Introduction of CS3 and Research in Workflow Technology Program

Xiao Liu {xliu@swin.edu.au}

CS3, Swinburne University of Technology Melbourne, Australia

Outline

> Introduction of CS3

– About Us

– Research

– Projects

– Collaborations

> Research in Workflow Technology Program

– Program Overview

– R&D Projects Overview

– SwinDeW Workflow Series

– Recent Publications

> Questions and Discussions

2

Introduction of CS3 (Centre for Complex Software Systems and Services)

> About Us: The Centre for Complex Software Systems and Services (CS3) is a Swinburne University research centre located in the Faculty of Information and Communication Technologies at Swinburne University of Technology in Melbourne, Australia. It is established as a Tier-1 university research centre in July 2008, but has its roots in the former Centre for Information Technology Research (CITR) established in December 2005.

> CS3 is one of the leading research centres in Australia and has an international reputation in its research areas with internationally leading researchers. It carries out research in close collaboration with industry and research partners nationally and internationally, supported by a wide range of research grants, strategic partnerships and industrial R&D projects.

3

Research in CS3

> The Centre carries out research across the following research programs:

– Component Software Technology – lead by Prof. Jun Han

– Intelligent Agent Technology – lead by Director, Prof. R. Kowalczyk.

– Web and Data Technology – lead by Prof. Chengfei Liu

– Workflow Technology – lead by Prof. Yun Yang

> targeting the following application areas:

– Service Oriented Systems

– Enterprise Software Systems

– Social Software Systems

– Cloud Computing Systems.

4

Research in CS3

5

Research in CS3

6

Projects in CS3

> Research Project Highlights (http://www.swinburne.edu.au/ict/research/cs3/projects.html)

– Novel cloud computing based on workflow technology for managing large numbers of process instances

– Managing Conflicts in Requirements Engineering with Argumentation Framework

– Rationalised Software Architecture Design

– Service Workflow for eScience and eBusiness

– Agent-Enabled Social Networks

– Reconfigurable Vehicle Software Systems

– An Organisation Oriented Framework for Collaborative Business Processes

– XML Views of Relational Databases, Constraints in XML Schema Integration

7

Research in Workflow Technology Program

> Program Overview

> R&D Projects Overview

> SwinDeW Workflow Series

> Recent Publications

8

Program Overview

> The Program conducts research into workflow technologies for complex software systems and services including peer-to-peer, grid, and cloud computing based e-science, e-business, transactional and inter-organisational workflows.

> Members:

9

Leader:Prof Yun Yang

Visitors (7-8/09):Prof Lee OsterweilProf. Lori Clarke

Researchers:Dr Jinjun ChenNauman Saeed (PhD)Qiang He (PhD - submitted)Ke Liu (PhD - submitted)Xiao Liu (PhD)Dong Yuan (PhD)Viv Farrell (PhD - submitted)Mr Bryce Gibson (IBL)

Others:Prof Ryszard KowalczykProf Chengfei Liu

Dr Jun Yan (Wollongong)Prof Hai Jin (HUST)Prof Mingshu Li (ISCAS)Prof Qing Wang (ISCAS)Prof Zhiwei Ni (HFUT)Prof Jinpeng Huai (BUAA)

R&D Projects Overview

> Primary projects:

– Novel cloud computing based on workflow technology for managing large numbers of process instances - ARC Linkage Project (LP) grant

– SwinDeW workflow family - partly funded by ARC DP

• Architectures / Models

• Scheduling / Data and service management

• Verification / Exception handling

• SLA

• (Security / trust)

10

Research in Workflow Technology Program

> Program Overview

> R&D Projects Overview

> SwinDeW Workflow Series

> Recent Publications

11

SwinDeW Workflow Series

SwinDeW – Swinburne Decentralised Workflow- foundation prototype based on p2p

> SwinDeW – past

> SwinDeW-A (for Agents) – ARC DP06

> SwinDeW-G (for Grid) – past

> SwinDeW-V (for Verification) – current (pending ARC DP)

> SwinDeW-E (for eScience) – current (pending ARC DP)

> SwinDeW-C (for cloud) – current (ARC LP)

> Others: SwinDeW-B / -S / -P / -G – past

12

SwinDeW-G

13

SwinDeW-C: Overview

14

Activity

Workflow Execution

UKVPAC

HongKong

SwinburneCS3

· SwinDeW-G· GT4· CentOS Linux

BeihangCROWN· SwinDeW-G· CROWN· Linux

SwinburneESR

· SwinDeW-G· GT4· CentOS Linux

AstrophysicsSupercomputer

· SwinDeW-G· GT4· SuSE Linux

PfC

na 1na

2na

3na 4na

5na 6na Na

ma 1ma

2ma

3ma 4ma

5ma 6ma Ma

Amazon Data Centre

Google Data Centre

Microsoft Data Centre

SwinDeW-G Grid Computing

Infrastructure

Commercial Cloud

Infrastructure

VMVMVM VM VMVMVM VMVMVMVMVM

……..

……..

