of node mobility

IMEP IMEP IMEP IMEP IMEP

ERA ERA ERA ERA ERA

Internet MANET Encapsulation Protocol

Epidemic Routing Agent

Epidemic Routing – Evaluation


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The Trouble with ER

•  Potentially high-failure rate •  Message duplication consumes nodal

resources •  Some mobility patterns can cause

disconnection •  Can be improved with contact probability

information - Levine et al


Message Ferrying (MF) @ GT

•  Zhao and Ammar •  Exploit non-randomness in device

movement to deliver data – A set of nodes called ferries responsible for

carrying data for all nodes in the network – Store-carry-forward paradigm to

accommodate disconnections •  Ferries act as a moving communication

infrastructure for the network


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Message Ferrying – The Idea

D

MF

M

S

MF

S M

D


MF Variations

•  Ferry Mobility –  Task-oriented, e.g., bus movement –  Messaging-oriented, e.g., robot movement

•  Regular Node Mobility –  Stationary –  Mobile: task-oriented or messaging-oriented

•  Number of ferries and level of coordination •  Level of regular node coordination •  Ferry designation

–  Switching roles as ferry or regular node [M. Ammar, Co-Next 2005]

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MF for Networks with Mobile Nodes

•  Nodes are mobile and limited in resources, e.g., buffer, energy

•  Single ferry is used – Not limited in buffer or energy – Trajectory of the ferry is known to all nodes

•  Data communication in messages – Application layer data unit – Message timeout


Four Approaches •  Non-Proactive ( = Messaging-Specific) mobility

–  Ferrying without Epidemic Routing –  Ferrying with Epidemic Routing

•  Proactive Routing Schemes –  Node-Initiated MF(NIMF)

•  Nodes move to meet ferry –  Ferry-Initiated MF (FIMF)

•  Ferry moves to meet nodes


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Node-Initiated Message Ferrying

Meet the

ferry? OK

Working

If no, keep working



Go to Ferry


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Send/Recv

Go to Work



Go to Work


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Intentional

Not planned

Mode Transition

WORKING GO TO FERRY

GO TO WORK SEND/RECEIVE

detour: whether the node is detouring; mode: which mode the node is in; 1.  WORKING mode

detour = FALSE; IF Trajectory Control indicates time to go to the ferry,

detour = TRUE; mode = GO TO FERRY;

On reception of a Hello message from the ferry: mode = SEND/RECV;

2.  GO TO FERRY mode Calculate a shortest path to meet the ferry; Move toward the ferry; On reception of a Hello message from the ferry:

mode = SEND/RECV; 3.  SEND/RECV mode

Exchange messages with the ferry; On finish of message exchange or the ferry is out of range:

IF detour is TRUE, mode = GO TO WORK; ELSE mode = WORKING;

4.  GO TO WORK mode Move back to node’s location prior to the detour; On return to the prior location:

mode = WORKING; On reception of a Hello message from the ferry: mode = SEND/RECV;

Node Operation in NIMF

[Zhao et al., MobiHoc04]

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Ferry Operations in NIMF

1.  Move according to a ferry route; 2.  Broadcast Hello messages periodically; 3.  On reception of an Echo message from a

node: Exchange messages with the node;

[Zhao et al., MobiHoc04]

Node Trajectory Control

•  Whether node should move to meet the ferry •  Goal: minimize message drops and reduce

proactive movement •  Go to ferry if

–  Work-time percentage > threshold –  and –  Estimated message drop percentage > threshold


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Simulations

•  Ns simulations using 802.11 MAC and default energy model

•  40 nodes in 5km x 5km area •  25 random (source, destination) pairs •  Node mobility

–  random-waypoint with max speed 5m/s •  Message timeout: 8000 sec •  Single ferry with speed 15m/s

– Rectangle ferry route [M. Ammar, Co-Next 2005]

Performance Metrics

•  Message delivery rate •  Message Delay •  Number of delivered messages per unit

energy – Only count transmission energy in regular

nodes


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Message Delivery Rate

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

100 200 300 400 500 600 700 800

Mes

sage

delivery rate

Node buffer s ize (mes s ages )

