Transcript A Grid Approach to provide Effective Awareness to On-Line Collaborative learning teams

1st International Workshop on
Distributed e-Learning Environments
14th of March 2005
A Grid Approach to Provide Effective
Awareness to On-line Collaborative
Learning Teams
by
Santi Caballe, Thanasis Daradoumis,
Claudi Paniagua and Fatos Xhafa
Index
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Introduction: the importance of providing effective
awareness to on-line collaborative teams.
Knowledge of group and individual activity,
and coordination are central to successful
cooperation. These factors are clearly critical
concerns in the design of computer systems […]
P. Dourish & V. Bellotti (1992)
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Index
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Introduction: the importance of providing effective
awareness to on-line collaborative teams.
 Approach: need for structuring and processing of
large amounts of group activity information.
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Index

Introduction: the importance of providing effective
awareness to on-line collaborative teams.
 Approach: need for structuring and processing of
large amounts of group activity information.
 Problem: lack of computational resources.
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Index

Introduction: the importance of providing effective
awareness to on-line collaborative teams.
 Approach: need for structuring and processing of
large amounts of group activity information.
 Problem: lack of computational resources.
 Solution: a Grid-based approach to process group
activity information through an application of the
Master-Worker paradigm using Planetlab platform.
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Index
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Introduction: the importance of providing effective
awareness to on-line collaborative teams.
Approach: need for structuring and processing of
large amounts of group activity information.
Problem: lack of computational resources.
Solution: a Grid-based approach to process group
activity information through an application of the
Master-Worker paradigm using Planetlab platform.
Experimental results: the benefits of a parallel
processing approach
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Index
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Introduction: the importance of providing effective
awareness to on-line collaborative teams.
Approach: the process of creating awareness.
Problem: lack of computational resources.
Solution: a Grid-based approach to process group
activity information through an application of the
Master-Worker paradigm using Planetlab platform.
Experimental results: the benefits of a parallel
processing approach
Conclusions and future work.
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Introduction (I)
Providing awareness to on-line learning teams
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Awareness of co-learners’ activities is essential to achieve
a successful cooperation, in terms of
 implicit coordination
 collaborative learning
 informal and spontaneous communication
Awareness allows tutors to track the collaborative learning
process for several purposes such as
 scaffolding
 assessment
 monitoring
Awareness enhances the collaboration in great deal in terms
of decision-making, social engagement, support and so on.
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Introduction (II)
Providing awareness to on-line learning teams
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During the collaboration, learners need to be aware of what
others are doing at the same time and what they did in the
past. This implies that awareness can be done in both modes
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Supplying effective and transparent awareness to users in
both modes is a significant challenge since
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synchronous: to provide real-time information (e.g. co-members
location and availability, who is doing what, etc.).
asynchronous: to provide deferred information (e.g. who, when, how
and where a shared resource has been created, changed, read, etc.).
users interact with the system all the time and generate a great
amount of information.
this information may include a great variety of types and formats.
the information collected needs to be classified, processed and
analyzed and make the analysis results available even in real time.
This requires processing capacity beyond a single computer.
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Introduction (III)
Context
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Group activity at Open University of Catalonia involves
hundreds of students and dozens of tutors in several on-line
courses.
 The complexity of the learning practices entails intensive
collaboration activity.
 BSCW is used as a groupware system to capture group
activity interaction in log files.
 BSCW does not provide log file processing nor statistical
analysis capabilities.
 BSCW generates a huge daily single log file and does not
classify nor structure data in any way.
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Approach (I): The process of creating awareness
The whole picture
Four stages in information management:
 Classification, processing, analysis and presentation.
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Approach (II): The process of creating awareness
Stage I: Classification
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Collection of information.
 Extraction of actions.
 Identification of events.
 Categorization according to
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Learning product
Group functioning
Scaffolding
Store as system log files.
Classification in synchronous environments is very similar.
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Approach (III): The process of creating awareness
Stage II: Processing
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Obtain event information from
large log files.
 Process log files according to
desired criteria. e.g.
•
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time
workspace
Store processing results in a
suitable database.
Processing of events needs great computational power.
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Approach (IV): The process of creating awareness
Stage III: Analysis
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Need for extracting
complex knowledge from
the database.
 Define consulting criteria.
 Send criteria and data to
external statistics package.
 Obtain useful statistical
results from the analysis.
External analysis offers the best existing statistical package.
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Approach (V): The process of creating awareness
Stage IV: Presentation
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Predefine an XML coding to
represent ad hoc statistical
measurements.
 Structure statistical results
into XML output.
 Convert XML into desired
presentation format.
 Present results to users.
Users receive knowledge as awareness information.
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Statement of the problem (I)
Need for processing of event information
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Real on-line environments with a large number of
students and tutors that are geographically
distributed.
 High degree of user-user and user-system
interaction generates lots of event information.
 Constant provision of awareness to group
participants in real-time.
 Essential to monitor, track and evaluate real,
