research-article

D2WORM: A Management Infrastructure for Distributed Data-centric Workflows

Authors:

Martin Jergler,

Mohammad Sadoghi,

Hans-Arno JacobsenAuthors Info & Claims

SIGMOD '15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

Pages 1427 - 1432

https://doi.org/10.1145/2723372.2735362

Published: 27 May 2015 Publication History

Abstract

Unlike traditional activity-flow-based models, data-centric workflows primarily focus on the data to drive a business. This enables the unification of operational management, concurrent process analytics, compliance with process or associated data constraints, and adaptability to changing environments. In this demonstration, we present D2Worm, a Distributed Data-centric Workflow Management system. D2Worm allows users to (1) graphically model data-centric workflows in a declarative fashion based on the Guard-Stage-Milestone (GSM) meta-model, (2) automatically compile the modelled workflow into several fine-granular workflow units (WFUs), and (3) deploy these WFUs on distributed infrastructures. A WFU is a system component that manages a subset of the workflow's data model and, at the same time, represents part of the global control flow by evaluating conditions over the data. WFUs communicate with each other over a publish/subscribe messaging infrastructure that allows the architecture to scale from a single node to dozens of machines distributed over different data-centers. In addition, D2Worm is able to (4) concurrently execute multiple workflow instances and monitor their behavior in real-time.

References

[1]

A. Adi and O. Etzion. Amit - The Situation Manager. VLDB Journal '04.

Digital Library

[2]

Amazon. Amazon's Corporate IT Migrates Business Process Management to the Amazon Web Services Cloud. https://media.amazonwebservices.com/AWS_Amazon_BPM_Migration.pdf, 2011.

[3]

S. Appel, S. Frischbier, T. Freudenreich, and A. Buchmann. Event Stream Processing Units in Business Processes. In BPM'13.

Digital Library

[4]

D. Calvanese, G. De Giacomo, and M. Montali. Foundations of Data-aware Process Analysis: A Database Theory Perspective. In PODS '13.

Digital Library

[5]

E. Damaggio, R. Hull, and R. Vaculín. On the equivalence of incremental and fixpoint semantics for business artifacts with Guard-Stage-Milestone lifecycles. Information Systems, 2013.

Digital Library

[6]

M. Dumas. On the convergence of data and process engineering. In ADBIS, 2011.

Digital Library

[7]

I. Elghandour and A. Aboulnaga. ReStore: Reusing Results of MapReduce Jobs. In VLDB'12.

Digital Library

[8]

S. Ganesan, Y. Yoon, and H. Jacobsen. Ni\ nos Take Five: The Management Infrastructure for Distributed Event-Driven Workflows. In DEBS'11.

Digital Library

[9]

Great Britain. Data Protection Act. 1998.

[10]

C. Houy, P. Fettke, P. Loos, W. Aalst, and J. Krogstie. Business Process Management in the Large. In BISE'11.

[11]

R. Hull and J. Su. NSF Workshop on Data-Centric Workflows (2009). http://dcw2009.cs.ucsb.edu/report.pdf.

[12]

H.-A. Jacobsen, A. K. Y. Cheung, G. Li, B. Maniymaran, V. Muthusamy, and R. S. Kazemzadeh. The PADRES Publish/Subscribe System. In Principles and Applications of Distributed Event-Based Systems. IGI Global, 2010.

[13]

B. Javadi, M. Tomko, and R. O. Sinnott. Decentralized Orchestration of Data-centric Workflows Using the Object Modeling System. In CCGRID'12.

Digital Library

[14]

V. Künzle and M. Reichert. Philharmonicflows: Towards a framework for object-aware process management. In Journal of Software Maintenance'11.

[15]

G. Li, V. Muthusamy, and H.-A. Jacobsen. A distributed service-oriented architecture for business process execution. TWEB'10.

Digital Library

[16]

A. Nigam and N. S. Caswell. Business artifacts: An approach to operational specification. IBM Syst. J.'03.

Digital Library

[17]

E. S. Ogasawara, D. de Oliveira, P. Valduriez, J. Dias, F. Porto, and M. Mattoso. An Algebraic Approach for Data-Centric Scientific Workflows. PVLDB'11.

[18]

E. S. Ogasawara, J. Dias, V. Silva, F. S. Chirigati, D. de Oliveira, F. Porto, P. Valduriez, and M. Mattoso. Chiron: a parallel engine for algebraic scientific workflows. Concurrency and Computation: Practice and Experience, 2013.

[19]

OMG. Case Management Model and Notation (CMMN). bmi/09-09--23.

[20]

M. Sadoghi, M. Jergler, H.-A. Jacobsen, R. Vaculin, and R. Hull. Safe Distribution and Parallel Execution of Data-centric Workflows over the Publish/Subscribe Paradigm. Technical report, University of Toronto, 2012.

[21]

K. D. Swenson. Mastering the Unpredictable. Meghan-Kiffer Press, 2010.

[22]

D. Wodtke, J. Weißenfels, G. Weikum, and A. K. Dittrich. The Mentor Project: Steps Toward Enterprise-Wide Workflow Management. ICDE '96.

