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BITS PilaniPilani Campus

Advanced Computer

Networks (CS ZG525)Virendra S Shekhawat

Department of Computer Science and Information Systems

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BITS PilaniPilani Campus

First Semester 2015-2016Lecture-15 [11th Oct 2015]

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BITS Pilani, Pilani CampusFirst Sem 2015-16

Agenda

• Routing in DTNs: Taxonomy and Design [CH-27]

– Reading

• Routing in Delay Tolerant Networks by Sushant Jain, 2004

• conferences.sigcomm.org/sigcomm/2004/papers/p299-jain111111.pdf

• Replication Based Routing Protocols for DTNs [CH-28]

– Reading

• Routing in Delay/Disruption Tolerant Networks: A taxonomy, Survey andChallenges by Yue Cao, 2012

• ukchinab4g.ac.uk/sites/default/files/5_Achievements/journal/routing_de

lay.pdf

3Advanced Computer Networks CS ZG525

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Routing Taxonomy

Advanced Computer Networks CS ZG525

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DTN Routing Taxonomy

• Random Routing – Epidemic

– Two Hop Routing

–

Spray and Wait• Prediction based Routing

– Based on past encounter statistics

• ProPhet Routing, MaxProp, RAPID

• Coding based Routing

– Source Coding

– Network Coding


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Opportunistic Routing

• Graph is disconnected and/or time-varying

• Set of contacts C: unknown

•

Set of nodes V: often unknown too• Basic Principle

– When two nodes meet one another, they must

decide whether to forward a message, and/or to

carry it further

– Store-and-forward Store-carry-and forward


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7/36BITS Pilani, Pilani CampusFirst Sem 2015-16

Why different routing

protocols…?

• Traditional routing protocols do not work well inenvironments prone to frequent and long liveddisruptions

• Basic assumptions used in these are

– Almost always connected network

– End to end path is exists between two end points

• How DTN environment is different

– Path may never be available between end points – Store-carry-forward A set of independent

opportunistic forwarding decisions will attempt toeventually deliver messages to destinations


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Basic Primitives of

Opportunistic Routing

• Message Replication

– Greedy Replication

– Controlled Replication

–Utility based Replication

• Message Forwarding

– Based on absolute utility criterion

– Based on relative utility criterion

• Message Coding

– Source Coding

– Network Coding


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Routing Objectives or Metrics

• Delivery Ratio: It is given by the ratio between thenumber of delivered messages and the number of

generated messages.

• Overhead Ratio: It is given by the ratio between the

number of message transmissions required for delivery

and the total number of messages delivered.

• Delivery Delay: It is given by the time duration between

the messages generation and their delivery.


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Message Replication[1]

• Message Replication- A relay X carrying a copy of msg m can decide to spawn a new copy of m and forward it to

the newly encountered node, Y

1. If the new neighbor does not have a copy of this msg

2. If node have buffer space available

3. If the “context” of the two nodes allows

• Greedy Replication- A node decides to forward a msg m

based on 1 and 2 only• e.g. Epidemic routing

• + Minimum average message delay

• - Consuming maximum network resources


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Epidemic Routing[1]

•

Give a message copy to every node encountered – essentially: flooding in a disconnected context

A

C

B

D

D

EF

D

D

D

D


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Epidemic Routing[2]

• How many transmissions (per message)?

– At least N

– All nodes receive the message

• What is the delay?

– Minimum among all possible routing schemes

– If NO resource constraints (bandwidth, buffer space)


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Message Replication [2]

• Controlled Replication- A node decides to forward amsg m based on all three conditions (i.e. 1,2 and 3shown in slide no. 8)

– “Context” keeps track on the number of copies to be created

– Copy-limited replication: each msg copy generated isaccompanied by a number of forwarding tokens (e.g. spray &wait)

– Time-limited replication: each new message generated (say attime Ts) may be further replicated to nodes (other than thedestination) only for an amount of time Trep

– Probability-limited replication: a node decides to forward acopy of a msg to any node it encounters with a specificprobability, P


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Reducing the Overhead of

Epidemic

Randomized Flooding (“Gossiping”)

• Give message to neighbor with a probability p ≤ 1

• p = 1) epidemic

•

p = 0) direct transmission+ Fewer transmissions

- For long duration, transmissions = O(N)

Other flooding-based variants:

• Each node forward up to Kmax times

• Self-limiting epidemic (SLEF)


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2-hop Scheme: Version 1

• When message created at source

– Forward to destination if within range

– Forward to a neighbor relay if destination not in range

• Relay: forward only to destination

• Transmissions per message

– At most 2

• Delay?

– Finite if each node meets every other node…eventually


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2-hop Scheme: Version 2

•

Source gives a copy to any relay encountered• Relays can only give copy to destination

Src

C

B

Dst

D

EF

D

D

D

Relay C cannot FWD to B

Relay C can FWD to Dst

Avg Transmissions per msg = (N-1)/2


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Spray and Wait (Binary

Spraying)

•Use forwarding tokens; SRC starts with L tokens

• When L = 1, can only forward to DST

Src

C

B

Dst

D

EF

D

D

D

DL = 4

L = 2

L = 2

L = 1

L = 1

L = 1L = 1


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Spray & Wait: Analysis

• L (e.g. L = 10) copies might be – Too little if number of nodes M is large (e.g. 10000) =>

almost 2-hop.v1

– Too many if number of nodes M small (e.g. 20) => almost

epidemic

• Analytical equation for S&W delay as a function of L/M – Choose desired L (tradeoff delay vs. transmissions)

• What if number of nodes is unknown? – Estimate number of nodes online


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Message Replication[3]

