The International Journal of eScience

Computing infrastructures and systems are rapidly developing and so are novel ways to map, control and execute scientific applications which become more and more complex and collaborative.
Computational and storage capabilities, databases, sensors, and people need true collaborative tools. Over the last years there has been a real explosion of new theory and technological progress supporting a better understanding of these wide-area, fully distributed sensing and computing systems. Big Data in all its guises require novel methods and infrastructures to register, analyze and distill meaning.

FGCS aims to lead the way in advances in distributed systems, collaborative environments, high performance and high performance computing, Big Data on such infrastructures as grids, clouds and the Internet of Things (IoT).

The Aims and Scope of FGCS cover new developments in:

[1] Applications and application support:

    Novel applications for novel e-infrastructures
    Complex workflow applications
    Big Data registration, processing and analyses
    Problem solving environments and virtual laboratories
    Semantic and knowledge based systems
    Collaborative infrastructures and virtual organizations
    Methods for high performance and high throughput computing
    Urgent computing
    Scientific, industrial, social and educational implications
    Education

[2] Methods and tools:

    Tools for infrastructure development and monitoring
    Distributed dynamic resource management and scheduling
    Information management
    Protocols and emerging standards
    Methods and tools for internet computing
    Security aspects

[3] Theory:

    Process specification;
    Program and algorithm design
    Theoretical aspects of large scale communication and computation
    Scaling and performance theory
    Protocols and their verification

Special Issue on Generative AI in Cybersecurity
Submission Date: 2025-05-15

Motivation and Scope

The world of cybersecurity is changing very rapidly, and the integration of Generative Artificial Intelligence (GenAI) represents a major transition in defense systems as well as attack tactics. Over the last decade, AI developments, especially through chatbots such as ChatGPT, Gemini, and DALL-E, have permeated several sectors, enhancing efficiency in operations and availing innovative approaches. This transformative technology is now at the center stage of cybersecurity by offering unprecedented possibilities and new challenges. Generative AI’s power transcends traditional use cases, fortifying defenses but also creating fresh angles for cyber threats. This special issue intends to examine the multifaceted influence of GenAI on cybersecurity by providing a comprehensive understanding of its potential to transform threat detection, mitigation, and response strategies. In particular, we are looking for ground-breaking studies that address topics including vulnerability assessment, automated hacking, ransomware and malware generation, as well as automation in cyber-defense mechanisms. There is also a need for papers examining the ethical concerns surrounding the use of GenAI within the cybersecurity landscape, hence promoting a balanced approach toward this potent tool.

The topics of Interest Include, but are not limited to:

    Vulnerability Assessment: Enhancing detection and assessment methodologies with GenAI.
    Social Engineering and Phishing Attacks: Crafting sophisticated social engineering attacks and developing prevention strategies.
    Automated Hacking and Attack Payload Generation: Automating hacking processes and generating complex attack payloads.
    Ransomware and Malware Code Generation: Creating and detecting advanced malicious software.
    Polymorphic Malware Generation: Generating and neutralizing dynamic, AI-generated threats.
    Cyberdefense Automation: Automating and enhancing defense mechanisms through AI integration.
    Cybersecurity Reporting and Threat Intelligence: Leveraging AI for advanced threat intelligence and proactive defense.
    Secure Code Generation and Detection: Employing AI for secure code generation and vulnerability detection.
    Identification of Cyber Attacks: Real-time attack identification and response using AI.
    Developing Ethical Guidelines: Establishing ethical norms for AI deployment in cybersecurity.
    Enhancing Cybersecurity Technologies: Augmenting existing tools and methodologies with AI.
    Incident Response Guidance: Utilizing AI in incident response and management.
    Malware Detection: Advancing detection techniques with AI.
    Social, Legal, and Ethical Implications of Generative AI: Comprehensive analysis of societal impacts and ethical considerations.

Guest Editors

S. Leili Mirtaheri
University of Calabria, Italy
leili.mirtaheri@dimes.unical.it

Andrea Pugliese
University of Calabria, Italy
andrea.pugliese@unical.it

Valerio Pascucci
University of Utah, United States of America
pascucci@acm.org

Important Dates

Submission portal opens: November 1, 2024
Deadline for paper submission: May 15, 2025
Latest acceptance deadline for all papers: September 15, 2025

Special Issue on Novel Applications and Techniques for Information Security
Submission Date: 2025-05-15

Motivation and Scope

We focus on the advances in two critical areas in security: insider threat detection and secure quantum computing. Insider threats require advanced detection strategies, while quantum computing demands new solutions and cloud security.

