Cross-Layer Network Planning and Performance Optimization Algorithms for WLANs

Cross-Layer Network Planning and Performance Optimization Algorithms

for WLANs

Yean-Fu Wen

Advisor: Frank Yeong-Sung Lin

2007/4/9

2

Agenda

Introduction Wi-Fi Hotspots (Ch. 2)

System Throughput Maximization Subject to Delay and Time Fairness Constraints

Wireless Mesh Networks (Ch. 3 and Ch. 4) Fair Throughput and End-to-end Delay with Capacity Assignmen

t Fair Inter-TAP Routing and Backhaul Assignment Algorithms

Ad Hoc Networks (Ch. 5) A Path-based Minimum Power Broadcast Algorithm

Wireless Sensor Networks (Ch. 6 and Ch. 7) Dynamic Radius, Duty Cycle Scheduling, Routing, Data Aggrega

tion, and Multi-Sink (Cluster) Conclusions & Future Work

Agenda Ch. 2Introduction Conclusion Ch. 3 Ch. 4 Ch. 5 Ch. 6 Ch. 7

3

Background

Wireless networks are the key to improving person-to-person communications, person-to-machine communications, and machine-to-machine communications.

The research scope of this dissertation covers various network architectures, and various protocol layers

[Ref: B3G Planning]


4Agenda Ch. 2Introduction Conclusion Ch. 3 Ch. 4 Ch. 5 Ch. 6 Ch. 7

5

Motivation

Fairness to ensure the allocated resources are sufficient for all MDs

to achieve equivalent throughput, channel access time, or end-to-end delay

to distribute and balance the traffic load or related links to solve the fairness issues due to spatial bias or energy

constraints in three networks with different structures Multi-range

causes different levels of energy consumption causes different bit-rate (capacity)

Multi-rate causes performance anomalies


6

Motivation

Multi-hop causes throughput and end-to-end delay fairness issuers causes inefficient energy usage in data-centric networks

Multicast reduce the number of duplicate packets in order to gain a “multica

st wireless advantage” and thereby reach multiple relay nodes reduce the number of duplicate packets in data-centric WSNs

Multi-channel whether to use multi-channel to reduce the number of collisions

Multi-sink in WMNs, find a TAP trade-off in routing to a backhaul via a shorte

r path or routing to light-load links and backhaul in WSNs, find a source sensor trade-off between the shortest rela

y node or the sink node and the in-network process to reduce energy consumption


7

Objective

How to achieve a throughput and channel access time fairness.

How to fairly allocate resources to solve the spatial bias problem in single hop or multi-hop wireless networks.

How to fairly distribute the traffic load among the relay nodes to reduce end-to-end delay and among the sensors to increase the sensor network’s lifetime.


8

Solution Approach

NS2 + MATLAB Lagrangean Relaxation (LR)

0

10

20

30

40

50

60

70

1 401 801 1201 1601 2001 2401

The number of iterations

Pow

er c

onsu

mpt

ion

UB

LB

PMST

=2

=1=0.5=0.25 =0.125 …


9

System Throughput Maximization Subject to Delay and Time Fairness Constraints in WLANs

We discuss how to achieve a trade-off between throughput fairness and channel access time fairness in 802.11 WLANs.

Problem multiple bit rates cause performance anomalies.

tF Slow MH

Ts TsTfTf

F Slow MH

Throughput fairness vs. channel access time fairness


10


Objective: maximize system

throughput. Subject to:

packet size; initial contention window si

ze; multiple back-to-back pack

ets; maximum cycle time time fairness;

To determine: the initial contention

window size for each bit rate class

the packet size for each bit rate class

the number of multiple back-to-back packets of class-k in a block within one transmission cycle

tdata ACK

SIFS

T(N)DIFS

backoff time

SLOT


11


Proposed algorithm modified binary search (Unimodal curve interval based on f

airness index constraints ) theorem: If the time value x is deducted from a class-k M

H, and it does not change any other class-j MHs, then the fairness:

increases iff x < xk – xj.

remains the same iff x = xk – xj.

decreases iff x > xk – xj.


12


Experiment results Although the problem has been shown to be NP-complete,

our numerical results reveal a simple unimodal feature The relation between three MAC layer parameters (i.e., the

initial contention window, packet size, and multiple back-to-back packets) and fairness achieves access time near-fairness and maximizes the system throughput with a simultaneous delay bound.