……..Application

Layer

Platform Layer

Unified Resource

Layer

Fabric Layer

SwinCloud……..

VM

SwinDeW-C Peer

SwinDeW-C Coordinator Peer

SwinDeW-C: Simulation Environment

Swinburne Cluster

VMware

SwinDeW-C

…... …...Physical Machines

Layer

Virtual Machines

Layer

ApplicationsLayer

Data Centres with Hadoop

SwinDeW-C is developed based on SwinDeW and SwinDeW-G . It is currently running at Swinburne University of Technology, which is composed of 10 servers and 10 high-end PCs. To simulate the cloud computing environment, we set up VMware software on the physical servers and create virtual clusters as data centres. Every data centre created is composed of 8 virtual computing nodes with storages, and we deploy an independent Hadoop file system on each data centre. SwinDeW-C runs on these virtual data centres that can send and retrieve data to and from each other. Through a user interface at the applications layer, which is a Web based portal, we can deploy workflows and upload application data.

15

Research Topics

> Workflow Temporal Verification in Scientific Workflow Systems

– Constraint Setting (BPM, CCPE), Checkpoint Selection (ICSE, TOSEM), Temporal Verification (TASE, CCPE), Exception Handling (ACOWR, JSS, TSE)

> Data Management in Cloud Workflow Systems

– Intermediate Data Storage Strategy, Data Replacement, Data Replication (IPDPS, CCPE, FGCS)

> Security and Privacy in Cloud Workflow Systems

Research in Workflow Technology Program

> Program Overview

> R&D Projects Overview

> SwinDeW Workflow Series

> Recent Publications

17

Selected Recent Publications – Journal Papers

> Please visit http://www.ict.swin.edu.au/personal/yyang/Publications.html for a full list of all publications in WT Program

> D. Yuan, Y. Yang, X. Liu, G. Zhang and J. Chen, A Data Dependency Based Strategy for Intermediate Data Storage in Scientific Cloud Workflow Systems. Concurrency and Computation: Practice and Experience, Wiley, to appear (accepted on June 4, 2010).

> D. Yuan, Y. Yang, X. Liu and J. Chen, A Data Placement Strategy in Cloud Scientific Workflows. Future Generation Computer Systems, Elsevier, to appear (accepted on Feb. 1, 2010).

> X. Liu, Z. Ni, J. Chen and Y. Yang, A Probabilistic Strategy for Temporal Constraint Management in Scientific Workflow Systems. Concurrency and Computation: Practice and Experience, Wiley, to appear (accepted on Nov. 27, 2009).

> J. Chen and Y. Yang, Temporal Dependency based Checkpoint Selection for Dynamic Verification of Temporal Constraints in Scientific Workflow Systems. ACM Transactions on Software Engineering and Methodology, to appear (accepted on June 17, 2009).

> Q. He, J. Yan, R. Kowalczyk, H. Jin, Y. Yang, Lifetime Service Level Agreement Management with Autonomous Agents for Services Provision. Information Sciences, Elsevier, 2009.

> K. Liu, J. Chen, Y. Yang and H. Jin, A Throughput Maximization Strategy for Scheduling Transaction Intensive Workflows on SwinDeW-G . Concurrency and Computation: Practice and Experience, Wiley, 2008.

> J. Chen and Y. Yang, Adaptive Selection of Necessary and Sufficient Checkpoints for Dynamic Verification of Temporal Constraints in Grid Workflow Systems. ACM Transactions on Autonomous and Adaptive Systems, June 2007.

18

Selected Recent Publications – Conference Papers

> X. Liu, J. Chen, Z. Wu, Z. Ni, D. Yuan, Y. Yang, Handling Recoverable Temporal Violations in Scientific Workflow Systems: A Workflow Rescheduling Based Strategy. Proc. of 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid2010), pages 534-537, Melbourne, Australia, May 2010.

> D. Yuan, Y. Yang, X. Liu and J. Chen, A Cost-Effective Strategy for Intermediate Data Storage in Scientific Cloud Workflow Systems. Proc. of 24th IEEE International Parallel & Distributed Processing Symposium (IPDPS2010), Atlanta, USA, Apr. 2010.

> Q. He, J. Yan, H. Jin, Y. Yang, ServiceTrust: Supporting Reputation-Oriented Service Selection. Proc. 7th International Conference on Service Oriented Computing (ICSoC2009), Lecture Notes in Computer Science, Vol. 5900, pages 269-284, Stockholm, Sweden, Nov. 2009.

> X. Liu, Y. Yang, J. Chen, Q. Wang and M. Li, Achieving On-Time Delivery: A Two-Stage Probabilistic Scheduling Strategy for Software Projects, Proc. of International Conference on Software Process (ICSP09), Lecture Notes in Computer Science, Vancouver, Canada, May 2009.

> X. Liu, J. Chen, K. Liu and Y. Yang, Forecasting Duration Intervals of Scientific Workflow Activities based on Time-Series Patterns, Proc. of 4th IEEE International Conference on e-Science (e-Science08), Indianapolis, USA, Dec. 2008.