This special issue focuses on two key challenges: i) Insider Threat Detection; ii) Secure Quantum Computing. It will also feature selected papers from the 2024 International Conference on Applications and Techniques in Information Security. With quantum computing on the rise, it brings both opportunities and security risks. Researchers will showcase new cryptographic techniques and hardware solutions to protect against these emerging threats. By sharing cutting-edge research, this issue aims to improve understanding, offer practical solutions, and encourage knowledge sharing to help build stronger, more secure systems.

Guest Editors

Shiva Raj Pokhrel
Deakin University, Australia
shiva.pokhrel@deakin.edu.au

Gang Li
Deakin University, Australia
Gang.li@deakin.edu.au

V S Shankar Sriram
SASTRA Deemed University, India
shankar.sriram@sastra.edu

Important Dates

Submission portal opens: January 15, 2025
Deadline for paper submission: May 15, 2025
Latest acceptance deadline for all papers: August 15, 2025

Special Issue on Digital Twin Ecosystems Engineering & Applications
Submission Date: 2025-05-20

Motivation and Scope

Recent advances in the areas of the Internet of Things, Artificial Intelligence, and Big Data Analytics have accelerated the use of Digital Twins to engineer cyber-physical systems in a range of diverse application domains such as manufacturing, healthcare, farming, and smart cities.

Digital Twins are virtual replicas of physical entities supported by real-time sensory inputs, and advanced data processing to create and feed complex digital models. Continuous monitoring, analysis, prediction and simulation of the real-world counterparts are among the main capabilities of Digital Twins, enhancing decision-making, efficiency, and proactive maintenance. When applied to large-scale scenarios, where monolithic solutions are not feasible, integrated networks of Digital Twins are being proposed as a modelling tool to offer a comprehensive view of a domain leading to the concept of Digital Twin Ecosystems.

This Special Issue seeks to explore the latest trends, challenges, and opportunities in the engineering and application of Digital Twin Ecosystems. Designing and implementing these next-generation Digital Twin Ecosystems face engineering and societal challenges including scalability, interoperability, data security, privacy, and ethical issues. Discussing these challenges requires collaborative efforts from both the research community and industry professionals to ensure effective and responsible development and is at the core of this Special Issue.

Guest Editors

Sara Montagna
Department of Pure and Applied Science, University of Urbino Carlo Bo, Italy
sara.montagna@uniurb.it 

Samuele Burattini
Department of Computer Science and Engineering, University of Bologna, Italy
samuele.burattini@unibo.it 

Marco Picone
Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, Italy
marco.picone@unimore.it 

Important Dates

Submission portal opens: January 15th, 2025
Deadline for paper submission: May 20th, 2025
Latest acceptance deadline for all papers: February 15th, 2026

Special Issue on High-performance Computing Heterogeneous Systems and Subsystems
Submission Date: 2025-05-30

Motivation and Scope

High-performance computing (HPC) is at a pivotal juncture, characterized by significant advancements in computing technologies and architectural features. This special issue explores this dynamic field's latest advancements, challenges, and innovations. Heterogeneous HPC systems integrate diverse computational resources, including CPUs, GPUs, FPGAs, and other specialized accelerators, to deliver superior performance for various applications. To harness their potential fully, these systems require novel resource management, scheduling, programming models, and performance optimization approaches. Combining cutting-edge research and practical insights, this special issue provides a comprehensive overview of heterogeneous HPC systems' current state and future directions. It is a valuable resource for researchers, practitioners, and policymakers interested in leveraging heterogeneous computing to solve complex scientific, engineering, and data-intensive problems more efficiently and effectively.

