With the continuous development of the Internet, massive data is generated. In the real world, different individuals interact with each other and these connections constitute a series of different graphs, also called as information networks. In recent years, graph representation learning (embedding) has become a hot research topic. Most of the related researches are conducted on homogeneous information networks that contains same type of nodes and edges. However, the real-world systems are actually more complex. Therefore, the concept of heterogeneous information network (HIN) consisting of multiple types of nodes and edges is put forward.

HIN takes diverse node types and edge types into consideration and can comprehensively characterize the real scenarios. HIN has been promoted to a variety of applications, such as recommendation system. To better facilitate downstream tasks, heterogeneous information network embedding (HNE) is proposed, which aims to project graph data into low dimensional vectors in the embedding space where the topological information and semantics are preserved, which is an important research problem.

Due to the heterogeneity of HIN, it is inappropriate to directly use traditional methods designed for homogeneous graphs to embed HIN. In recent years, HNE problem has attracted more and more research interests, and it is definitely worth studying. Besides, the potential of modeling scenarios in different research fields into heterogeneous networks for specific tasks has not been fully mined. Therefore, this special issue will have important significance and far-reaching influence on the following aspects: 1) Introducing emerging research and development in the field of HIN. 2) Studying the HNE problem with different techniques. 3) Promoting HIN to different application scenarios to enable researchers to take advantage of the power of graph data mining techniques. 4) Exploring interests, seeking potential cooperation, and promoting the HIN with other related fields.

Topics of interest include, but are not limited to:

Shallow models for heterogeneous network embedding.
Deep neural network based heterogeneous network embedding.
Auto-encoder based heterogeneous network embedding.
Graph neural network based heterogeneous network embedding, including semi-supervised and self-supervised methods.
Pre-training on heterogeneous networks.
Dynamic heterogeneous network embedding.
Application-oriented heterogeneous network embedding, including recommendation, identification and so on.

Guest Editors

Weimin Li, Shanghai University, China. [email protected]

Lu Liu, University of Leicester, UK. [email protected]

Kevin I.-K. Wang, University of Auckland, New Zealand. [email protected]

Qun Jin, Waseda University, Japan. [email protected]

Important Dates

Submission portal opens: September 01, 2022

Deadline for paper submission: February 01, 2023

Latest acceptance deadline for all papers: June 01, 2023

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from September 01, 2022. When submitting your manuscript please select the article type VSI: SI-HINEA.

All submissions deemed suitable by the editors to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production to be published in the special issue.

16 June 2022

Special Issue on Trust, Security, and Privacy in Metaverse

Motivation and Scope

The term Metaverse has been coined to further facilitate the digital transformation in every aspect of our physical lives. As a virtual digital world that maps and interacts with the real world, the Metaverse is a vast, unified, enduring, and shared domain. With the supported by extended reality (XR) technology, digital twins, blockchain technology, communication technology (5G/6G), artificial intelligence (AI), cloud computing, etc., the real world can be seamlessly connected to the digital world through a Metaverse immersive experience. Therefore, a lot of work and life will take place in the virtual world, greatly promoting information consumption. At present, the development of the Metaverse is still in the infancy stage, and there will be a huge space for the expansion of the industry related to the Metaverse. In the future, the Metaverse will give birth to a series of new technologies, new formats, and new models to promote the transformation of traditional industries. Despite the novel potentials which could be enabled by the Metaverse ecosystem, this also imposes new trust, security, and privacy challenges for Metaverses because attackers will likely collect users’ personal information or destroy the Metaverse system by interacting or attacking networks and hardware devices. Therefore, it needs to develop novel methodologies to tackle these challenges as soon as possible, rather than waiting for the future when problems are already entrenched in the ecosystem, which will have serious implications for the social acceptability and future development of the Metaverse. This special issue solicits original and high-quality works on recent advances on trust, security, and privacy issues in the Metaverse.

