Dynamic Workflow Management and Monitoring Using DDS

Author(s):  
Pan Pan ◽  
Abhishek Dubey ◽  
Luciano Piccoli
Author(s):  
Ling Liu ◽  
Calton Pu ◽  
Duncan Dubugras Ruiz

This chapter presents a framework for dynamic restructuring of long-running business processes. The framework is composed of the ActivityFlow specification language, a set of workflow restructuring operators, and a dynamic workflow management engine. The ActivityFlow specification language enables the flexible specification, composition, and coordination of workflow activities. There are three unique features of our framework design. First, it supports a collection of specification mechanisms, allowing workflow designers to use a uniform workflow specification interface to describe different types of workflows involved in their organizational processes. A main objective of this characteristic is to help increase the flexibility of workflow processes in accommodating changes. The ActivityFlow language also provides a set of activity modeling facilities, enabling workflow designers to describe the flow of work declaratively and incrementally, and allowing to reason about correctness and security of


2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986220
Author(s):  
Youngkuk Kim ◽  
Siwoon Son ◽  
Yang-Sae Moon

In this article, we address dynamic workflow management for sampling and filtering data streams in Apache Storm. As many sensors generate data streams continuously, we often use sampling to choose some representative data or filtering to remove unnecessary data. Apache Storm is a real-time distributed processing platform suitable for handling large data streams. Storm, however, must stop the entire work when it changes the input data structure or processing algorithm as it needs to modify, redistribute, and restart the programs. In addition, for effective data processing, we often use Storm with Kafka and databases, but it is difficult to use these platforms in an integrated manner. In this article, we derive the problems when applying sampling and filtering algorithms to Storm and propose a dynamic workflow management model that solves these problems. First, we present the concept of a plan consisting of input, processing, and output modules of a data stream. Second, we propose Storm Plan Manager, which can operate Storm, Kafka, and database as a single integrated system. Storm Plan Manager is an integrated workflow manager that dynamically controls sampling and filtering of data streams through plans. Third, as a key feature, Storm Plan Manager provides a Web client interface to visually create, execute, and monitor plans. In this article, we show the usefulness of the proposed Storm Plan Manager by presenting its design, implementation, and experimental results in order.


2013 ◽  
Vol 655-657 ◽  
pp. 1738-1741
Author(s):  
Qi Yin ◽  
Ji Hu

Workflow management technology is an important computer technology in enterprise business process management. At present, there was a few of Workflow Engine which supported BPEL4WS specification. Base on the current research case of workflow, the aim of our study bring a Workflow platform support BPEL4WS Specification.According to the analysis of the web service’s new features and issues, we look into the dynamic workflow based on web services from the angles of service-oriented. We introduce the basic concepts, elements , activity, fault handler and compensate mechanism of BPEL4WS.This paper presents a design schem of framework of a web service-based dynamic workflow engine.


2004 ◽  
Vol 46 (6) ◽  
pp. 423-431 ◽  
Author(s):  
Georgios John Fakas ◽  
Bill Karakostas

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