The topics include but are not limited to:

1. Heterogeneous Programming Models and Runtime Systems:

    Models, parallel resource management, and automated parallelization
    Algorithms, libraries, and frameworks for heterogeneous systems

2. Heterogeneous Architectures:

    Power/energy management, reliability, and non-von Neuman architectures
    Memory and interconnection designs
    Data allocation, caching, and disaggregated memory
    Consistency models, persistency, and failure-atomicity

3. Heterogeneous Resource Management:

    System and software designs for dynamic resources
    High-level programming, run-time techniques, and resource frameworks
    Scheduling algorithms, resource management, and I/O provisioning

4. Heterogeneity in Artificial Intelligence:

    AI/ML/DL predictive models and optimized systems for heterogeneous workflows and applications
    Tools and workflows for AI/ML/DL in scientific applications

Guest Editors

Sergio Iserte
Barcelona Supercomputing Center, Spain
sergio.iserte@bsc.es  

Pedro Valero-Lara
Oak Ridge National Laboratory, USA
valerolarap@ornl.gov 

Kevin A. Brown
Argonne National Laboratory, USA
kabrown@anl.gov 

Important Dates

Submission portal opens: October 01, 2024
Deadline for paper submission: May 30, 2025
Latest acceptance deadline for all papers: July 31, 2025

Special Issue on Cloud Continuum
Submission Date: 2025-08-30

Motivation and Scope

Cloud computing has become a common commodity with many different providers and solutions. Several new architectural models are being developed and applied to ensure scalability, quality of service, and resilience. The models focus both on the providers, optimizing the use of their infrastructure, and on the users' side, optimizing the response times and/or costs. This scenario is becoming more complex with the possibility of having computing power close to the users on edge/fog models. All this scenario can be seen as the Cloud Continuum.

There are already some conferences that have the Cloud Continuum in their call-for-papers. However, only some of them have explicitly focused on the applications. We aim to attract a broader range of papers, from software engineering to High-Performance Computing applications. All of them will be discussed in the Cloud Continuum scenario.

The following list includes some of the major topics for this special issue:

    Energy Efficiency
    AI-powered Services
    Security
    IoT Applications
    Architectural Models
    Serverless Computing
    Elasticity
    Storage Virtualization
    Sustainable Models
    Programming Models
    QoS for Applications
    Optimization and Performance Issues
    Communication Protocols
    Big Data
    High-Performance Computing Applications
    Innovative Cloud Applications and Experiences
    Availability and Reliability
    Microservices
    New Models (e.g., spot instances)
    Frameworks and APIs
    HPC as a Service

Guest Editors

Alfredo Goldman
University of São Paulo, Brazil
gold@ime.usp.br

Eduardo Guerra
University of Bolzano, Italy
eduardo.guerra@unibz.it

Jean Luca Bez
Lawrence Berkeley National Laboratory, USA
jlbez@lbl.gov

Important Dates;

Submission Portal Opens: April, 15th, 2025;
Deadline for paper submission: August, 30th 2025;
Latest acceptance deadline for all papers: February 15th, 2026.

Special Issue on Advanced Situational Awareness and Resilience for Hyperconnected Industrial Scenarios
Submission Date: 2025-09-01

Motivation and Scope:

New technological trends and their adaptation to different strategic sectors, especially those aimed at the industrial sector and their interconnected infrastructures, entail multiple types of risks, including those related to security, privacy, and safety. This makes situational awareness and related areas, such as advanced prediction and detection, a priority requirement when it comes to protecting the most critical resources relevant to the business model or between models. However, the effectiveness of situational awareness is only assured if defensive measures are accompanied with advanced preparedness, response, and recovery strategies, thus providing guarantees of resilience.

Significant research progresses, in line to situational awareness, have already shown the way to: (i) combat some of the mentioned problems, some of them against counterfeiting and advanced persistent threats, (ii) promote predictive maintenance and resilience, and (iii) implement Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI) methods to address not only cyberattacks on critical infrastructures, but also to mitigate adversarial AI attacks. But, overall, all these advances are still insufficient considering the heterogenous, hyper-interconnected and complex nature of many today’s critical infrastructures. The assumption of the new industrial paradigms (Industry 4.0/5.0) and the multiple factors that come into play in the protection of critical systems, in which it is necessary to safeguard operational performance, proactivity and coordination according to the NIS2 directive, become undoubtedly relevant when it comes to managing critical situations.

All the above leads to the innate need to consider and apply cutting-edge technologies to promote trustworthy industrial security, where the inclusion of disruptive techniques, methods and technologies become relevant factors to address the expected level of situational awareness and resilience. Therefore, this Special Issue (SI) aims to bring together cutting-edge results that address the specific challenges of all these topics and their implication in specific industrial environments. The aim is to promote research and progress in line with new technologies, as well as to learn about the most recent issues and advances in this application area with special attention to novelty and originality within the subject matter.

