Mobility Increases Mobility Increases The Capacity of Ad-The Capacity of Ad-

hoc Wireless hoc Wireless NetworksNetworks

ByByGrossglauser and TseGrossglauser and Tse

Gautam PohareGautam PohareHeli Mehta Heli Mehta

Computer ScienceComputer ScienceUniversity of Southern CaliforniaUniversity of Southern California

Outline• Characteristics & Technical challenges

of mobile adhoc networks. • Diversity and its analysis• Gupta and Kumar Model• The authors new approach• Session and Transmission Model

Outline (Cont’d)• Results • Two-phase Scheduling • Sender/Receiver centric approach• Distributed Implementation• Related Work• Conclusion and Critiques

Wireless Internet accessWireless LANsWireless Video/Music Multimedia to the CarSensor Networks Smart Homes/AppliancesAutomated Vehicles/HighwaysAll this and more…

Wire less Networks

Mobile AdMobile Ad--Hoc NetworksHoc Networks

No backbone infrastructure

Routing can be multihop.

Network is dynamic (links change, nodes move around) Fully connected network but with different link SINRs

Adaptive techniques can be exploited

Important for ubiquitous computing

Technical Challenges• Hardware

– Small, lightweight,low power

• Communication Systems– Harsh-time varying propagation

environment

– Scarce radio spectrum

– Data rates

Mobile Wireless Network• Characteristic:

– time variation of the channel strength of the underlying communication links.

• Reasons:– Multi path fading– Path loss via distance attenuation– Shadowing by obstacles– Interference from other users.

Use of Diversity for Time Variation

• Point-to-point Diversity can be obtained by:– Interleaving of coded bits– Combining of multipaths– multiple antennas or multiple basestations

• Multiuser diversity: Basic Idea: performance ↑ thro many independent

signal paths between tx-rc. Multiple users are communicating to the base station

via time-varying fading channel. Motivation from Knopp and Humblet’s paper.

Diversity Analysis:• Obtained by:

- Allocating channel to the user who can best exploit it.

- Overall throughput maximized.

• But Problems in this …… It incurs additional delay. Additional delay [buffer pkts until channel becomes

strong] More diversity can be obtained on asynchronous networks Examples: Email, Event notification

More diversity can be obtained on asyn

n/w reasons: • N/w topology changes due to user

mobility• Theorems we will see which proves

this.• Focus is on applications that can

tolerate delays of several mins/hrs like email,….

Gupta and Kumar Model:• Fixed Ad-hoc network with Relaying

– Nodes are immobile– Each node can be source, destination or

relay

• Result:– As the number of nodes per unit area n

increases, the throughput per S-D pair decreases approximately 1/n.

Problems with fixed Adhoc N/w :• Excessive interference in long range direct

communication.• If relaying used - # of hops increase (root of

n)• Nodes carry lot of relay traffic. Hence, more delay, less throughput.• Scalability problems !!! - Traffic rate per S-

D actually goes down to Zero as n increases.

New Approach by the authors is :• Avg long-term throughput per S-D pair can be kept

constant even if n increases !• Totally contrasting to fixed model by G & K.

How is this achieved ???• Source node sends packets to every other nodes

within its radius which act as relays.• Relays, when come near to the destination node,

deliver packet.• Many relay nodes => more probability its close to

dest node.• Imp: Max 1 Relay => Max 2 Hops S-D . So η ↑.• Fault Tolerance !!!

Models• Session Model:

– Each node is source node for one session and destination node for another session.

– Source-Destination association does not change with time.

– Each node has an infinite buffer capacity.– Nodes themselves move.

Transmission Model(Time slots present)

• At time t, node I transmits data at rate R packet/second to node j if

Pi(t) - transmission power, ij(t) - channel gain, - signal to interference ratio, No - background noise power, L - processing gain

Transmission Model (Cont’d)

The channel gain is given by (α > 2 , Xi and Xj are node locations)

2 Models used for experiments:

• One with packets directly transmitted from S-D

• Another nodes can be relays.• Scheduler, depending on scheduling policy,

chooses senders and receivers based on power levels• Long term throughput improvement is

feasible.