Topics of interest include, but are not limited to:

Authentication mechanisms
Quantum cryptography
Data mining and data analysis for trust and security
Security/privacy protocol design
Security and privacy of digital twins
Blockchain applications in the Metaverse
Intrusion detection and prevention systems for network security
Intrusion detection for IoT-based wearable devices
Trusted software and applications
XR and its related communication security
Privacy-preserving computation and Metaverse
Security and privacy of machine learning in the Metaverse
Adversarial examples in the Metaverse (attack and defense)
Trust, security, and privacy in cloud computing/edge computing
Novel theories, architectures, models, applications, and paradigms
Privacy preservation in AI-enabled networks
Trust, security, and privacy issues in the use of Metaverse underlying technologies (e.g., AI, digital twins, XR, blockchain, 5G/6G, cloud computing, etc.)
Miscellaneous trust, security, and privacy issues in the Metaverse

Proposals for this special issue should provide original content to broaden the knowledge about the Trust, Security, and Privacy in Metaverse. Extended versions (more than 30% of new content) of the best papers of the The 17th International Conference on Information Security Practice and Experience (https://ispec2022.ndhu.edu.tw/) are also invited to publish in this Special Issue.

Guest Editors

Hu Xiong, University of Electronic Science and Technology of China, China. [email protected]

Kuo-Hui Yeh, National Dong Hwa University, Taiwan. [email protected]

Han-Chieh Chao, National Dong Hwa University, Taiwan. [email protected]

Chunhua Su, the University of Aizu, Japan. [email protected]

Weizhi Meng, Technical University of Denmark, Denmark. [email protected]

Important dates

Submission portal opens: June 1, 2022

Deadline for paper submission: December 31, 2022

Latest acceptance deadline for all papers: May 15, 2023

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from June 1, 2022. When submitting your manuscript please select the article type VSI: TSP_Metaverse.

25 April 2022

Special Issue on Cybersecurity in the digital world

Motivation and Scope

We live in a hyperconnected world in which technology plays an essential role. Smartphones, computers, laptops, webcams and any other type of technological gadgets are part of our daily life activities. However, from hospitals, schools or governments to any type of company, cybersecurity cannot be taken for granted.

The huge number of cyberattacks that emerge daily calls for the development of systems, mechanisms and applications that make harder the attackers' success. In this regard, cybersecurity controls need to be established. They can be distinguished between prevention, which corresponds to blocking an attack; deterrence, which focuses on making the attack difficult; redirection, that is based on modifying the target; mitigation, which tries to reduce the impact of the cyberattack; detection, which looks for spotting the attack when it happens or sometime afterwards; and recovery, that focuses on recovering from damage after a cyberattack has taken place.

The purpose of this special issue is to look for proposals that develop systems, mechanisms or applications in line with any of aforementioned cybersecurity controls. For instance, a honeypot approach can be directly linked to redirection controls and the development of a cyberattack predictor is related to prevention.

Topics of interest include, but are not limited to:

Governance and dynamic risk management
Cryptography, quantum and post-quantum
Access control and authentication
Intrusion and anomaly detection and prevention
Context and situational awareness
Response and recovery for (ciber)-resilience
Cyber threat intelligence
Security in critical infrastructures
Security in IoT/ CPS
Cloud/Edge computing security
Fake content management
Privacy enhanced technologies
Emerging technologies for cybersecurity such as Artificial Intelligence and Blockchain
Security and privacy for emerging technologies
Forensic analysis

Proposals for this special issue should provide original content to broaden the knowledge in the cybersecurity field. Extended versions (more than 30% of new content) of the best papers of the Jornadas Nacionales de Investigación en Ciberseguridad (JNIC) cybersecurity conference (https://2022.jnic.es) are also invited to publish in this Special Issue.