E pidemic R outingE pidemic R outing (w/ ferry)

NIMFFIMF-‐NNFIMF-‐T A

FIMF

NIMF

F w/ER

ER


Message Delay

0

500

1000

1500

2000

2500

3000

3500

4000

100 200 300 400 500 600 700 800

Mes

sage

delay

(sec

)

Node buffer s ize (mes s ages )

E pidemic R outingE pidemic R outing (w/ ferry)

NIMFFIMF-‐NNFIMF-‐T A

FIMF

F w/ER

ER

NIMF


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Impact of Node Mobility Pattern

Mobility Model Scheme Delivery Rate Delay (sec) Energy efficiency (KB/J) Random

Waypoint NIMF 0.912 3569 300 FIMF 0.931 3691 181

ER(w/ ferry) 0.661 2084 14 ER 0.316 1546 10

Limited Random

Waypoint NIMF 0.699 3896 267 FIMF 0.850 4091 137

ER(w/ ferry) 0.211 2851 11 ER 0.061 2221 6


Where Does MF Fit?

•  Consider the space of wireless mobile networks

•  Two Important Dimensions – Relative Mobility – Density


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Some Terminology •  A Space Path: A multi-hop path where all the

links are active at the same time

•  A Space/Time Path: A multi-hop path that exists over time

•  NOTE: S path is a special case of S/T path •  See http://www.cc.gatech.edu/fac/Mostafa.Ammar/papers/STroute.ps


Example

A Space Paths Network


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Example

A No Path Network


Example

A Space Time Path


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Example

A Hybrid Network


The Mobile Wireless Space

Node Density

“ Relat

ive M

obility

”

High

Low

High

Space Paths

Low

No (Space/Time) Paths

Space/Time Paths

Hybrid Environments


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Mapping Solutions to Space

Node Density

“ Mob

ility

”

High

Low

Low

High

Space Paths

No (Space/Time) Paths

Space/Time Paths

Hybrid Environments

MF is necessary here

Traditional MANET solutions apply here

MF is applicable for the entire space


MAC Layer Support for Delay Tolerant Video Transport in

Disruptive MANETs Morten Lindeberg, Stein Kristiansen, Vera Goebel and omas Plagemann

University of Oslo, Department of Informatics [mglindeb, steikr, goebel, plageman]@i".uio.no

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Background and Motivation

•  Emergency and rescue scenarios •  Video streaming services can improve

communication and operational efforts – E.g., firemen wearing head-mounted cameras

•  Infrastructure destroyed or not existing

•  Solution: Mobile ad hoc networks with possible disruptions

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Target Scenario

CCCCCCCr2Cr1

I5I4

Cr1

I5I4

I3I3

I2

I

I1

I2

I1Sr

Ix - Intermediate node(s)Sr - Source node

Crx- Carrier node(s)CCC - Command Control Center

Location of the accident

500 m

500

m

Command and control center

Distance=1750 m

•  Mimic realistic scenario •  Enforce store-carry-forwarding

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Use existing technology? •  Video encoding:

–  H.264 significantly reduce bandwidth requirements •  Transport:

–  TCP does not work well

•  Network: –  IP + MANET routing: OLSR

•  Wireless: –  IEEE 802.11 ad hoc mode

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Transport: Overlay Solution

•  A delay tolerant overlay – Store-carry-forward paradigm – Dts-Overlay –  Inspired by MOMENTUM [1] – Messages are sent hop-by-hop – Route through carrier nodes when no route exist

•  Problem: packet loss

Dts-Overlay

UDP

IP / OLSR

MAC(IEEE 802.11 a/b)

Route availability

+MAC address/ARP status

Rejectedpackets

+Retransmission

queue status

PHY(IEEE 802.11 a/b)

Dts-Overlay

UDP

IP / OLSR

MAC(IEEE 802.11 a/b)

PHY(IEEE 802.11 a/b)

