Business Process Management

Information System is one of the key domain in which lot of research has been done in the past few years. Applying Information systems to heterogeneous and distributed environments is one of the current research areas. Business Process Management Systems is the information systems which deal with the administration of tasks in the business processes, organizational structures, or in the related context. The Workflow Management system, the early idea of BPM, controls the workflow in an organization, data transfer, and integration of legacy information systems with existing programs and program modules, delegation of business tasks. Offering task management services especially modeling of business processes and underlying organizations, BPM serves it meaning and incorporates the WFM system. BPM supporting the use of knowledge concerning the awareness/unawareness of integrated software, and analysis of processes and organizational structure in terms of verification, modification, evaluation are key management in BPM syste

A Dynamic Workflow Simulation Platform

International audienceAbstract--In numeric optimization algorithms errors at application level considerably affect the performance of their execution on distributed infrastructures. Hours of execution can be lost only due to bad parameter configurations. Though current grid workflow systems have facilitated the deployment of complex scientific applications on distributed environments, the error handling mechanisms remain mostly those provided by the middleware. In this paper, we propose a collaborative platform for the execution of scientific experiments in which we integrate a new approach for treating application errors, using the dynamicity and exception handling mechanisms of the YAWL workflow management system. Thus, application errors are correctly detected and appropriate handling procedures are triggered in order to save as much as possible of the work already executed

Supporting Quality of Service in Scientific Workflows

While workflow management systems have been utilized in enterprises to support businesses for almost two decades, the use of workflows in scientific environments was fairly uncommon until recently. Nowadays, scientists use workflow systems to conduct scientific experiments, simulations, and distributed computations. However, most scientific workflow management systems have not been built using existing workflow technology; rather they have been designed and developed from scratch. Due to the lack of generality of early scientific workflow systems, many domain-specific workflow systems have been developed. Generally speaking, those domain-specific approaches lack common acceptance and tool support and offer lower robustness compared to business workflow systems. In this thesis, the use of the industry standard BPEL, a workflow language for modeling business processes, is proposed for the modeling and the execution of scientific workflows. Due to the widespread use of BPEL in enterprises, a number of stable and mature software products exist. The language is expressive (Turingcomplete) and not restricted to specific applications. BPEL is well suited for the modeling of scientific workflows, but existing implementations of the standard lack important features that are necessary for the execution of scientific workflows. This work presents components that extend an existing implementation of the BPEL standard and eliminate the identified weaknesses. The components thus provide the technical basis for use of BPEL in academia. The particular focus is on so-called non-functional (Quality of Service) requirements. These requirements include scalability, reliability (fault tolerance), data security, and cost (of executing a workflow). From a technical perspective, the workflow system must be able to interface with the middleware systems that are commonly used by the scientific workflow community to allow access to heterogeneous, distributed resources (especially Grid and Cloud resources). The major components cover exactly these requirements: Cloud Resource Provisioner Scalability of the workflow system is achieved by automatically adding additional (Cloud) resources to the workflow system’s resource pool when the workflow system is heavily loaded. Fault Tolerance Module High reliability is achieved via continuous monitoring of workflow execution and corrective interventions, such as re-execution of a failed workflow step or replacement of the faulty resource. Cost Aware Data Flow Aware Scheduler The majority of scientific workflow systems only take the performance and utilization of resources for the execution of workflow steps into account when making scheduling decisions. The presented workflow system goes beyond that. By defining preference values for the weighting of costs and the anticipated workflow execution time, workflow users may influence the resource selection process. The developed multiobjective scheduling algorithm respects the defined weighting and makes both efficient and advantageous decisions using a heuristic approach. Security Extensions Because it supports various encryption, signature and authentication mechanisms (e.g., Grid Security Infrastructure), the workflow system guarantees data security in the transfer of workflow data. Furthermore, this work identifies the need to equip workflow developers with workflow modeling tools that can be used intuitively. This dissertation presents two modeling tools that support users with different needs. The first tool, DAVO (domain-adaptable, Visual BPEL Orchestrator), operates at a low level of abstraction and allows users with knowledge of BPEL to use the full extent of the language. DAVO is a software that offers extensibility and customizability for different application domains. These features are used in the implementation of the second tool, SimpleBPEL Composer. SimpleBPEL is aimed at users with little or no background in computer science and allows for quick and intuitive development of BPEL workflows based on predefined components

Scientific Workflow Integration For Services Computing

In recent years, significant scientific advances are increasingly achieved through complex scientific processes. As the exponential growth in computing technologies and scientific data, a scientific workflow may comprise a large number of heterogeneous scientific services and applications, provided by different organizations. These services, applications, and their associated data are usually distributed across heterogeneous computing environments. The integration and management of such scientific workflows are pushing the limits of current workflow technology. This dissertation presents an integrated solution to composing, scheduling, executing and developing scientific workflows and scientific workflow management systems. To provide a foundation for workflow composition, scheduling, execution and management, we propose the first reference architecture for scientific workflow management systems. The reference architecture not only provides a high-level organization of subsystems and their interactions in a workflow system, but also provides a basis for comparison between different systems and a guidance for the architectural design of an SWFMS in a specific scientific domain. To integrate heterogeneous services and applications and enable them composed to workflows, we propose a task template model which not only provides an appropriate abstraction of heterogeneous services and applications, but also encapsulates the composition and mapping of shims and functional task components within a task interface. Our proposed task specification language (TSL) not only integrates heterogeneous services and applications into uniform workflow tasks, but also provides a solution to address both TYPE-I and TYPE-II shimming problems in composing scientific workflows. To schedule scientific workflows in emerging services computing environments, we propose two workflow scheduling algorithms, the SHEFT algorithm and the SCPOR algorithm, to prioritize tasks in a workflow, map tasks onto suitable resources and order the execution of tasks on the assigned resources, so that the workflow makespan can be minimized. Our extensive experiments have shown that our proposed algorithms not only outperform other algorithms for large-scale, data-intensive and compute intensive workflows, but also allow the assigned resources elastically change on demand of the size of workflows. To execute workflows on distributed computing environments, we propose a task run model to model the run-time behaviors of tasks. The proposed task run description language (TRDL) enables the execution of task instances constructed from heterogeneous services and applications. We also develop an SOA based task management subsystem to manage all task templates, task instances and task runs for the invocation and execution of various heterogeneous task components. Finally, our developed SOA based workflow management system, the VIEW system, and a VIEW based workflow application system, the FiberFlow system, validate our architectures, models, languages, and algorithms