37 research outputs found
Discovering business process simulation models in the presence of multitasking and availability constraints
Business process simulation is a versatile technique for quantitative analysis of business
processes. A well-known limitation of process simulation is that the accuracy of the simulation
results is limited by the faithfulness of the process model and simulation parameters given as
input to the simulator. To tackle this limitation, various authors have proposed to discover
simulation models from process execution logs, so that the resulting simulation models more
closely match reality. However, existing techniques in this field make certain assumptions
about resource behavior that do not typically hold in practice, including: (i) that each resource
performs one task at a time; and (ii) that resources are continuously available (24/7). In reality,
resources may engage in multitasking behavior and they work only during certain periods
of the day or the week. This article proposes an approach to discover process simulation
models from execution logs in the presence of multitasking and availability constraints. To
account for multitasking, we adjust the processing times of tasks in such a way that executing
the multitasked tasks sequentially with the adjusted times is equivalent to executing them
concurrently with the original times. Meanwhile, to account for availability constraints, we
use an algorithm for discovering calendar expressions from collections of time-points to infer
resource timetables from an execution log. We then adjust the parameters of this algorithm
to maximize the similarity between the simulated log and the original one. We evaluate the
approach using real-life and synthetic datasets. The results show that the approach improves
the accuracy of simulation models discovered from execution logs both in the presence of
multitasking and availability constraintsEuropean Research Council PIX 834141Ministerio de Ciencia, Innovación y Universidades OPHELIA RTI2018-101204-B-C22Junta de Andalucía EKIPMENTPLUS (P18–FR–2895
Blockchain Support for Collaborative Business Processes
Blockchain technology provides basic building blocks to support the execution of collaborative business processes involving mutually untrusted parties in a decentralized environment. Several research proposals have demonstrated the feasibility of designing blockchain-based collaborative business processes using a high-level notation, such as the Business Process Model and Notation (BPMN), and thereon automatically generating the code artifacts required to execute these processes on a blockchain platform. In this paper, we present the conceptual foundations of model-driven approaches for blockchain-based collaborative process execution and we compare two concrete approaches, namely Caterpillar and Lorikeet
Blockchains for Business Process Management - Challenges and Opportunities
Blockchain technology promises a sizable potential for executing
inter-organizational business processes without requiring a central party
serving as a single point of trust (and failure). This paper analyzes its
impact on business process management (BPM). We structure the discussion using
two BPM frameworks, namely the six BPM core capabilities and the BPM lifecycle.
This paper provides research directions for investigating the application of
blockchain technology to BPM.Comment: Preprint for ACM TMI
La saga PERSEUS
Presentamos PERSEUS, un marco computacional que permite crear administradores de objetos persistentes a lamedida. Se pueden crear tres tipos de administradores: no confiables, confiables basados en puntos de verificación, y confiablesbasados en transacciones. Dichas configuraciones son posibles debido a la arquitectura y la recuperación multi-nivel utilizados enPERSEUS. Este método de recuperación permite separar la tolerancia de fallas del sistema del soporte a transacciones, los cualesgeneralmente son implementados de manera conjunta