20% improvement in system throughput over the original MAC protocol.


13

Fair Throughput and End-to-end Delay with Capacity Assignment for WMNs

We discuss the scenario where many clients use the same backhaul to access the Internet. Consequently, throughput depends on each client’s distance from the gateway node.


14


Objective: to minimize the maximal

end-to-end delay of the WMN.

Subject to: capacity link delay

To determine: the capacity that should be

allocated to the selected links of a TAP node.

the end-to-end delay on the selected path of a TAP node.

the maximum end-to-end delay of the WMN.


15

3 4

2

s1,1

s2,2 Link (2,3) Link (3,4)

1 Link (1,3)


Proposed algorithm monotonic increases in f(u,v)

the delay time approaching ∞, when f(u,v) C(u,v) the delay function is a convex function

020406080

100120140160180200

0.8

0.82

0.84

0.86

0.88 0.9

0.92

0.94

0.96

0.98

Traffic load / Link capacity

The

del

ay ti

me

Delay time


16


Experiment results


0

5

10

15

20

25

50 70 90 110

130

150

170

190

The number of TAP nodes

Nor

mal

ized

end

-to-e

nd d

elay

Extended delay fairness scheme (by EDTB)Spatial bias fairness schemeAverage capacity scheme

17

Fair Inter-TAP Routing and Backhaul Assignment Algorithms for WMNs

How to cluster backbone mesh networks efficiently so that the load-balanced routing is concentrated on given and “to-be-determined” backhauls.

Problem


backhaul

TAP

link

18


Objective: to minimize the sum of the

aggregated flows of selected links

Subject to: budget backhaul assignment backhaul selection routing link capacity load balancing

To determine: which TAP should be selected to

be a backhaul which backhaul should be

selected for each TAP to transmit its data

The routing path from a TAP to a backhaul.

whether a link should be selected for the routing path.

aggregated flow on top-level selected link.

aggregated flow on each backhaul.

a top-level load-balanced forest.


19


Proposed algorithm weighted backhaul assignment (WBA) algorithm greedy load-balanced routing (GLBR) algorithm


20


Experiment results the load-balanced routing and backhaul assignment experi

ment results demonstrate that the GLBR plus WBA algorithms with the LR-based approach achieve a gap of 30% and outperform other algorithms by at least 10%

0

100

200

300

400

500

600

25 36 49 64 81 100 121 144Number of nodes

Nor

mal

ized

flow

s

GLBR-1 UB-1 LB-1GLBR-2 UB-2 LB-2GLBR-4 UB-4 LB-4


0

100

200

300

400

500

600

20 30 40 50 60 70 80 90 100

Number of nodes

Nor

mal

ized

flow

WBA LIDHD UBLB

21

A Path-based Minimum Power Broadcast Algorithm for Ad-hoc (Sensor) Networks

We discuss how to construct a multicast tree that minimizes power consumption with “multicast wireless advantage”.

Problem

1

2

3

4

5

6

7

8

9

11

12

10

(1,2)

(1,3)

rv

ev(rv)

ev(rv) = rv + a

Power

consumption

(normalized)

Power range


22


Objective: to minimize the total bro

adcast power consumption

Subject to: routing tree radius

To determine: routing path from each

source to the destination, denoted as an OD-pair.

whether a link should be on the multicast tree.

a multicast tree. transmission radius for

each MD.


23


Proposed algorithm a path-based minimum power broadcast algorithm

Experiment results

0

10

20

30

40

50

60

70

25 35 45 55 65 75 85 95 105

The number of nodes

Pow

er c

onsu

mption (norim

aliz

ed)

MSPT PMST GIBTBIP EWMA LR-UBLR-LB


24

Cross-Layer Duty Cycle Scheduling with Data Aggregation Routing for WSNs

We discuss how to increase the battery lifetime and energy consumption efficiency of a network from the Physical layer to the Application layer in term of the following issues: data aggregation tree structure Routing duty-cycle scheduling node-to-node communication time the number of retransmissions dynamically adjusted radius