Digital Library

Cited By

Li YDeng GBai CYang JWang GZhang HBai JYuan HXu MWang S(2023)Demystifying the QoS and QoE of Edge-hosted Video Streaming Applications in the Wild with SNESetProceedings of the ACM on Management of Data10.1145/36267231:4(1-29)Online publication date: 12-Dec-2023
https://dl.acm.org/doi/10.1145/3626723
Song WJacobsen H(2018)Static and Dynamic Process ChangeIEEE Transactions on Services Computing10.1109/TSC.2016.253602511:1(215-231)Online publication date: 1-Jan-2018
https://doi.org/10.1109/TSC.2016.2536025
Jergler MZhang KJacobsen H(2018)Multi-Client Transactions in Distributed Publish/Subscribe Systems2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2018.00022(120-131)Online publication date: Jul-2018
https://doi.org/10.1109/ICDCS.2018.00022
Show More Cited By

Recommendations

Geo-Distribution of Flexible Business Processes over Publish/Subscribe Paradigm
Middleware '16: Proceedings of the 17th International Middleware Conference

An increasing amount of business processes are inherently knowledge-intense and require ad-hoc decision making. Flexible modeling approaches such as the Case Management Model and Notation (CMMN) were designed to support such scenarios. At the same time, ...
Towards highly parallel event processing through reconfigurable hardware
DaMoN '11: Proceedings of the Seventh International Workshop on Data Management on New Hardware

We present fpga-ToPSS (Toronto Publish/Subscribe System), an efficient event processing platform to support high-frequency and low-latency event matching. fpga-ToPSS is built over reconfigurable hardware---FPGAs---to achieve line-rate processing by ...
Towards an extensible efficient event processing kernel
PhD '12: Proceedings of the on SIGMOD/PODS 2012 PhD Symposium

The efficient processing of large collections of patterns (Boolean expressions, XPath queries, or continuous SQL queries) over data streams plays a central role in major data intensive applications ranging from user-centric processing and ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGMOD '15: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data

May 2015

2110 pages

ISBN:9781450327589

DOI:10.1145/2723372

General Chair:
Timos Sellis
RMIT University, Australia
,
Program Chairs:
Susan B. Davidson
University of Pennsylvania, USA
,
Zack Ives
University of Pennsylvania, USA

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGMOD: ACM Special Interest Group on Management of Data

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2015

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

SIGMOD/PODS'15

Sponsor:

SIGMOD

SIGMOD/PODS'15: International Conference on Management of Data

May 31 - June 4, 2015

Victoria, Melbourne, Australia

Acceptance Rates

SIGMOD '15 Paper Acceptance Rate 106 of 415 submissions, 26%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

8
Total Citations
View Citations
285
Total Downloads

Downloads (Last 12 months)7
Downloads (Last 6 weeks)2

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Li YDeng GBai CYang JWang GZhang HBai JYuan HXu MWang S(2023)Demystifying the QoS and QoE of Edge-hosted Video Streaming Applications in the Wild with SNESetProceedings of the ACM on Management of Data10.1145/36267231:4(1-29)Online publication date: 12-Dec-2023
https://dl.acm.org/doi/10.1145/3626723
Song WJacobsen H(2018)Static and Dynamic Process ChangeIEEE Transactions on Services Computing10.1109/TSC.2016.253602511:1(215-231)Online publication date: 1-Jan-2018
https://doi.org/10.1109/TSC.2016.2536025
Jergler MZhang KJacobsen H(2018)Multi-Client Transactions in Distributed Publish/Subscribe Systems2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS.2018.00022(120-131)Online publication date: Jul-2018
https://doi.org/10.1109/ICDCS.2018.00022
Hou SZhao SCheng BChen SCheng YChen J(2017)A Distributed Deployment Algorithm of Process Fragments With Uncertain Traffic MatrixIEEE Transactions on Network and Service Management10.1109/TNSM.2017.272886314:3(690-701)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1109/TNSM.2017.2728863
Andersen ASaus M(2017)Privacy preserving distributed computation of community health research dataProcedia Computer Science10.1016/j.procs.2017.08.319113(633-640)Online publication date: 2017
https://doi.org/10.1016/j.procs.2017.08.319
Jergler MSadoghi MJacobsen H(2016)Geo-Distribution of Flexible Business Processes over Publish/Subscribe ParadigmProceedings of the 17th International Middleware Conference10.1145/2988336.2988351(1-13)Online publication date: 28-Nov-2016
https://dl.acm.org/doi/10.1145/2988336.2988351
Jergler MJacobsen HSadoghi MHull RVaculin R(2016)Safe distribution and parallel execution of data-centric workflows over the publish/subscribe abstraction2016 IEEE 32nd International Conference on Data Engineering (ICDE)10.1109/ICDE.2016.7498393(1498-1499)Online publication date: May-2016
https://doi.org/10.1109/ICDE.2016.7498393
Zenmyo TIijima SFukuda I(2016)Managing a complicated workflow based on dataflow-based workflow scheduler2016 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2016.7840779(1658-1663)Online publication date: Dec-2016
https://doi.org/10.1109/BigData.2016.7840779

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten