Transcript Ingegneria dell'Informazione

Department of Information Engineering
University of Padova, ITALY
Special Interest Group on
NEtworking & Telecommunications
A Soft QoS scheduling algorithm
for Bluetooth piconets
Andrea Zanella, Daniele Miorandi, Silvano Pupolin, Cristian Andreola
{andrea.zanella, daniele.miorandi, silvano.pupolin, freccia}@dei.unipd.it
WPMC 2003, 21-22 October 2003
Outline of the contents

Motivations & Purposes

Bluetooth Basic

Hard-QoS & Soft-QoS

Soft-QoS for Bluetooth: SFPQ

Results and Demostration

Concluding Remarks
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What and Why…
Motivations &
Purposes
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Motivations

Demand for QoS support over portable
electronic devices is increasing:


audio/video streaming

interactive games

multimedia
Unfortunately, Bluetooth does not provide native
QoS support…
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Aim of the study

Adding Soft-QoS support to BT piconets

Definition of Soft-QoS parameters

Design of Soft-QoS scheduling algorithm

Analisys of the proposed algorithm
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What the standard says…
Bluetooth basic
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Bluetooth piconet


Two up to eight Bluetooth units sharing the
same channel form a piconet
slave2
slave3
In each piconet, a unit acts as master, the
others act as slaves
master
slave1


Channel access is based on a centralized
polling scheme
Full-duplex is supported by Time-divisionduplex (TDD), with time slots of T=0.625 ms
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master
active slave
parked slave
standby
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Multi-slot packets

Data packets can be:

1, 3, or 5 slot long

Unprotected or 2/3 FEC protected
Paylod Capacity
350
300

Unprotected packet formats (DH)

higher data capacity

more subject to errors
Protected packet formats (DM):
Bytes

250
200
150
100
50
0

medium data capacity
1 slot

higher protection against errors
Medium rate
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3 slots
5 slots
High rate
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Introduction to QoS issues
QoS in Bluetooth
networks
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Resource Allocation

Different types of
applications:

Web Browsing


Streaming audio



Medium-to-high data rate
Low delay and jitter
High data rate
Voice


Low delay and jitter
Low data rate
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Hard & Soft QoS
 Hard

Widely used in wired networks

Integrated Services: flow based (RSVP)

Differentiated Services: class based
 Soft

QoS
QoS
Suitable for wireless networks

Applications may work even if, for short periods of time, QoS
requirements are not satisfied

Deal with limited bandwith and radio channel
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FPQ algorithm


Aim: providing Hard QoS support by means of
a Fair and efficient Polling scheme*
QoS parameters required for each link



Expected data rate
Maximum acceptable delay
Adjust priorities of the slaves on the basis of



Slaves’ queue length estimation
Traffic parameters
QoS parameters
*[FPQ: a fair and efficient polling algorithm with QoS support for Bluetooth piconet, INFOCOM03]
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FPQ scheme

Purpose


Slave Analyzer determines




Determine priority of each data
flow
Select the master/slave link with
highest priority
Limits

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Pdata: probability of having
queued packets
NSLP: interval of time since last
POLL/NULL sequence
Selection Algorithm


Determine the most efficient
polling sequence fulfilling QoS
requirements
Inefficient service differentiation
under high traffic loads
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Soft QoS support
Soft-FPQ algorithm for
Bluetooth piconets
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Soft-FPQ algorithm

Aim: Providing Soft QoS by means of dynamic
estimation of flows’ satisfaction

Definition of a new Soft QoS parameter: Target
Satisfaction

Priorities are adjusted according to QoS parameters
and the estimated satisfaction margin for each slave

Low traffic: high satisfaction for all flows

High traffic: distribute resources to fulfill exactly QoS request
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Soft QoS parameters




Average packet inter-arrival time: ITL
Average packet length: PL
Maximum sustainable packet delay: MD
Target Satisfaction index

Percentage of packets that are expected to satisfy the
QoS constrains
0   1
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Dynamic Satisfaction estimation
Empty queue
1
Arrival rate:  
ITL
Probability:
Arrival time:
y k  E ( , k )
p(k )  P[ yk  TSk  TAPk  MD | yk  TSk ]
Estimated Satisfaction:
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1
 i (k ) 
N
~
k
 p ( n)
n N k
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Example of dynamic estimation
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Istantaneous Satisfaction

Estimated Satisfaction is updated anytime an AP packet
is received

To cope with long silence periods of slaves, we
introduce the Istantaneous Satisfaction that is updated
slot by slot according to function …

Istantaneous satisfaction is reset at the first AP arrival
~
ˆ
 (to  t )   (to )  (, N , MD, M (t ))
1

ITL
M ( t )     t
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Maximum Delay
Number of points
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Satisfaction Margins
Satisfaction Margin:
 i  ˆi  i
Target Satisfaction
Actual Satisfaction
Normalized Satisfaction Margin:
i 
max j ( j )   i
 (max
j
( j )   h )
h
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Priority Evaluation
FPQ PriorityEvaluation

Pri      pdata  (1   )  ni   (1   )  i
 Traffic Demand
 QoS Request
Fairness
Normalized Satisfaction Index
Constants:
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  0.8
  0.7
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NS2 Simulation
Simulation of QoS
Bluetooth Piconet
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Simulation Scenario

Piconet with 7 slaves

Only upstream traffic
One application per slave

One application =1 (Hard QoS)

One application =0.9

One streaming video application =0.9

4 Best Effort applications =0.2


Simulation dynamic
 Slaves with high  are active for all the simulation time


Best Effort transmissions start sequentially seconds apart
When all the applications are active the system gets congested
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Satisfaction perceived (1/3)
Target Satisfaction: =1
Heavy
Load
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Satisfaction perceived (2/3)
Target Satisfaction: =0.9
Heavy
Load
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Satisfaction perceived (3/3)
Target Satisfaction: =0.2
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Delay Distribution


Video Streaming Delay
Distribution
Low traffic


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Video Streaming
Delay Distribution
High traffic
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Video Streaming Demo
 Scenario




Upstream traffic only
One application per slave
One application streaming
video, =0.9
Two Best Effort application,
=0.2
FPQ
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 Demo



Structure
RTP Server: send packets
of video stream
RTP Client: receive
packets and display video
Delay: introduce precomputed packet delays
SFPQ
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Conclusions & Future work

Support of Soft QoS in
Bluetooth

Better service differentiation

Efficient resource distribution

Better support to real time and
audio/video streaming
applications


Next steps



Improve algorithms setting and
introduce dynamic parameters
tuning
Extension of the algorithm to
Scatternet structures
Development of low complexity
Satisfaction Estimation
algorithms
Better behavior of the piconet
under high traffic conditions
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That’s all!
Thanks for
your attention!
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