21 papers · ranked by Valyu relevance
Théo Fagnoni, Bellinda Mesbah, Mahsun Altin, Paul Kingston
This paper introduces Opus, a novel framework for generating and optimizing Workflows tailored to complex Business Process Outsourcing (BPO) use cases, focusing on cost reduction and quality enhancement while adhering to established industry processes and operational constraints. Our approach generates executable…
Anastasios Gounaris
Business Process Model and Notation (BPMN) provides a standard for the design of business processes. It focuses on bridging the gap between the analysis and the technical perspectives, and aims to deliver process automation. The aim of this technical report is to complement this effort by transferring knowledge from…
Gaurav Kaushik, Sinisa Ivkovic, Janko Simonovic, Nebojsa Tijanic + 2 more
As biomedical data becomes increasingly easy to generate in large quantities, the methods used to analyze it have proliferated rapidly. However, for the insights gained from these analyses to be meaningful, the analysis methods themselves must be transparent and reproducible. To address this issue, numerous groups have…
Georgia Kougka, Anastasios Gounaris, Alkis Simitsis
Workflow technology is rapidly evolving and, rather than being limited to modeling the control flow in business processes, is becoming a key mechanism to perform advanced data management, such as big data analytics. This survey focuses on data-centric workflows (or workflows for data analytics or data flows), where a…
Min Cui, Yipeng Wang
Workflow scheduling in cloud computing is attracting increasing attention. Cloud computing can assign tasks to available virtual machine resources in cloud data centers according to scheduling strategies, providing a powerful computing platform for the execution of workflow tasks. However, developing effective workflow…
Samar Awad, Marwa Gamal, Khaled Abd El Salam, Rehab F. Abdel-Kader
With the rapid advancement of fog-cloud computing, task offloading and workflow scheduling have become pivotal in determining system performance and cost efficiency. To address the inherent complexity of this heterogeneous environment, a novel hybrid optimization strategy is introduced, integrating the Improved…
Sonia Yassa, Rachid Chelouah, Hubert Kadima, Bertrand Granado
We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service)…
Dineshan Subramoney, Clement N. Nyirenda
— This work presents a comparative evaluation of four population-based optimization algorithms for workflow scheduling in cloud-fog environments. These algorithms are as follows: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE) and GA-PSO. This work also provides the motivational…
Kevin Kang, Jinwen Wo, Jon Jiang, Zhong Wang
We propose Adaptive Container Service (ACS), a new paradigm for deploying bioinformatics workflows in cloud computing environments. By encapsulating the entire workflow within a single virtual container, combined with automatic workflow checkpointing and dynamic migration to appropriately scaled containers, ACS-based…
Young-Jin Kim, Garam Kim, Sangil Kim, Dawoon Jung + 1 more
This study aims to improve the efficiency of task switching in hospital laboratories. In a laboratory, several medical technicians perform multiple tasks. Technicians are not aware of the marginal amount of time it takes to switch between tasks, and this accumulation of lost minutes can cause the technician to worry…
Yuxiang Liu, Xinzhong Xia, Jingyang Zhang, Kun Wang + 11 more
'Mengmeng Wu' 'Jinchao Shi' 'Chao Ma' 'Ying Liu' 'Boyang Hu' 'Xinying Wang' 'Bo Wang' 'Ruzhi Wang' 'Bing Wang' 'Zeashan Hameed Khan'] This study presents a systematic approach to enhance the efficiency of monocrystalline silicon photovoltaic module assembly lines using advanced simulation modeling. The research focuses…
Amir Pandi, Christoph Diehl, Ali Yazdizadeh Kharrazi, Léon Faure + 10 more
The study, engineering and application of biological networks require practical and efficient approaches. Current optimization efforts of these systems are often limited by wet lab labor and cost, as well as the lack of convenient, easily adoptable computational tools. Aimed at democratization and standardization, we…
R. Nallakumar, K S Sruthi Priya
Cloud Computing is the latest blooming technology in the era of Computer Science and Information Technology domain. There is an enormous pool of data centres, which are termed as Clouds where the services and associated data are being deployed and users need a constant Internet connection to access them. One of the…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Peter Kraus, Edan Bainglass, Francisco F. Ramirez, Enea Svaluto-Ferro + 7 more
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We…
Augusto Morales, Tomas Robles, Ramon Alcarria, Edwin Cedeño
The execution of scientific workflows is gaining importance as more computing resources are available in the form of grid environments. The Publish/Subscribe paradigm offers well-proven solutions for sustaining distributed scenarios while maintaining the high level of task decoupling required by scientific workflows.…
Andrei-Alin Corodescu, Nikolay Nikolov, Akif Quddus Khan, Ahmet Soylu + 4 more
'Ahmet Soylu' 'Mihhail Matskin' 'Amir H. Payberah' 'Dumitru Roman' 'Haipeng Dai'] The emergence of the edge computing paradigm has shifted data processing from centralised infrastructures to heterogeneous and geographically distributed infrastructures. Therefore, data processing solutions must consider data locality to…
Samuel Lampa, Martin Dahlö, Jonathan Alvarsson, Ola Spjuth
The complex nature of biological data has driven the development of specialized software tools. Scientific workflow management systems simplify the assembly of such tools into pipelines and assist with job automation and aids reproducibility of analyses. Many contemporary workflow tools are specialized and not designed…
Aidan Slattery, Zhenghui Wen, Pauline Tenblad, Diego Pintossi + 3 more
The optimization, intensification, and scaling up of chemical processes are essential and time-consuming aspects of contemporary chemical manufacturing, necessitating expertise and precision due to their intricate and sensitive nature. However, these process development problems are often carried out independently and…
Alejandro F. Villaverde, Fabian Fröhlich, Daniel Weindl, Jan Hasenauer + 1 more
Mechanistic kinetic models usually contain unknown parameters, which need to be estimated by optimizing the fit of the model to experimental data. This task can be computationally challenging due to the presence of local optima and ill-conditioning. While a variety of optimization methods have been suggested to…