Guest Editors:

José María de Fuentes, Universidad Carlos III de Madrid, Spain, [email protected]

Lorena González, Universidad Carlos III de Madrid, Spain, [email protected]

Cristina Alcaraz, Universidad de Málaga, Spain, [email protected]

Marta Beltran, Universidad Rey Juan Carlos, Spain, [email protected]

Gianluca Dini, Università di Pisa, Italy, [email protected]

Important Dates

Submission portal opens: April 20, 2022

Deadline for paper submission: August 15, 2022

Latest acceptance deadline for all papers: December 20, 2022

Manuscript Submission Instructions

17 April 2022

Special Issue on Distributed and Parallel Processing of Big Spatiotemporal Data

Motivation and Scope

We are witnessing the continued proliferation of mobile equipment (e.g., smartphones, wearable sensors) and location-based social media (e.g., online map services, ride-hailing services, micro-blogging services), making it possible for us to acquire huge volumes of spatiotemporal data. Spatiotemporal data has many unique data features consisting of spatial, temporal, and some other relevant information, including text, attribute-value pairs, and classifications. It is of great importance to build up functionalities of obtaining useful and timely knowledge from massive-scale spatiotemporal data. Traditional centralized data processing mechanisms is incapable of handling the skyrocketing volume of spatiotemporal data. As such, it is imperative to process spatiotemporal data under distributed environment. However, effective and efficient processing of big spatiotemporal data under distributed environment is still an open problem to the data science community. On the one hand, the efficiency and effectiveness spatiotemporal data processing and applications at mobile devices require research on the next-generation distributed and peer-to-peer system infrastructure and application development. On the other hand, the huge volume of data leads to many interesting paradigms in the cloud, IoT, 5G networks, and their collaborations with mobile computing, virtual reality, and metaverse.

This special issue will focus on the ability to manage, mine, and analyze big spatiotemporal data by taking advantage of modern distributed and peer-to-peer system infrastructure and developing next-generation data management systems, bridging the gap between spatiotemporal data science and distributed computing systems. For the purpose, we may need to investigate the following technical challenges. (1) How to build-up next-generation distributed and peer-to-peer system infrastructure for processing big spatiotemporal data? (2) How to manage multisource spatiotemporal data by leveraging high-performance computing paradigm and high-throughput computing paradigm? (3) How to analyze spatiotemporal data streams and discover bursty events under many-task mobile computing frameworks? (4) How to develop generic distributed database systems for storing and indexing big spatiotemporal data and supporting fundamental database operations?

To address aforementioned challenges, this special issue aims to pioneer novel distributed data management techniques, data processing frameworks and paradigms on the basis of IoT and 5G environments, parallel data mining algorithms, multisource and multimodal streaming data processing mechanisms, and geo-spatial query processing and optimization algorithms to establish generic distributed database systems for managing, mining, and analyzing big spatiotemporal data in an effective and efficient way.

Topics of interest include, but are not limited to:

Compute resource management for spatiotemporal data processing and applications
Spatiotemporal data representation models on HPC and HTC systems
IoT-based spatiotemporal data processing frameworks
Distributed spatiotemporal data analytics on 5G infrastructures
Workflow systems for spatiotemporal data analytics Distributed data management systems for spatiotemporal data acquisition, storage, and access
Spatiotemporal data analytics on cloud computing infrastructures
Parallel processing of spatiotemporal queries
Many-task spatiotemporal computing paradigm
Privacy-preserving spatiotemporal data mining under distributed environment
Distributed spatiotemporal indexing techniques
Distributed management of location-based social networks
Analytics of multiple data streams
Emerging applications in spatiotemporal data management (e.g., virtual reality, metaverse)
Spatiotemporal analysis in knowledge graph

Guest Editors

Shuo Shang, University of Electronic Science and Technology of China, [email protected]

Bingsheng He, National University of Singapore, [email protected]

Lizhe Wang, China University of Geoscience, [email protected]

Important Dates

Submission portal opens: April 11, 2022

Deadline for paper submission: October 31, 2022

Latest acceptance deadline for all papers: April 30, 2023

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from April 11, 2022. When submitting your manuscript please select the article type VSI: Big spatiotemporal data.

