Thesis Topic Details

Topic ID:
3522
Title:
Automatic Abstraction in Mining for Cloud Management Processes
Supervisor:
Ingo Weber
Research Area:
Cloud Computing, Distributed Systems, Business Process Management
Associated Staff
Assessor:
Len Bass
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE BIOM BINF SE
Group Suitable:
Yes
Industrial:
No
Pre-requisites:
COMP9322 or COMP9423
Description:
With developments such as virtualization and cloud computing, system operation (such as installation, deployment, upgrading) has become a significantly more complex task: an operator might be responsible for thousands of machines, which are built and connected in ever more complex ways. Therefore it is important to support operators to make sure that, e.g., an upgrade process is executing correctly and has the desired result.

Our work thus is concerned with (i) discovering how processes are executed for log files, and (ii) making sure a running process corresponds to the correct execution. Initial works of ours have been published - see below.

One issue in discovering a process model from logs is the level of abstraction: usually, the logs are a lot more fine-grained and detailed than the level of abstraction we want in our process models. Setting the level of abstraction is currently done in a largely manual fashion. When trying to abstract automatically, several hard research challenges arise: which events belong together? And when is a model appropriate, e.g., easy to understand for a human?

In the context of this work, there are numerous open topics for future research, see
http://ssrg.nicta.com.au/students/theses.pml#ug-IW
/ other topics in the database supervised by me.

Previous publication:
- Sherry Xu, Ingo Weber, Hiroshi Wada, Len Bass, Liming Zhu and Steve Teng. Detecting Cloud Provisioning Errors Using an Annotated Process Model. 2nd Workshop on Secure and Dependable Middleware for Cloud Monitoring and Management, pp. 6, Beijing, China, December, 2013.
Comments:
Students will work closely with senior researchers at National ICT Australia (NICTA) in a very friendly, diverse team environment. Suitable for students interested in software design, architecture, and practical industry development methods.
Students will be exposed to latest cloud technologies and advanced methods from business process management / process mining.
Past Student Reports
 
No Reports Available. Contact the supervisor for more information.

Check out all available reports in the CSE Thesis Report Library.

NOTE: only current CSE students can login to view and select reports to download.