Workflow dependency analysis and its implications on distributed workflow systems

被引:0
|
作者
Kim, KH [1 ]
机构
[1] Kyonggi Univ, Dept Comp Sci, Paldal Ku, Suwon 442760, Kyonggido, South Korea
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The design and implementation of a workflow management system is typically a large and complex task. Decisions need to be made about the hardware and software platforms, the data structures, the algorithms, and the interconnection of various modules utilized by various users and administrators. These design decisions are further complicated by requirements such as scalability, flexibility, robustness, speed, and usability. In this paper I describe four types of workflow dependency analyses conceived to be helpful in the design of distributed workflow systems, and in the understanding of the spectrum of possibilities for large-scale, domain specific, and flexible distributed workflow architectures. That is, this paper analyzes four types of dependencies, such as data dependency, activity (control) dependency, role dependency, and actor dependency, in a workflow model based upon the information control net. Also, it describes the implications of the dependency analysis mechanisms on architecting an object-based distributed workflow system. In order to perform the dependency analysis, the abstraction (framework) is at first done on a workflow model to generate dependent relationships among data, activities, roles and actors, respectively. Next, based-upon the abstracted workflow model that is formally and graphically represented by four difference types of dependent nets, each of which is generated by its corresponding algorithm conceived in this paper, it is possible to define a series of advanced workflow models and architectures that are appropriately applicable for implementing a distributed workflow system. The main reason why the workflow dependency analysis should be meaningful and valuable work lies just on it.
引用
收藏
页码:677 / 682
页数:6
相关论文
共 50 条
  • [41] Key issues and experiences in development of distributed workflow management systems
    Li, HC
    Yang, Y
    Shi, ML
    WEB TECHNOLOGIES AND APPLICATIONS, 2003, 2642 : 507 - 512
  • [42] Flexible Distributed Workflow Management Systems Design Based on CORBA
    Li, Ya
    Wang, Hairui
    Tong, Xiong
    Zhang, Li
    MECHATRONICS AND APPLIED MECHANICS, PTS 1 AND 2, 2012, 157-158 : 839 - +
  • [43] Performance and availability assessment for the configuration of distributed workflow management systems
    Gillmann, M
    Weissenfels, J
    Weikum, G
    Kraiss, A
    ADVANCES IN DATABSE TECHNOLOGY-EDBT 2000, PROCEEDINGS, 2000, 1777 : 183 - 201
  • [44] Integrating Provenance Data from Distributed Workflow Systems with ProvManager
    Marinho, Anderson
    Murta, Leonardo
    Werner, Claudia
    Braganholo, Vanessa
    Ogasawara, Eduardo
    Serra da Cruz, Sergio Manuel
    Mattoso, Marta
    PROVENANCE AND ANNOTATION OF DATA AND PROCESSES, 2010, 6378 : 286 - +
  • [45] Timing constraint workflow nets for workflow analysis
    Li, JQ
    Fan, YS
    Zhou, MC
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2003, 33 (02): : 179 - 193
  • [46] Workflow ART: a framework for multidimensional workflow analysis
    Monakova, Ganna
    Leymann, Frank
    ENTERPRISE INFORMATION SYSTEMS, 2013, 7 (01) : 133 - 166
  • [47] SENSITIVITY ANALYSIS OF WORKFLOW SCHEDULING ON GRID SYSTEMS
    Lopez, Maria M.
    Heymann, Elisa
    Senar, Miquel A.
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2007, 8 (03): : 301 - 311
  • [48] Optimizing data regeneration and storage with data dependency for cloud scientific workflow systems
    Fan, Lei
    Zhou, Lin
    Wang, Meijuan
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 238
  • [49] Sensitivity analysis of workflow scheduling on grid systems
    Departament d' Arquitectura d' Ordinadors i Sistemes, Operatius Universitat Autònoma de Barcelona, Barcelona, Spain
    Scalable Comput. Pract. Exp., 2007, 3 (301-311):
  • [50] Advances in Workflow Systems
    Chung, Paul Wai Hing
    COMPUTATIONAL INTELLIGENCE IN INFORMATION SYSTEMS, 2015, 331 : 1 - 9