• Utility based replication- the forwarding decisiondepends on the “context” of the current custodian and

that of the candidate relay node

– Uncontrolled utility based replication: e.g. A node forwards a

new copy to a new neighbor only if the neighbor has a high

enough probability of the future encounter with the

destination (used to improve epidemic routing)

– Controlled utility based replication: e.g. Number of replicas of

a message delivered to a relay node can be decided based

upon the ratio of encounter value that the relay advertises


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Utility Functions

• Destination Dependent – Age of last encounter

– History of past encounters

– Pattern of location visited

– Social networks – Traditional Routing Table Entry

• Destination Independent

– Amount of mobility

– Node resources

– Cooperative behavior

– Trustworthiness


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Prophet Routing

• Like Epidemic routing, but maintains a probability ofdelivery for each node pair p(i,D)

• Node i copies message to j only if p(j,D) > p(i,D)

• Algorithm:

i D

p(i,D) = 1

Contact with Dest D

i

D

p(i,D) * γt, (γ < 1)

No Contact with Dest D

Per Hop Probability

Contact with j

i

D

p(i,D) = f(p(i,D),p(j,D))

j

Path Probability


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Past Encounters: Encounter

Frequency

• Last encounter not necessarily representative• Consider:

– Node A meets D every 10min, last saw D before 5min

– Node B meets D every 1h, last saw D before 1min

• Use frequency: p(i,D) = # encounters(i,D) / Timewindow• Consider

– Node A meets D every 10min, for 1sec each time

– Node B meets D every 20min, for 2min each time

• Use total contact duration: p(i,D) = Timeconnected / Timewindow•

Consider – Node A meets D every 10 min

– Node B meets D in bursts: average = 10min, average during burst =1min, last meeting before 30sec

Prediction Becomes Complex!Advanced Computer Networks CS ZG525

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Message Forwarding

• By message forwarding, a node relinquishes its copyof msg and ceases to be one of its custodians

– Forwarding can be done based on a utility function or in

a probabilistic manner – If a node i carrying a msg copy for a destination d

encounters a node j with no copy of the msg then

• U j(d) >Uth (Absolute utility criterion)

•U j(d) > Ui(d) (Relative utility criterion)

• e.g. If utility function is lower than a certain threshold, nodes

with highest mobility to move farthest in the network are

chosen as relays


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Message Coding

• Message can be coded at the source (aka source coding)or in the network (aka network coding)

•

Source coding- Increases delivery reliability andreducing worst case delay

• Network Coding-A way to increase the capacity of the

wireless networks


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Reducing the overhead of

epidemic: Network Coding[1]

• Coding may combine one or more packets

x1

x2

x3

Outgoing links

Incoming links x1

x2

x3

Store-and-forward

x1

x2

x3


R d i th h d f

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Reducing the overhead of

epidemic: Network Coding[2]

• Coding may combine one or more packets

Outgoing links

Incoming links x1

x2

x3

Network Coding

f(x1,x2,x3)


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BITS Pilani, Pilani CampusFirst Sem 2015-16 Advanced Computer Networks CS ZG52527

Coding Packets: A simple

example

• XOR: The simplest combination:2 1 2 1

x x ) x ,f(x

1 0 1 1msg x1:

0 1 1 0msg x2:

1 1 0 1f(x1,x2):

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Coding Packets: A simple

example

• XOR: The simplest combination:2 1 2 1

x x ) x ,f(x

1 0 1 1msg x1:

0 1 1 0msg x2:

1 1 0 1f(x1,x2):

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De-coding Packets: A simple

example

• Assume node that send x1 receives the coded packet f(x1,x2)

1 0 1 1msg x1:

0 1 1 0msg x2:

1 1 0 1f(x1,x2):

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Network Coding for Wireless

• Broadcast nature of medium: natural ground

for network coding

A BC

B x1 A x2B x1

A x2 B x1A x2

No coding: delay = 4 Advanced Computer Networks CS ZG525 30

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Network Coding for Wireless

• Broadcast nature of medium: natural ground

for network coding

A BC

B x1 A x2B x1

A x2

Coding: delay = 3

21 xx

21 xx 21 xx


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MAXPROP (1/2)

• Motivated by pedestrian mobility and city vehicles (busses)• Addressed resources issues considering vehicles

– Bulky equipment

– energy

• Maintains ordered destination based queues – Ordered by the estimated likelihood of a future transitive path to that

destination

• Assumes

–

Unlimited buffer for own messages per node – Fixed size buffer for relaying messages

– No topology knowledge/control


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MAXPROP (2/2)

• Communication steps (flooding-based!):

1. Neighbor Discovery

(no knowledge of when the next opportunity to communicate will be)

2. Data Transfer

a) Transfer packets destined for neighbor peer

b) Transfer routing information

c) Acknowledge any delivered data

d) Prioritize “young” relayed packets (with lower hop counts)

e) Send un-transmitted packets by estimated delivery likelihood

f) Ensure only new packets are sent

3. Storage Management

(expunge packets to accommodate the relay buffers)


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RAPID Protocol

• RAPID: Resource Allocation Protocol for Intentional DTNRouting

• Goal: Intentionally affect a single routing metric (e.g.

average delay, missed deadlines, and maximum delay)

• Method: Utility function (Ui) based replication(Ui is

defined as expected contribution of packet i to this

metric)

• Average Delay Optimization: Ui = - D(i) – The protocol replicates the packet that results in the greatest

decrease in delay among all packets in its buffer


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Challenges and Open Issues

• Need for a framework to compare various routingapproaches

• Congestion control in DTNs

•

Prediction based approaches still needs to beinvestigated more

• Multicasting and any-casting in DTNs is still untouched

• Capturing mobility characteristics and topology control

is the biggest challenges so far


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Thank You !

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