A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

GRIDCC: Real-time workflow system

The Grid is a concept which allows the sharing of resources between distributed communities, allowing each to progress towards potentially different goals. As adoption of the Grid increases so are the activities that people wish to conduct through it. The GRIDCC project is a European Union funded project addressing the issues of integrating instruments into the Grid. This increases the requirement of workflows and Quality of Service upon these workflows as many of these instruments have real-time requirements. In this paper we present the workflow management service within the GRIDCC project which is tasked with optimising the workflows and ensuring that they meet the pre-defined QoS requirements specified upon them

Usability of Scientific Workflow in Dynamically Changing Environment

Scientific workflow management systems are mainly data-flow oriented, which face several challenges due to the huge amount of data and the required computational capacity which cannot be predicted before enactment. Other problems may arise due to the dynamic access of the data storages or other data sources and the distributed nature of the scientific workflow computational infrastructures (cloud, cluster, grid, HPC), which status may change even during running of a single workflow instance. Many of these failures could be avoided with workflow management systems that provide provenance based dynamism and adaptivity to the unforeseen scenarios arising during enactment. In our work we summarize and categorize the failures that can arise in cloud environment during enactment and show the possibility of prediction and avoidance of failures with dynamic and provenance support

Tasks, cognitive agents, and KB-DSS in workflow and process management

The purpose of this paper is to propose a nonparametric interest rate term structure model and investigate its implications on term structure dynamics and prices of interest rate derivative securities. The nonparametric spot interest rate process is estimated from the observed short-term interest rates following a robust estimation procedure and the market price of interest rate risk is estimated as implied from the historical term structure data. That is, instead of imposing a priori restrictions on the model, data are allowed to speak for themselves, and at the same time the model retains a parsimonious structure and the computational tractability. The model is implemented using historical Canadian interest rate term structure data. The parametric models with closed form solutions for bond and bond option prices, namely the Vasicek (1977) and CIR (1985) models, are also estimated for comparison purpose. The empirical results not only provide strong evidence that the traditional spot interest rate models and market prices of interest rate risk are severely misspecified but also suggest that different model specifications have significant impact on term structure dynamics and prices of interest rate derivative securities.

An LTL Semantics of Business Workflows with Recovery

We describe a business workflow case study with abnormal behavior management (i.e. recovery) and demonstrate how temporal logics and model checking can provide a methodology to iteratively revise the design and obtain a correct-by construction system. To do so we define a formal semantics by giving a compilation of generic workflow patterns into LTL and we use the bound model checker Zot to prove specific properties and requirements validity. The working assumption is that such a lightweight approach would easily fit into processes that are already in place without the need for a radical change of procedures, tools and people's attitudes. The complexity of formalisms and invasiveness of methods have been demonstrated to be one of the major drawback and obstacle for deployment of formal engineering techniques into mundane projects

Diagnosis of Errors in Stalled Inter-Organizational Workflow Processes

Fault-tolerant inter-organizational workflow processes help participant organizations efficiently complete their business activities and operations without extended delays. The stalling of inter-organizational workflow processes is a common hurdle that causes organizations immense losses and operational difficulties. The complexity of software requirements, incapability of workflow systems to properly handle exceptions, and inadequate process modeling are the leading causes of errors in the workflow processes. The dissertation effort is essentially about diagnosing errors in stalled inter-organizational workflow processes. The goals and objectives of this dissertation were achieved by designing a fault-tolerant software architecture of workflow system’s components/modules (i.e., workflow process designer, workflow engine, workflow monitoring, workflow administrative panel, service integration, workflow client) relevant to exception handling and troubleshooting. The complexity and improper implementation of software requirements were handled by building a framework of guiding principles and the best practices for modeling and designing inter-organizational workflow processes. Theoretical and empirical/experimental research methodologies were used to find the root causes of errors in stalled workflow processes. Error detection and diagnosis are critical steps that can be further used to design a strategy to resolve the stalled processes. Diagnosis of errors in stalled workflow processes was in scope, but the resolution of stalled workflow process was out of the scope in this dissertation. The software architecture facilitated automatic and semi-automatic diagnostics of errors in stalled workflow processes from real-time and historical perspectives. The empirical/experimental study was justified by creating state-of-the-art inter-organizational workflow processes using an API-based workflow system, a low code workflow automation platform, a supported high-level programming language, and a storage system. The empirical/experimental measurements and dissertation goals were explained by collecting, analyzing, and interpreting the workflow data. The methodology was evaluated based on its ability to diagnose errors successfully (i.e., identifying the root cause) in stalled processes caused by web service failures in the inter-organizational workflow processes. Fourteen datasets were created to analyze, verify, and validate hypotheses and the software architecture. Amongst fourteen datasets, seven datasets were created for end-to-end IOWF process scenarios, including IOWF web service consumption, and seven datasets were for IOWF web service alone. The results of data analysis strongly supported and validated the software architecture and hypotheses. The guiding principles and the best practices of workflow process modeling and designing conclude opportunities to prevent processes from getting stalled. The outcome of the dissertation, i.e., diagnosis of errors in stalled inter-organization processes, can be utilized to resolve these stalled processes