Academic literature on the topic 'Temporal Workflow'

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Journal articles on the topic "Temporal Workflow"

1

Plesniewicz, Gerald, and Baurzhan Karabekov. "Specifying temporal knowledge for workflows ontologies." Open Computer Science 6, no. 1 (2016): 226–31. http://dx.doi.org/10.1515/comp-2016-0020.

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AbstractA workflow is an automation of a process, in which participants (people or programs) are involved in activities for solving a set of tasks according to certain rules and constraints in order to attain a common goal. The concept of workflow appeared in business informatics. Currently the workflow techniques are used in many other fields such as medical informatics, bioinformatics, automation of scientific research, computer-aided design and manufacturing, etc. An ontology is a formal description (in terms of concepts, entities, their properties and relationships) of knowledge for solving a given class of problems. In particular, ontologies can be used in problems related to workflows. In this paper, we introduce a formalism that extends the language of the interval Allen’s logic, and show how this formalism can be applied to specify temporal knowledge in ontologies for workflows. For the extended Allen’s logic, we construct a deduction system based on the analytic tableaux method. We also show (by examples) how to apply the deduction method to query answering over ontologies written in the extended Allen’s logic.
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2

Wu, Na, Decheng Zuo, and Zhan Zhang. "Dynamic Fault-Tolerant Workflow Scheduling with Hybrid Spatial-Temporal Re-Execution in Clouds." Information 10, no. 5 (2019): 169. http://dx.doi.org/10.3390/info10050169.

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Improving reliability is one of the major concerns of scientific workflow scheduling in clouds. The ever-growing computational complexity and data size of workflows present challenges to fault-tolerant workflow scheduling. Therefore, it is essential to design a cost-effective fault-tolerant scheduling approach for large-scale workflows. In this paper, we propose a dynamic fault-tolerant workflow scheduling (DFTWS) approach with hybrid spatial and temporal re-execution schemes. First, DFTWS calculates the time attributes of tasks and identifies the critical path of workflow in advance. Then, DFTWS assigns appropriate virtual machine (VM) for each task according to the task urgency and budget quota in the phase of initial resource allocation. Finally, DFTWS performs online scheduling, which makes real-time fault-tolerant decisions based on failure type and task criticality throughout workflow execution. The proposed algorithm is evaluated on real-world workflows. Furthermore, the factors that affect the performance of DFTWS are analyzed. The experimental results demonstrate that DFTWS achieves a trade-off between high reliability and low cost objectives in cloud computing environments.
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3

Chountas, Panagiotis, and Ilias Petrounias. "Temporal conflict in workflow schemas." Journal of Computational Methods in Sciences and Engineering 11, no. 4 (2011): 193–207. http://dx.doi.org/10.3233/jcm-2011-0365.

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4

Leong, Iok-Fai, Yain-Whar Si, and Robert P. Biuk-Aghai. "Critical Path Based Approach for Predicting Temporal Exceptions in Resource Constrained Concurrent Workflows." International Journal of Information Technology and Web Engineering 5, no. 3 (2010): 27–48. http://dx.doi.org/10.4018/jitwe.2010070102.

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Departmental workflows within a digital business ecosystem are often executed concurrently and are required to share a limited number of resources. However, unexpected events from the business environment and delays in activities can cause temporal exceptions in these workflows. Predicting temporal exceptions is a complex task, since a workflow can be implemented with various types of control flow patterns. In this paper, the authors describe a critical path based approach for predicting temporal exceptions in concurrent workflows, which are required to share limited resources. This approach allows predicting temporal exceptions in multiple attempts while workflows are being executed.
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5

Deng, Ning, Xiao Dong Zhu, Yuan Ning Liu, Yan Pu Li, and Ying Chen. "Time Management Model of Workflow Based on Time Axis." Applied Mechanics and Materials 442 (October 2013): 458–65. http://dx.doi.org/10.4028/www.scientific.net/amm.442.458.