<OverlayMessage>

Node 1 Node 2

[1] Cabrero, S., Paneda, X.G., Plagemann, T., Goebel, V.: Overlay solution for multimedia data over sparse MANETs. In: International Wireless Communications and Mobile Computing Conference, IWCMC (2009)

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Packet loss •  OLSR routes with broken links

–  In essence, lower layers are not delay tolerant

•  Address Resolution Protocol (ARP) 1.  ARP will loose packets if no nodes reply with

matching MAC address to the broadcasted IP address

•  IEEE MAC 802.11

1.  Packets silently dropped after final retransmission 2.  .. or if queue exceeds limit

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Solution •  ARP Support:

– Avoid packet loss by only forwarding when address is resolved

•  MAC Support (IEEE 802.11b):

– MAC Return: Do not drop packet after final re-transmission, hand it to Dts-Overlay

– Link Adapt: Do not forward if the MAC transmission queue is filling (link is probably down)

– Reduce non-meaningful re-transmissions (MAC re-transmission limit)

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Implementation •  Implemented in ns-3 (network simulator)

•  Workload: –  Foreman CIF resolution (352x288) –  12 second duration on repeat –  H.264 baseline profile –  Target bitrate 256 kb/s

•  Wireless model: –  IEEE 802.11b ad hoc mode –  DSSS modulation –  Friis propagation loss model –  Constant speed propagation delay model

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Evaluation •  Metrics:

1.  Packet reception (Rxv) 2.  Buffered packets (Buf ) 3.  Packet loss (Pl) 4.  Sum of bytes (video) at PHY layer (Txtot)

•  Present average from five different runs 3600 s duration •  Main-Studies (3600 s duration):

–  ER (custom scenario) –  Sparse MANET (1250 m x 1250 m, 20 nodes, random walk) –  Dense MANET (250 m x 250, 20 nodes and additional workload,

random walk)

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Results: Pre-Study

•  Address Resolution

– Affect packet loss substantially! – We achieve lowest packet loss with Dynamic

ARP! –  .. wait for ARP resolution before using a link

Default Static Dynamic Pl 39.3 % 31.7 % 19.5 %

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Configurations

C3 C4 C5 C6 C7 Re-trans. 7 3 3 3 3 MAC Return

No No No Yes Yes

Link Adapt No No Yes No Yes

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Results: ER

0 %

10 %

20 %

30 %

40 %

50 %

60 %

70 %

80 %

90 %

100 %

C3 C4 C5 C6 C7

Pl Buf Rx

Lowering retransmission limit cause packet loss

Deploying Link Adapt does not affect packet

reception much

MAC Return close to eliminates all

packet loss

Link Adapts improves further,

even reduces total transmission ov by

4%

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Results: Sparse MANET Tendencies are the same, high standard deviation (mobility)

Switch to single run

0

20000

40000

60000

80000

100000

120000

140000

160000

0 500 1000 1500 2000 2500 3000 3500

Pack

et co

unt (

#)

Time (s)

SentC3C4C5C6C7

0

100

200

300

400

500

600

700

800

900

0 500 1000 1500 2000 2500 3000 3500

Txt (

MB)

Time (s)

C3C4C5C6C7MAC Return

improves reception

With even less transmissions than default configuration

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Results: Dense MANET

0 20 40 60 80

100 120 140 160

C3 C4 C5 C6 C7

TxTot (MB)

TxTot (MB)

Not much loss really, although some duplicates for MAC Return

Link Adapt has strong effect on transmissions

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Conclusion

•  MAC Support Evaluation: – MAC Return drastically reduce packet loss – Allow us to lowering MAC retransmission limit – Link Adapt lowers overhead of transmissions

that are not meaningful •  Usability is strengthened through

evaluation also in a dense MANET

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Summary

•  Background, motivation, overview •  Epidemic routing •  Message ferrying •  Mobility/density space •  Acknowledgement: Many transparencies

are from Mustafar Ammar’s keynote talk at Co-Next 2005

Documents

Delay Tolerant Networking - Universitetet i · PDF file1 Delay Tolerant Networking Thomas Plagemann Distributed Multimedia Systems Group Department of Informatics University of Oslo