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Data processing systems are increasingly deployed in the cloud. While monolithic systems run fully on virtual servers, recent systems embrace cloud infrastructure and utilize the disaggregation of compute and storage to scale them…
Many large enterprises that operate highly governed and complex ICT environments have no efficient and effective way to support their Data and AI teams in rapidly spinning up and tearing down self-service data and compute infrastructure, to…
Serverless computing is an emerging cloud computing paradigm, being adopted to develop a wide range of software applications. It allows developers to focus on the application logic in the granularity of function, thereby freeing developers…
As cloud computing is increasingly transforming the information technology landscape, organizations and businesses are exhibiting strong interest in Software-as-a-Service (SaaS) offerings that can help them increase business agility and…
Function-as-a-Service (FaaS) is at the core of serverless computing, enabling developers to easily deploy applications without managing computing resources. With an Infrastructure-as-Code (IaC) approach, frameworks like the Serverless…
This note aims to provide a systematic investigation of direct data-driven control, enriching the existing literature not by adding another isolated result, but rather by offering a unifying, versatile, and broad framework that enables the…
Serverless computing is becoming widely adopted among cloud providers, thus making increasingly popular the Function-as-a-Service (FaaS) programming model, where the developers realize services by packaging sequences of stateless function…
Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane application programming interfaces (APIs) which may be leveraged by user-defined software-defined networking…
The cloud computing platform gives people the opportunity for sharing resources, services and information among the people of the whole world. In private cloud system, information is shared among the persons who are in that cloud. For this,…
Developing an error-free spreadsheet has been a problem since the beginning of end-user computing. In this paper, we present a methodology that separates the modeling from the implementation. Using proven techniques from Information Systems…
The field of web and mobile software frameworks is relatively mature, with a large variety of tools in different languages that facilitate traditional app development where data in a relational database is displayed and modified. Our…
Configuring and evolving dashboards in complex and large-scale Systems-of-Systems (SoS) can be an expensive and cumbersome task due to the many Key Performance Indicators (KPIs) that are usually collected and have to be arranged in a number…
Open Source Software (OSS) development challenges traditional software engineering practices. In particular, OSS projects are managed by a large number of volunteers, working freely on the tasks they choose to undertake. OSS projects also…
Cloud computing has been emerged in the last decade to enable utility-based computing resource management without purchasing hardware equipment. Cloud providers run multiple data centers in various locations to manage and provision the…
This paper tries to reduce the effort of learning, deploying, and integrating several frameworks for the development of e-Science applications that combine simulations with High-Performance Data Analytics (HPDA). We propose a way to extend…
With the emergence of large-scale data-intensive high-performance applications, new I/O challenges appear in the efficient management of petabytes of information in High-Performance Computing (HPC) environments. Data management environments…
In this paper, the new information system development methodology will be proposed. This methodology will enable the whole data model to be built and adjusted at the run time, without rebuilding the application. This will make the user much…
Cloud-native applications have significantly advanced the development and scalability of online services through the use of microservices and modular architectures. However, achieving adaptability, resilience, and efficient performance…
Data-driven engineering refers to systematic data collection and processing using machine learning to improve engineering systems. Currently, the implementation of data-driven engineering relies on fundamental data science and software…
Microservices have become a popular architectural style for data-driven applications, given their ability to functionally decompose an application into small and autonomous services to achieve scalability, strong isolation, and…