Physical layer

Application layer

MAC layer

Network layer

25


Objective: minimize the total energy

consumed by a target transmission

Subject to: restrictions on the structure

of trees in the form of three link constraints

duty cycle scheduling. the time for node-to-node

communication dynamic radius

To determine: a routing path from the

source node to the sink node; the time at which aggregation

of sub-tree data will be completed;

the earliest time at which a node wakes up and begins aggregating data; and

the time needed for a successful node-to-node transmission.

the power range of each node;


26


S4

13

1

1

2

2

3

D κ

S1 S2 S3

[0, 0+1][0, 0+3]

[0, 3+1]

[3, 4+1]

[3, 5+0]

[0, 3+2]

[0, 0+2][0, 0+3]

2

34

7

8

65

O

Proposed algorithm


00

00

0

0

0

0

∞ ∞∞

0

∞

27


Experiment results

Maximum Communication Radius = 2.5

0

10

20

30

40

50

60

70

80

10 20 30 40 50 60 70 80 90 100The number of sensors

Ene

rgy

cons

umpt

ion

LRA SPT GIT CNS

The number of nodes = 250The number of source nodes = 90

30

35

40

45

50

55

60

65

70

1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4

The power range

Ene

rgy

cons

umpt

ion

LRA SPT GIT CNS

The number of source nodes = 90Maximum power range = 2.5

30

35

40

45

50

55

60

65

70

75

100 110 120 130 140 150 160 170 180 190 200 210 220 230 240 250

The number of sensor nodes

Ene

rgy

cons

umpt

ion

LRA SPT GIT CNS


0

20

40

60

80

100

120

140

LRA SPT GIT CNSThe data aggregation routing algorithms

Ener

gy c

onsu

mption O-MAC T-MAC S-MAC

28

Energy-Efficient Data Aggregation Routing and Duty-Cycle Scheduling for Multi-Sink WSNs

Problem We discuss how to increase the lifetime in the networks

already discussed with a multiple sink structure (outgoing information gateways) and a cluster structure (source node’s message must forward to cluster-head first)


29


Objective: minimize the total energy

consumed by a target transmission to one of the sink nodes.

Subject to: sink selection ….(see the previous

problem)

To determine: The sink node that a source

node will route to; ….(see the previous problem)


30


Experiment results

0

20

40

60

80

100

120

140

160

180

1 2 3 4 5 6 7 8 9 10The number of sink nodes

Ener

gy c

onsu

mpt

ion

MDAR GIT CNS SPTO-MAC S-MAC T-MAC


31

Conclusions & Future Work

For hot-spot networks system throughput maximization subject to delay and time

fairness constraints

For mesh networks fair inter-TAP routing fair inter-TAP routing & backhaul assignment algorithms fair throughput and end-to-end delay routing

For ad hoc networks message broadcasting dynamic adjustment of the transmission radius


32


For wireless sensor networks data aggregation routing duty cycle scheduling node-to-node communication time retransmissions dynamic radius multi-sink cluster


33


Hot-spot & Mesh Networks channel assignment

Ad hoc & Sensor Networks the proposed maximization of mobile network lifetime is extende

d to include balancing power consumption among all nodes within a multiple session construction.

IEEE 802.16 BWA Networks optimization of the related parameters and placing controls on sc

heduling and admissions to minimize delay and maximize performance under QoS considerations;

minimization of end-to-end delay with controls on scheduling in IEEE 802.16 mesh mode.


34

THANK YOU FOR YOUR ATTENTION


35

Appendix A: To increase a sensor network’s lifetime

Destination

Origin


36

Energy-Efficient Data Aggregation Routing and Duty-Cycle Scheduling in Cluster-based WSNs

κ

S1

S2

S3

S4

13

1

1

2

23

[nu, luv]

[n5,l54]

[0, 3+1]

[3, 4+1]

[3, 5+0]

[0, 3+2]

[0, 2]

[0, 3]

2

34

7

8

6

5

[nu, mu] of each node denote the earliest wake up time and the aggregated time successful transmission, respectively.

[nu, max{mv} + luv]


37

Energy-Efficient Data Aggregation Routing and Duty-Cycle Scheduling in Cluster-based WSNs

Problem we discuss how to enlarge the lifetime in the previous

issues with a multiple sink structure (outgoing information gateways) and a cluster structure (source node’s message must forward to cluster-head first)


Documents

Cross-Layer Network Planning and Performance Optimization Algorithms for WLANs