complex, long-term, collaborative problem-solving
situations.
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Statement of the problem (II)
Lack of computational resources
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Need for processing of a huge amount of event
information gathered in single log files.
Essential to dispose of the processing results of
group activity in real-time.
Event information in log files should be partitioned
in multiple log files according to particular needs.
Event information must be constantly processed in
an efficient manner during the processing stage.
Lack of sufficient computational resources is the
main obstacle to the constant processing of
multiple data log files in real time.
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Solution (I)
Redefining the processing stage
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Obtain event information from
large log files.
Structure the information
according to particular needs.
Create log files of different
degrees of granularity.
Process all log files at the
same time.
Store results in the database.
Need for the processing of all log files to be parallelized.
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Solution (II)
A Grid-based solution
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Grid technology provides broad access to massive
information and computational resources.
 In this context, Grid computing paradigm
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overcomes the lack of computational resources to process
a large amount of event information.
allows processing of the log files taking advantage of the
parallelism inherent in the distributed nature of Grid.
provides load balance in the processing of log files of
different granularity.
Master-Worker paradigm using Planetlab platform,
a Grid-based approach for processing log files.
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A Grid approach (I)
Master-Worker paradigm
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Distinguishes two types of processors:
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Advantages:
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master: performs the control and coordination tasks.
workers: perform most of the computational work.
flexibility: workers can be implemented in different ways.
scalability: workers can be easily added.
separation of concerns: master does coordination and
workers do specific tasks.
Target: parallel applications with weak
synchronization and reasonably large grain size.
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A Grid approach (II)
A prototype for processing log files (I)
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EventExtractor: extracting information from BSCW
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MW model: appropriate in this context given that
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converts event information into well-formatted data.
stores the extraction results in a database.
needs a lot of time to process sequentially.
log files of different granularity are processed.
workers are not synchronized between them.
communication load between master and workers are low.
Planetlab platform: using a real Grid environment
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by installing the Globus Toolkit 3 Grid service container,
and deploying the prototype on Planetlab.
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A Grid approach (III)
A prototype for processing log files (II)
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A minimal Grid implementation made up of:
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the worker as a Grid service that does the main work by the next steps:
• wraps the EventExtractor routine,
• publishes an interface that the master calls in order to dispatch a task,
• passes a string representation of the events to be processed, and
• returns a data structure containing performance information.
After completion the task, the worker is put back into a queue of idle workers
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the master first obtains the event log file to be processed, the available
workers, the task size to be dispatched to workers and the number of
workers to use that put in a idle queue. Then enters the next loop:
• reads a specific number of events from a event log file,
• calls a idle worker and sends it the events to be processed,
The master exits the loop when all events in the current log file have
been read and all tasks to be dispatched have been finalized.
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Experimental results (I)
Preliminaries
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An ad hoc test battery was designed made up of:
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exhaustive collection of log files
• from the spring term of a course with 140 students arranged in 5member groups and 2 tutors.
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a selected sample of a few log files
• as a representative stratum of file size and event complexity.
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All test battery was processed by the EventExtractor
on single-processor nodes of Planetlab
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involving usual configurations.
with different work load.
repeating the execution several times.
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Experimental results (II)
Parallel processing results
The parallel processing results were obtained by
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running tests for different task sizes and number of workers
observing how much close each set of workers is to
achieve its theoretic maximum speed-up.
Task Size = 5
% of Max Speed-up Achieved
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1,2
1
0,8
0,6
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2
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Num ber of Workers
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Relative speed-up for 5-event task and different number of workers
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Experimental results (III)
Analysis of the results
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Apart from very small task sizes, the speed up
observed was very close to the maximum achievable.
 The more workers used in our tests the closer to
the maximum was the speed up achieved by the
smallest tasks.
 Results were a little biased due to the homogeneous
behaviour observed in Planetlab and they should be
adjusted to the dynamic workload of a real Grid.
 Event complexity is key to take advantage of the
benefits of a Grid environment as BSCW system
generates a very few different types of events.
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Conclusions and future work
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We have first argued how the provision of continuous
awareness to on-line learning teams can greatly
improve the group activity.
 We have also shown that in the process of creating
awareness there is a strong need for computational
resources to process large amounts of information.
 According the results obtained in this study, the
benefits of Grid enhances depending on the volume
and complexity of event log files to be processed.
 As ongoing work, we plan to improve our prototype
in terms of communication master-workers, faulttolerance and dynamic discovery of idle workers.
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Thank you !
Questions?
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