In particular, the topics of interest for this Special Issues includes but not limited to:

    Governance, plans, and automated security controls
    Dynamic risk management and automatic feedback
    Adversarial offense, modeling, and demonstrations
    Advanced attack prediction for advanced awareness and proactivity
    AI-enhanced attack detection and stealthy movements
    Mitigation of adversarial AI attacks on industrial & critical infrastructures
    Smart threat interpretation and projection for attack traceability
    Advanced attack response, playbooks, and mitigation
    Green prediction, detection, and response approaches for lightweight situational awareness
    Advanced recovery and feedback to the situational awareness
    Cyber threat intelligence and coordination
    Sharing data and trust management
    Auditing and accountability for situational awareness
    Intelligent and accurate feedback to situational awareness
    Privacy and anonymization techniques for situational awareness
    Lightweight protection to the situational awareness and implied technologies
    Dynamic preparation and coordination through simulations
    Automated training for (re-)skilling and knowledge in situational awareness
    Industrial use cases with practical demonstrations for situational awareness and resilience: energy, health, transportation, manufacturing, etc.

Guest Editors:

Cristina Alcaraz

Cristina Alcaraz
University of Malaga, Malaga, Spain
alcaraz@uma.es; contact person for further information

Fabio Martinelli

Fabio Martinelli
Italian National Research Council (CNR), Roma, Italy
fabio.martinelli@iit.cnr.it

Panagiotis Bountakas

Panagiotis Bountakas
Sphynx, Zug, Switzerland 
p.bountakas@sphynx.ch

Important Dates:

Submission portal opens: February 01,  2025
Deadline for paper submission: September 01, 2025
Latest acceptance deadline for all papers: December 31, 2025

Special Issue on Leveraging Cutting-Edge High Performance Computing for Large-Scale Applications
Submission Date: 2025-09-30

Motivation and Scope

High Performance Computing (HPC) recently entered into the exascale era, marking an important milestone of its history. High-end supercomputers and clusters with remarkable level of performance are now commonly available for standard and specific computational needs, thereby increasing the focus on HPC and related topics. Leveraging the potential of large-scale supercomputers is an HPC skillful task that requires in-depth knowledge on both hardware and software. Indeed, the architectural structure of cutting-edge HPC processors is rather complex, with each feature provided by a specialized mechanism, the processing overhead of which can turn out to be an efficiency bottleneck. This challenge becomes more pronounced as the potential processing power of the machine increases. For example, at the compute node level, processors with many cores might have a NUMA architecture, a deeper memory hierarchy and/or wide SIMD capabilities. At the interprocessor level, hardware support for data exchanges can also significantly increase running time. There is a wide range of applications that genuinely need a whooping computing speed, one of them being the training of large-scale AI models. The evolution of HPC appears closely tied to the growing demand for speed from such large-scale applications. As a result, the implementation of cutting-edge techniques should remain scalable on large-scale machines. Achieving this level of efficiency is challenging but highly sought after by HPC community, including end-users.

This special issue aims at addressing the aforementioned technical context and scientific challenges, thus expecting to gather insightful contributions on how to leverage the increasing potential of HPC systems for cutting-edge applications. We invited various types of submissions: research papers (fundamental and experimental), position papers, extended version of conference papers, and surveys. Papers are solicited on a broad range of topics including (but not limited to):

    Scalability with large-scale parallel machines (issues, limits, methods, applications)
    Efficiency with large clusters of accelerators (e.g. FPGAs, GPUs, AI accelerators)
    Parallel algorithms and scheduling for heterogeneous and/or hierarchical systems
    Fault-tolerance for large-scale HPC systems
    Models and tools for performance/energy evaluation on large-scale HPC systems
    Power consumption and carbon footprint of large-scale HPC solutions
    Applications that need cutting-edge HPC
    Combinatorial optimization from the exascale standpoint
    AI in the exascale era
    Large-scale Cloud systems
    Quantum computing (efficiency perspectives)
    Integrating Classical and Quantum Computing

Guest Editors

Claude

Claude TADONKI
Mines Paris, PSL University, Paris, France
claude.tadonki@minesparis.psl.eu

mencagli

Gabriele MENCAGLI
University of Pisa, Pisa, Italy
gabriele.mencagli@unipi.it

Gabriele

Leonel SOUSA
Instituto Superior T´ecnico, Universidade de Lisboa, Lisboa, Portugal
las@inesc-id.pt

Important Dates

Submission portal opens: April 14, 2025
Deadline for paper submission: September 30, 2025
Latest acceptance deadline for all papers: December 30, 2025