11 March 2022

Special Issue on Artificial Intelligence in Biomedical Big Data and Digital Healthcare

Motivation and Scope

Biomedical knowledge reasoning is required to enhance the explainability of medical AI applications by overcoming the limitations of deep-learning methods as black-box models. Also, understanding correlations among multi-modal biomedical data can improve diagnostics support systems' performance and discover biomedical knowledge. Recently, transformer-based models, such as UNITER and VL-BERT, have exhibited remarkable performance for dealing with multi-modal data. Finally, the need of restraining data where they belong has boosted the advent of federated learning to cope with privacy and scalability issues.

This special issue aims at different research areas of artificial intelligence in biomedical big data, digital healthcare, bioinformatics, medicine, and biology. Thereby, this issue attempts to discuss novel research directions and contributions related to models, analysis, and applications for practicalizing biomedical AI applications.

Topics of interest include, but are not limited to:

Deep-learning-empowered artificial intelligence models for biomedical applications
Biomedical knowledge reasoning
Biomedical knowledge graph construction and completion
Biomedical knowledge graph embedding
Biomedical knowledge extraction from electronic medical record
Explainable diagnostics support system
Diagnostics support system based on electronic medical record
Multi-modal biomedical data analysis models
Multi-modal transformer models for biomedical data
Data anonymization methods for biomedical data
Privacy-aware biomedical data analysis
Federated learning for biomedical data
Causal Inference for multi-modal biomedical data
Self-supervised learning for multi-modal biomedical data
Biomedical image/signal processing
Sensing, detection, and recognition in biomedical image/signal
Natural language processing and knowledge discovery in biomedical documents
Emerging digital healthcare applications
Wearable medical wireless sensors
Mobile and cloud computing for digital healthcare
Security, trust, and privacy in digital healthcare

Guest Editors

Chang Choi, Gachon University, Rep. of Korea. [email protected]

Christian Esposito, University of Salerno, Italy. [email protected]

Kiho Lim, William Paterson University of New Jersey, USA. [email protected]

Tian Wang, Beihang University, Institute of Artificial Intelligence, China. [email protected]

Important Dates

Submission portal opens: June 1, 2022

Deadline for paper submission: August 1, 2022

Latest acceptance deadline for all papers: December 1, 2022

Manuscript Submission Instructions

3 March 2022

Motivation and Scope

Meeting the 17 Sustainable Development Goals (UN Agenda 2030 for Sustainable Development) requires acting and adopting strategies from varied fronts. Technological innovation has proved to be one of such fronts, and its potential should be harnessed and maximized to support sustainable development and deliver the highest impact. In this scenario, the good use of ICT and emerging frugal technologies is particularly urgent, considering that most SDGs focus on social good. Social good can be defined as something that benefits the largest number of people in the largest possible way. Examples are: clean air (SDG 3 and 11), clean water (SDG 6), healthcare (SDG 3), and literacy (SDG 4). In the attempt to address social good issues engaging communities and citizens through digital technologies, a new concept emerged: digital social innovation. This concept lies at the intersection of three areas: innovation, social and environmental problems, and digital technologies, and has a strong focus on helping communities in sharing data, collaborating to solve societal problems and scaling their initiatives focusing on open and distributed technologies and new sustainable business models.

This special issue intends to elicit multidisciplinary contributions describing innovative applications and services, such as methods and tools, able to address the presented challenges adequately. As a result, this special issue will act as a forum for presenting research studies in emerging ICT solutions for sustainable development and digital social innovation.

