Transcript Adaptive QoS for Service-Oriented Learning Environments

Adaptive QoS for ServiceOriented Learning Environments
Colin Allison, Martin Bateman, Ross Nicoll
and Alan Ruddle
School of Computer Science
University of St Andrews
[email protected]
Overview
• Identify goals of Collaborative Learning
Environments
• Educational goals -> QoS requirements
• How to meet QoS requirements
• Example: Finesse – Learning
environment
• Conclusions
Pedagogical Goals
• Collaboration
– Synchronous
• video
• audio
– Asynchronous
• notebooks
• instant messenger
• Ubiquitous & heterogeneous
– Network
– Device
• Experiential and Active Learning
• Realism – ‘Live data’
Finesse
Finance Education in a Scalable Environment
• Supports teaching of fund management
• Virtual portfolios at the core
– Inspect historic data
– Buy/sell shares
– Try to make a profit
• Notebook for asynchronous collaboration
Finesse
Pedagogical aspects of
Finesse
•
•
•
•
Asynchronous
Ubiquitous – 100% web
Realism – London Stock Exchange
Experiential
Finesse – To add
• Re-engineer to be GSDL
based
• Synchronous
communications
– Video conferencing
– Synchronous groupware
• Device independence
QoS Aspects
• User perception
–
–
–
–
Responsive
Timely
Looks good
Easy to use
• Network
–
–
–
–
Low delay
Low jitter
High bandwidth
Low packet loss
QoS Timeliness &
Responsiveness
QoS
Interactive Example
Bandwidth Sample
Require Resource Application
Rate
ment
Type
Delay
Timelin- Continuou Interactive high
ess
s Media
video
250 ms Yes
Yes
Interactive Low audio
medium
8000 hz 250 ms Yes
yes
CGI/
Servlet
N/A
No
Respon- Websiveness Server
Based
Low-high
15 fps
5s
Jitter Loss
Tolerant
No
What does the Grid bring
• Common infrastructure
Registry
– OGSA, WSDL, UDDI, etc
• Component sharing
• Dynamic Service
Composition
• QoS based service
discovery
1
2
Service
Requester
3
Service
Provider
FiGS – Finesse Grid Services
User
Browser
Video
Web
Servlets
Application
Video
Phone
VoiceML
Finesse
Services
G
S
:
GS: Notebook
M
a
n
a
g
e
r
GS: Portfolio
GS: Conferencing
GS: Stock
Data
Source 1 GS: Stock
Data
Source 2
Grid Services
Internet QoS Approaches
– Eg IntServ
• Aggregate flows
– Eg DiffServ
• Adaptive
• Best effort
– Eg most applications
Increasing
Infrastructure
• Resource Reservation
Adaptive QoS Provision
• Past network conditions -> statistics
– Active: RTP/RTCP traffic
– Passive: Traffic monitoring
• Estimate likely network path conditions
– Temporal & spatial patterns in traffic
• Inform application at start
• Application adapts to changes
Location Information Server
Conference Controller Architecture
for Video Conferencing
Adaptive QoS Advantages
• Network edge deployment
– Under your administrative control
– Manageable traffic rates
• Learns from traffic
– Sharing traffic knowledge
• Utilises session knowledge
– Duration, number of participants, type
Example Conference Configuration
Conclusions
• Collaborative Learning Environment
– Achieve pedagogical goals
• Pedagogical goals -> QoS requirements
• Architecture for Adaptive QoS
– Deployable now
Questions?
Traffic Patterns
Research
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