Advanced Communication Network 2009 2009.06.08 2009.06.08 Joint Throughput Optimization for Wireless Mesh Networks R97725024 戴智斌 R97725037 蔡永斌 Xiang-Yang

Advanced Communica-tion Network 2009

2009.06.08

Joint Throughput Optimization for

Wireless Mesh Networks

R97725024 戴智斌 R97725037 蔡永斌

Xiang-Yang Li, Senior Member, IEEE, Ashraf Nusairat, Student Member, IEEE, Yanwei Wu, Student Member, IEEE, Yong Qi, Member, IEEE,

JiZhong Zhao, Member, IEEE, Xiaowen Chu, Member, IEEE, and Yunhao Liu, Senior Member, IEEE

IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 8, 2009

Advanced Communica-tion Network 2009 2009.06.08

Outline

Introduction

System Model and Assumption

Problem Formulation

Efficient TDMA Scheduling

Performance Evaluation

Conclusion

Advanced Communica-tion Network 2009 2009.06.08 3

Introduction


Introduction (1/2)

Wireless mesh network (WMNs) are being

used for extending the Internet

connectivity for mobile nodes.

Many US cities (e.g. Medford, Oregon,

Chaska, Minnesota; Nashville, Illinois; and

Gilbert, Arizona) have deployed WMNs.


Introduction (2/2)

The major problem of WMNs is the

reduction of capacity due to interference

caused by simultaneous transmissions.

How to optimize joint throughput under

certain fairness constraints via joint

routing, link scheduling, and dynamic

channel assignment.





7

Wireless Mesh Network– MMM for (multihop multiradio multichannel)

– with multiple sink nodes (wireless router with gateway

function)

Internet


Assumptions

Different nodes may have…– Multiple radios

– Multiple channels

– Different transmission range and interference

range

– Combined channel

8


Dynamic Channel Combining

Channel 1

Channel 2

Channel 3

Channel 4

Channel 5

Channel 1

Channel 2

Channel 3

Channel 4

Channel 5

Channel 1

Channel 2

Channel 3

Channel 4

Channel 5

Combining

InterferenceNode 1 Node 2



Multiple radios– Virtual nodes and links

10

u

z

v

w



Why we need interference models?– PrIM, fPrIM, RTS/CTS, TxIM

11

Sender 1

Receiver 1

Sender 2

Receiver 2

Interference


Problem Formulation


Problem Formulation

Given:– an MMM WMN G = (V,E), flow demand l(u)

from each sourch node u.

Objective– Maximize Fairness

– Maximize Joint Throughput

13


Maximize Fairness

14

Node 1

Node 4

Node 3

Node 2

Node 6

Node 7

Node 5Mobile Client

Mobile Client

The flow

coming to the node

The flow going out of

the node

Achieved Flow

load demanded

flow achieved of ratio minimum λ


MAX Fairness LP

15


Maximize Joint Throughput

16

Internet

g

iiisp sf

1

)(max

Node NodeNode NodeNode

Node Node Node Node

Node NodeNode NodeNode

Gateway Router


MAX Joint Throughput LP

17


Interference Free Schedule

Link Scheduling– Give each link a schedule

– list of time slots and corresponding channels

Objective– interference free

18

GL


Mixed IP MAX Flow Fairness

19


LP Flow Fairness

Maximize Fairness

20


Maximize Joint Throughput

21





Centralized scheduling for link

transmission– Assume that T is the number of time slots per

scheduling period.

– We need to schedule time slots for

a virtual link using channel .

23




Links Sorting

Different links sorting algorithm– Our algorithm relies on some special sorting of

the links, which depends on the interference

models.

– No common sorting that works for all

interference models.

25


Improvement

Parametric searching improve the overall

achieved flow.

26

MCC 1,


Performance Evaluation


Impact of Multichannels (1/1)

When channel combining is performed, it provides higher throughput and higher fairness..

Increasing the number of channels per radio increases the throughput and fairness.


Impact of Multiradios (1/1)

When channel combining is performed, it provides higher throughput and higher fairness..

The bouncing is that the actual number of radios assigned to each node is randomly generated for

each simulation run.

Increasing the number of radios per node “seems to” increase the throughput and fairness.


Impact of Interference Model (1/1)

With channel combining, the network receives the highest fairness and throughput under PrIM, while it receives the lowest fairness under the

RTS/CTS model and lowest throughput throughput under TxIM.


Impact of Interference Model (1/1)

Without channel combining, the network receives the highest fairness and throughput

under PrIM, while it receives the lowest fairness and throughput under the RTS/CTS model.


Conclusion


Conclusion (1/1)

The main contributions of this paper are– Theoretical performance guarantee for

algorithms.

– Impact of channel combining.

– Realistic models and other restrictions.

Advanced Communica-tion Network 2009

2009.06.08

Documents

Advanced Communication Network 2009 2009.06.08 2009.06.08 Joint Throughput Optimization for Wireless Mesh Networks R97725024 戴智斌 R97725037 蔡永斌 Xiang-Yang