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Coastal communities are confronted with a growing incidence of climate-induced flooding, necessitating adaptation measures for resilience. In this paper, we introduce a framework that integrates an urban digital twin with a geospatial…
Cloud platforms' growing energy demand and carbon emissions are raising concern about their environmental sustainability. The current approach to enabling sustainable clouds focuses on improving energy-efficiency and purchasing carbon…
Digital twin technology has been regarded as a beneficial approach in supply chain development. Different from traditional digital twin (temporal dynamic), supply chain digital twin is a spatio-temporal dynamic system. This paper explains…
The potential of digital twin technology is yet to be fully realized due to its diversity and untapped potential. Digital twins enable systems' analysis, design, optimization, and evolution to be performed digitally or in conjunction with a…
The desired outcome for urban digital twins is an automatically generated detailed 3D model of a building from aerial imagery, footprints, LiDAR, or a fusion of these. Such 3D models have applications in architecture, civil engineering,…
Network Digital Twins represent a key technology in future networks, expected to provide the capability to perform accurate analysis and predictions about the behaviour of 6G mobile networks. However, despite the availability of several…
Verification and validation (V&V) of autonomous vehicles (AVs) typically requires exhaustive testing across a variety of operating environments and driving scenarios including rare, extreme, or hazardous situations that might be difficult…
As a bridge from virtuality to reality, Digital Twin has increased in popularity since proposed. Ideas have been proposed theoretical and practical for digital twins. From theoretical perspective, digital twin is fusion of data mapping…
Cloud workloads today are typically managed in a distributed environment and processed across geographically distributed data centers. Cloud service providers have been distributing data centers globally to reduce operating costs while also…
Considering the market's competitiveness and the complexity of organizations and projects, analyzing data is crucial to decision support on software development and project management processes. These practices are essential to increase…
Modern large-scale data centers are known for their engineering complexity, cooling, and oversubscription challenges. To mitigate these issues, this article proposes the implementation of community data centers that are closer to consumers…
Interactive data visualization is a major part of modern exploratory data analysis, with web-based technologies enabling a rich ecosystem of both specialized and general tools. However, current visualization tools often lack support for…
Digital twins are virtual representations of physical objects or systems used for the purpose of analysis, most often via computer simulations, in many engineering and scientific disciplines. Recently, this approach has been introduced to…
This paper aims to provide a comprehensive critical overview on how entities and their interactions in Complex Networked Systems (CNS) are modelled across disciplines as they approach their ultimate goal of creating a Digital Twin (DT) that…
Cloud computing has been attracting the attention of several researchers both in the academia and the industry as it provides many opportunities for organizations by offering a range of computing services. For cloud computing to become…
This paper presents a novel approach for computing resource management of edge servers in vehicular networks based on digital twins and artificial intelligence (AI). Specifically, we construct two-tier digital twins tailored for vehicular…
We propose a universal framework for a system of virtual accelerator controls (Twinac), a standard toolkit for research institutions to design, maintain, and use a real-time, end-to-end "digital twin" of their particle accelerator facility.…
We propose a digital twin approach to improve healthcare decision support systems with a combination of domain knowledge and data. Domain knowledge helps build decision thresholds that doctors can use to determine a risk or recommend a…
Data visualization and analytics are nowadays one of the corner-stones of Data Science, turning the abundance of Big Data being produced through modern systems into actionable knowledge. Indeed, the Big Data era has realized the…
CI/CD pipelines are central to DevOps practices, yet their growing complexity makes them increasingly difficult to interpret, analyze, and systematically evolve. Existing tooling primarily offers execution logs and static graph…