Topics of interest include, but are not limited to:

IT for development and for education
Digital democracy, open data for transparency and disinformation
AI for social good and social informatics
IT for smart living, sustainable cities and communities
Frugal solutions for IT and Sustainable IT
Smart governance and e-administration
Citizen science and Civic intelligence
Environmental monitoring
ICT for health and social care
Technology addressing the digital divide]
Blockchain for social good
Ethical computing, privacy, trust, and ethical issues in ICT solutions
Gamification, serious game, and game with a purpose

Guest Editors

Catia Prandi, University of Bologna, Italy. [email protected]

Diogo Pacheco, University of Exeter, UK. [email protected]

Costas Mourlas, University of Athens, Greece. [email protected]

Important Dates

Submission portal opens: October 15, 2022

Deadline for paper submission: January 15, 2023

Latest acceptance deadline for all papers: June 30, 2023

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from October 15, 2022. When submitting your manuscript please select the article type VSI: GoodIT 2022.

5 January 2022

Special Issue on Semantic Modeling and Design Patterns for Internet of Things (IoT) Ecosystems

Motivation and Scope

Internet of Things (IoT) applications are nowadays adopted worldwide and they are expected to play an even more significant role in the next future as technological enablers in manifold sectors, ranging from healthcare to smart working, from smart cities to edge computing, thus creating new IoT ecosystems capable of supporting the novel use cases that are devised and deployed with a constantly growing frequency. Such an ongoing IoT-driven transformation demands for interoperating services, reliable sensor data integration, adequate security levels, scalable access to resources and effective service discovery methods. Therefore, when an environment as dynamic as the IoT is involved, knowledge representation and management strategies face several challenges, in terms of capabilities and requirements (e.g., data annotation, processing time, query-response time, assessment of missing values) to be guaranteed.

This special issue aims to address the areas of semantic modeling and design patterns for IoT ecosystems, as these two aspects can help providing guidance to IoT system designers who have to cope with the knowledge representation stage in the IoT domain as well as to IoT system implementers who need to use and coordinate different IoT frameworks. Researchers and practitioners from academia and industry are invited to submit their research works dealing with novel solutions to improve efficiency and reliability in this domain. Manuscripts proposing semantic models for the IoT domain and introducing novel IoT semantic design patterns are especially appreciated.

Topics of interest include, but are not limited to:

Semantic models for IoT ecosystems
Dynamic semantics in IoT ecosystems
Lightweight semantics in IoT frameworks
Formal ontologies for IoT applications
Ontological meta-models for IoT frameworks
Annotation ontologies for IoT ecosystems
Semantic-enabled knowledge discovery in the IoT domain
Semantic-enabled access to IoT services
Resource classification and reasoning in IoT ecosystems
Semantic reasoning for edge computing scenarios
Semantic-driven edge computing
IoT semantic design patterns
Semantic-based IoT design patterns
Applications in smart cities and virtual communities, smart energy, healthcare, smart transportation

Guest Editors

Domenico Potena, Università Politecnica delle Marche, Italy. [email protected]

Marco Zappatore, Università del Salento, Italy. [email protected]

Alex Mircoli, Università Politecnica delle Marche, Italy. [email protected]

Antonella Longo, Università del Salento, Italy. [email protected]

Important Dates

Submission portal opens: February 1, 2022

Deadline for paper submission: July 1, 2022

Latest acceptance deadline for all papers: November 1, 2022

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from February 1, 2022. When submitting your manuscript please select the article type VSI: SemIoT.

3 December 2021

Special Issue on Integration of Machine Learning and Edge Computing for Next Generation Smart Wearable Systems