Results:

• Thus within a factor of log n, the throughput per S-D pair goes to zero like R/ n in the case when the nodes are fixed.

Fixed Node with Relaying ( G & K Model):– The following results yield upper and lower

bounds on the throughput.• Theorem : There exits c and c’ such that

Results (Cont’d):Fixed Node with Relaying ( G & K

Model):Reason for throughput becoming zero for fixed

nodes:• As Model scales, relay nodes ↑ by √n

In mobile nodes with Relaying, max # of hops is 2.Without relaying, no way of high throughput as n

increases.

Results• Mobile nodes without relaying::• Theorem: Direct transmission between the source and

destination nodes, and no relaying !

ResultsMobile nodes without relaying::• Theorem (Contd) : If c is any constant satisfying

This result says that without relaying, the throughput per S-D pair goes to zero at least as fast as

Problems with mobile nodes w/o relaying

• Too much long range communication• Resulting interference limits #

concurrent transmissions.• Hence throughput low.

Results Mobile Nodes with Relaying

• Why you need the relaying?• the source and destination become nearest

neighbors for small fraction of time(1/n)• Concurrent O(n) transmission are possible• How???• Theorem: For the scheduling policy , the expected

number E[Nt] of feasible sender-receiver pairs is (n).

Mobile Nodes with Relaying gives :

• Transmission to nearest nodes. • O(n) Concurrent successful

transmissions per time slot. • Receiver power at the nearest

neighbor is of same order as total interference from O(n) interferers.

• At max 2 hops for packet to reach from source to destination

Two phase scheduling

• Scheduling of packet transmission from source to destination : 1st phase

• Scheduling of packet from relays to final destination: 2nd phase

• Interleaved phase• Scheduling policy depends only on

location of the node

Two-phase scheduling policy

Throughput analysis:• Throughput = probability of two

nodes to be selected as sender receiver pair

• Throughput per each S-D pair turns out to be O(1) : theorem 3.5

Sender-Centric Vs. Receiver Centric Approach

• Sender-Centric means it is senders that selects the closest receiver to send to.

• Receiver-Centric means it is receivers that selects the closest sender from which receive.

Analysis

• Problem with receiver centric approach:-Two receivers may select the same sender • Adv of receiver centric approach:• In receiver centric approach, signal from

selected sender is always the strongest.• SIR Ratio – the interference in receiver

centric approach is stochastically smaller

Throughput for sender centric approach

Numerical Results• For given α there is an optimal sender

density Θ that maximizes the throughput.

• If density is too low the channel reuse has not been exploited.

• If density is too large the interference power becomes too dominant

• Select Θ carefully

Distributed Implementation– Node decide whether it wants to be sender or

receiver– Even phase: Sender forward packets from

source to relays.– Odd phase: Sender forward packets from relays

to destinations. – Uncoordinated access– Future work: Study of local scheduling strategies and their

impact on end to end delay.

Related Work• Infostation focused on maximizing the capacity of a

point to point channel in fix power budget• Our focus: spatial reuse of channel to

achieve higher throughput.• Related interference model studies the probability of capturing a single

receiver• Gupta & Kumar model

Conclusion• Results show that direct communication

between sources and destinations alone cannot achieve higher throughput because they are too far apart most of the time

• Delay tolerant applications can take advantage of node mobility to significantly increase the throughput capacity of networks.

Critiques:• The scheduling policy given is totally

abstract. • There will be duplicate packets problem

when multiple relays send the same pkt to the destination. No explanation for this.

• No way for real-time data – audio,video etc.• No communication protocol specified which

is crucial for efficiency in wireless networks• All Theoretical concepts, no practical

implementation model !!