Grid-enabled Workflows for Industrial Product Design

This paper presents a generic approach for developing and using Grid-based workflow technology for enabling cross-organizational engineering applications. Using industrial product design examples from the automotive and aerospace industries we highlight the main requirements and challenges addressed by our approach and describe how it can be used for enabling interoperability between heterogeneous workflow engines

ADEPT2 - Next Generation Process Management Technology

If current process management systems shall be applied to a broad spectrum of applications, they will have to be significantly improved with respect to their technological capabilities. In particular, in dynamic environments it must be possible to quickly implement and deploy new processes, to enable ad-hoc modifications of single process instances at runtime (e.g., to add, delete or shift process steps), and to support process schema evolution with instance migration, i.e., to propagate process schema changes to already running instances. These requirements must be met without affecting process consistency and by preserving the robustness of the process management system. In this paper we describe how these challenges have been addressed and solved in the ADEPT2 Process Management System. Our overall vision is to provide a next generation process management technology which can be used in a variety of application domains

Integration of BPM systems

New technologies have emerged to support the global economy where for instance suppliers, manufactures and retailers are working together in order to minimise the cost and maximise efficiency. One of the technologies that has become a buzz word for many businesses is business process management or BPM. A business process comprises activities and tasks, the resources required to perform each task, and the business rules linking these activities and tasks. The tasks may be performed by human and/or machine actors. Workflow provides a way of describing the order of execution and the dependent relationships between the constituting activities of short or long running processes. Workflow allows businesses to capture not only the information but also the processes that transform the information - the process asset (Koulopoulos, T. M., 1995). Applications which involve automated, human-centric and collaborative processes across organisations are inherently different from one organisation to another. Even within the same organisation but over time, applications are adapted as ongoing change to the business processes is seen as the norm in today’s dynamic business environment. The major difference lies in the specifics of business processes which are changing rapidly in order to match the way in which businesses operate. In this chapter we introduce and discuss Business Process Management (BPM) with a focus on the integration of heterogeneous BPM systems across multiple organisations. We identify the problems and the main challenges not only with regards to technologies but also in the social and cultural context. We also discuss the issues that have arisen in our bid to find the solutions

HyperLoom possibilities for executing scientific workflows on the cloud

We have developed HyperLoom - a platform for defining and executing scientific workflows in large-scale HPC systems. The computational tasks in such workflows often have non-trivial dependency patterns, unknown execution time and unknown sizes of generated outputs. HyperLoom enables to efficiently execute the workflows respecting task requirements and cluster resources agnostically to the shape or size of the workflow. Although HPC infrastructures provide an unbeatable performance, they may be unavailable or too expensive especially for small to medium workloads. Moreover, for some workloads, due to HPCs not very flexible resource allocation policy, the system energy efficiency may not be optimal at some stages of the execution. In contrast, current public cloud providers such as Amazon, Google or Exoscale allow users a comfortable and elastic way of deploying, scaling and disposing a virtualized cluster of almost any size. In this paper, we describe HyperLoom virtualization and evaluate its performance in a virtualized environment using workflows of various shapes and sizes. Finally, we discuss the Hyperloom potential for its expansion to cloud environments.61140639

SciTokens: Capability-Based Secure Access to Remote Scientific Data

The management of security credentials (e.g., passwords, secret keys) for computational science workflows is a burden for scientists and information security officers. Problems with credentials (e.g., expiration, privilege mismatch) cause workflows to fail to fetch needed input data or store valuable scientific results, distracting scientists from their research by requiring them to diagnose the problems, re-run their computations, and wait longer for their results. In this paper, we introduce SciTokens, open source software to help scientists manage their security credentials more reliably and securely. We describe the SciTokens system architecture, design, and implementation addressing use cases from the Laser Interferometer Gravitational-Wave Observatory (LIGO) Scientific Collaboration and the Large Synoptic Survey Telescope (LSST) projects. We also present our integration with widely-used software that supports distributed scientific computing, including HTCondor, CVMFS, and XrootD. SciTokens uses IETF-standard OAuth tokens for capability-based secure access to remote scientific data. The access tokens convey the specific authorizations needed by the workflows, rather than general-purpose authentication impersonation credentials, to address the risks of scientific workflows running on distributed infrastructure including NSF resources (e.g., LIGO Data Grid, Open Science Grid, XSEDE) and public clouds (e.g., Amazon Web Services, Google Cloud, Microsoft Azure). By improving the interoperability and security of scientific workflows, SciTokens 1) enables use of distributed computing for scientific domains that require greater data protection and 2) enables use of more widely distributed computing resources by reducing the risk of credential abuse on remote systems.Comment: 8 pages, 6 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US