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The goal of workflow system is to guarantee that the right activities are executed and completed within the correct and ideal time periods via automation, moreover, in order to help a company to be sufficiently competitive, the workflow system it adopts should be able to ensure activities are carried out to the maximum extent as possible and to manage several workflow instances at the same time. Hence, sufficient consideration of temporal constraints and efficiency should be taken into the design process of workflow system. This paper proposes a model of workflow control based on time axis which is able to ensure one or more workflows to advance in correct time period efficiently and precisely.
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6

Kafeza, Eleanna. "Advanced Temporal Constraints for Business Processes Modelling and Execution." International Journal of Systems and Service-Oriented Engineering 8, no. 4 (2018): 1–25. http://dx.doi.org/10.4018/ijssoe.2018100101.

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In several applications like healthcare, time in workflow execution is critical. Several control and data dependencies arise that must be specified, validated as conflict free, and maintained during workflow execution. The author models these kinds of dependencies as constraints that impose temporal restrictions on the relative order of execution of the activities. Hence, a finer granularity of activity execution with respect to time is introduced. The author incorporates a subset of interval algebra in the workflow specification model and the author proposes the T-WfMc specification model. The author examines the consistency issues that arise, and the author proposes different correctness criteria.
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7

YU, Yang, Yong TANG, Mao-Lin PAN, Ting-Ting ZHENG, and Jian-Bin MAI. "Temporal Workflow Process Model and Its Soundness Verification." Journal of Software 21, no. 6 (2010): 1233–53. http://dx.doi.org/10.3724/sp.j.1001.2010.03608.

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8

Zhao, J. Leon, and Edward A. Stohr. "Temporal workflow management in a claim handling system." ACM SIGSOFT Software Engineering Notes 24, no. 2 (1999): 187–95. http://dx.doi.org/10.1145/295666.295687.

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9

Liu, Xiao, Dingxian Wang, Dong Yuan, Futian Wang, and Yun Yang. "Workflow temporal verification for monitoring parallel business processes." Journal of Software: Evolution and Process 28, no. 4 (2016): 286–302. http://dx.doi.org/10.1002/smr.1761.

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10

Powers, Christina M., Karmann A. Mills, Stephanie A. Morris, et al. "Nanocuration workflows: Establishing best practices for identifying, inputting, and sharing data to inform decisions on nanomaterials." Beilstein Journal of Nanotechnology 6 (September 4, 2015): 1860–71. http://dx.doi.org/10.3762/bjnano.6.189.

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There is a critical opportunity in the field of nanoscience to compare and integrate information across diverse fields of study through informatics (i.e., nanoinformatics). This paper is one in a series of articles on the data curation process in nanoinformatics (nanocuration). Other articles in this series discuss key aspects of nanocuration (temporal metadata, data completeness, database integration), while the focus of this article is on the nanocuration workflow, or the process of identifying, inputting, and reviewing nanomaterial data in a data repository. In particular, the article discusses: 1) the rationale and importance of a defined workflow in nanocuration, 2) the influence of organizational goals or purpose on the workflow, 3) established workflow practices in other fields, 4) current workflow practices in nanocuration, 5) key challenges for workflows in emerging fields like nanomaterials, 6) examples to make these challenges more tangible, and 7) recommendations to address the identified challenges. Throughout the article, there is an emphasis on illustrating key concepts and current practices in the field. Data on current practices in the field are from a group of stakeholders active in nanocuration. In general, the development of workflows for nanocuration is nascent, with few individuals formally trained in data curation or utilizing available nanocuration resources (e.g., ISA-TAB-Nano). Additional emphasis on the potential benefits of cultivating nanomaterial data via nanocuration processes (e.g., capability to analyze data from across research groups) and providing nanocuration resources (e.g., training) will likely prove crucial for the wider application of nanocuration workflows in the scientific community.
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