> X. Liu, J. Chen and Y. Yang, A Probabilistic Strategy for Setting Temporal Constraints in Scientific Workflows, Proc. 6th International Conference on Business Process Management (BPM2008), Lecture Notes in Computer Science, Sept. 2008 Milan, Italy.

> J. Chen and Y. Yang, Temporal Dependency based Checkpoint Selection for Dynamic Verification of Fixed-time Constraints in Grid Workflow Systems, Proc. of 30th International Conference on Software Engineering (ICSE2008), Leipzig, Germany, May 2008.

19

Collaborated Results So Far> Journal (accepted/revising/submitted)

– X. Liu, Z. Ni, J. Chen and Y. Yang, A Probabilistic Strategy for Temporal Constraint Management in Scientific Workflow Systems. Concurrency and Computation: Practice and Experience, Wiley, to appear (accepted on Nov. 27, 2009). SCI: 1.791

– Z. Wu, X. Liu, Z. Ni, D. Yuan, Y. Yang, A Market-Oriented Hierarchical Scheduling Strategy in Cloud Workflow Systems, Journal of Supercomputing, submitted, decision around July 2010. SCI: 0.62

– X. Liu, Z. Ni, D. Yuan, Y. Jiang, J. Chen, Y. Yang, A Statistical Time-Series Pattern based Interval Forecasting Strategy for Activity Durations in Cloud Workflow Systems, Journal of Systems and Software, under revision. SCI:1.24

– X. LIU, Z. NI, Z. WU, D. YUAN, J. CHEN, Y. Yang, A Novel General Framework for Automatic and Cost-Effective Handling of Recoverable Temporal Violations in Scientific Workflow Systems, Journal of Systems and Software, submitted. SCI: 1.24

> Conference (accepted/submitted)

– X. Liu, J. Chen, Z. Wu, Z. Ni, D. Yuan, Y. Yang, Handling Recoverable Temporal Violations in Scientific Workflow Systems: A Workflow Rescheduling Based Strategy. Proc. of 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid2010), pages 534-537, Melbourne, Australia, May 2010.

– X. Liu, Z. Ni, Z. Wu, D. Yuan, J. Chen, Y. Yang, An Effective Framework of Light-Weight Handling for Three-Level Fine-Grained Recoverable Temporal Violations in Scientific Workflows, 16th IEEE International Conference on Parallel and Distributed Systems (ICPADS2010), Shanghai, China, Dec.7-11, 2010, submitted.

On Going Work

> Comparison of Five Representative Metaheuristics based Workflow Scheduling Algorithms in Handling Scientific Workflow Temporal Violations: (aiming for one A* Journal)

– GA, ACO, PSO, SA, GRAPS

– Min-Min, MCT (Simple Heuristics)

> Further improvement on ACO, PSO and other algorithms for workflow scheduling and rescheduling (aiming for 1 to 2 SCI Journals)

> Cloud Computing based Stock Exchange System (aiming for 1 SCI Journals)

– Instance intensive, Scalability, Security

Future Collaboration Topics – With Cloud Computing

> Knowledge Cloud

– Distributed Data Mining in Cloud Environment

> Map Reduce for Machine Learning

– Parallel and Distributed Computing for Implementing Machine Learning Algorithms for such as Clustering, Classification and Association Rule Mining (Google, Baidu)

> Cloud Privacy

– Privacy Preserving

CORE Ranking

> Conference Ranking

– A+ 6% (ICSE)

– A 27% (FSE, ASE, ICSP, eScience, BPM, ICPP, IPDPS)

– B 31%

> Journal Ranking

– A* 5% (TSE, TOSEM, TPDS, JPDC)

– A 15% (CCPE, FGCS)

> For more information about call-for-papers, conference ranking and statistics, you may visit my webpage: http://www.ict.swin.edu.au/personal/xliu/

23

Questions and Discussions

> Apply for PhD in Australia

> PhD Study in Australia

> Writing Academic Papers in English

> Any other things you want to know?

24

Structure of a Paper> Title> Abstract

> Key words> Introduction

> Related Work

> System Model & Problem Statement

> Methods / Solutions> Simulations / Experiments> Conclusion> Acknowledgement> References

25

Tips:> Read the latest papers previously published in the conference or

journals you want to submit: get to know the template, the style and etc.

> Cite the papers previously published in the conference or journals: get to know the PC Chair’s and PC member’s recent work.

> Structure is most important!

> Related work is really important! Not only introduce them, but also point out their pros and cons.

> Evaluation is really important!

> Do not use unfamiliar words! See what other people used

> Do not use complex sentences if not necessary! Short and simple is the best.

26

Some Photos

27

Some Useful Links> CS3: http://www.swin.edu.au/ict/research/cs3/> Prof. Yun Yang: http://www.ict.swin.edu.au/ictstaff/yyang> Dr. Jinjun Chen : http://www.swinflow.org/> CORE Ranking: http://www.core.edu.au/> Workflow System: http://wwwis.win.tue.nl/~wvdaalst/> Grid/Cloud Computing: http://www.gridbus.org/

28

The End, Thanks!

29