adaptive qos for service- oriented learning environments colin allison, martin bateman, ross nicoll...
Post on 22-Dec-2015
218 views
TRANSCRIPT
Adaptive QoS for Service-Oriented Learning
EnvironmentsColin Allison, Martin Bateman, Ross
Nicoll and Alan Ruddle
School of Computer ScienceUniversity of St Andrews
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
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 Requirement
Interactive Resource Type
Example Application
Bandwidth
Sample Rate
Delay Jitter Loss Tolerant
Timelin-ess
Continuous Media
Interactive video
high 15 fps 250 ms Yes Yes
Interactive audio
Low - medium
8000 hz 250 ms Yes yes
Respon-siveness
Web-Server Based
CGI/Servlet
Low-high N/A 5 s No No
What does the Grid bring
• Common infrastructure– OGSA, WSDL, UDDI, etc
• Component sharing• Dynamic Service
Composition• QoS based service
discovery
Registry
ServiceRequester
ServiceProvider
12
3
FiGS – Finesse Grid Services
Browser
Video
User Web Servlets
GS:
Manager
GS: Notebook
GS: Conferencing
GS: Portfolio
GS: Stock Data Source 1 GS: Stock
Data Source 2Finesse
Services
Grid Services
Application
VoiceML
Video
Phone
Internet QoS Approaches
• Resource Reservation– Eg IntServ
• Aggregate flows– Eg DiffServ
• Adaptive• Best effort
– Eg most applications
IncreasingInfrastructure
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
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
Conclusions
• Collaborative Learning Environment– Achieve pedagogical goals
• Pedagogical goals -> QoS requirements
• Architecture for Adaptive QoS– Deployable now