Motivation and Scope

Machine learning (ML) provides an enabling technology for the development of the next generation of smart devices. However, the integration of ML and edge computing faces major challenges. While powerful models can tackle difficult tasks such as visual recognition or natural language processing, the constrained resources of embedded systems might prevent direct deployment of the designed inference function into an edge device. Bringing ML to embedded systems is indeed an important requirement for building the next generation of intelligent devices. Under the paradigm of edge computing, ML may play a major role in empowering multiple application areas. The list of use cases includes sensor networks, industrial IoT, robotics, assistive technology, smart healthcare, prostheses and exoskeletons, connected vehicles, and many others. However, the deployment of a ML model on an embedded system faces major challenges. An embedded system imposes constraints in terms of energy consumption, processing speed, size, and cost. The constraint on energy consumption is particularly critical when battery-operated devices are involved. While powerful models (e.g., deep networks) can tackle difficult tasks such as visual recognition or natural language processing, the constrained resources of embedded systems might prevent direct deployment of the designed inference function into an edge device. An additional challenge is how to implement the training process on the device, which is especially relevant for the systems that can adapt online using, for instance, incremental learning. Online learning and adaptation is a critical function when tackling real life challenges in unpredictable and dynamically changing environments.

This special issue collects manuscripts describing methodologies and systems that tackle the integration of ML into embedded systems. The focus is on solutions that can stimulate significant improvements in wearable systems across different domains.

Topics of interest include, but are not limited to:

Embedded machine learning
Power-efficient machine learning implementations on FPGAs
Online learning on resource-constrained edge devices
Lightweight architectures for deep learning
High-performance, low-power computing for deep learning and computer vision
On-chip training of deep neural networks
Edge-driven Intelligence for wearable device
Intelligent sensors
Assistive robots and bionic limbs empowered by edge computing
Security of edge-based ML application
Adversarial attacks to lightweight deep learning solutions

Guest Editors

Paolo Gastaldo, University of Genoa, Italy. [email protected]

Edoardo Ragusa, University of Genoa, Italy. [email protected]

Strahinja Dosen, Aalborg University, Denmark. [email protected]

Francesco Palmieri, University of Salerno, Italy. [email protected]

Important Dates

Submission portal opens: June 5, 2022

Deadline for paper submission: September 30, 2022

Latest acceptance deadline for all papers: February 28, 2023

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from June 5, 2022. When submitting your manuscript please select the article type VSI: Smart Wearable Systems.

30 November 2021

Special Issue on Cluster and Cloud Computing for Life Sciences (LIFE2022)

Motivation and Scope

Computational methods are nowadays ubiquitous in the field of bioinformatics and biomedicine. Besides established fields like molecular dynamics, genomics or neuroimaging, new emerging methods like deep learning models rely heavily on large-scale computational resources. These new methods need to manage Tbytes or Pbytes of data with large-scale structural and functional relationships, TFlops or PFlops of computing power for simulating highly complex models, or many-task processes and workflows for processing and analyzing data. Today, many areas in Life Sciences are facing these challenges, such as biomodelling, predictive models of disease and treatment, evolutionary biology, medical biology, cell biology, biomedical image processing, biosignal sensoring or computer-supported diagnosis. Clouds, Edge/Fogs and Big Data Environments are promising to address research, clinical and medical research community requirements as they allow for significant reduction of computational time to run large experiments, for speeding-up development time for new algorithms, and to reduce barriers for large-scale multi-centric collaborations.

This special issue provides a forum for presenting research works showing advances of bioinformatics and medical applications using distributed IT systems, new ideas and approaches to successfully apply distributed IT-systems in translational research, clinical intervention, and decision-making, and novel proposal to tackle specific challenges in Life Sciences computing such as security, traceability, data interoperability, simulation of complex models, creation of cloud services, or application of artificial intelligence techniques to enhance decisions and to speed up processes.

Topics of interest include, but are not limited to:

Detailed application use-cases highlighting achievements and roadblocks
Exploitation of distributed IT resources for Life Sciences, HealthCare and research applications, for example medical imaging, disease modeling, bioinformatics, Public health informatics, drug discovery, clinical trials
Service and/or algorithm design and implementation applicable to medical and bioinformatic applications
Improved energy consumption of bioinformatic applications using clouds
Modeling and simulation of complex biological processes
Genomics and molecular structure evolution
Molecular dynamics
Clouds for big data manipulation in bioinformatics and medicine
Ontologies and biomedical text mining
Biological data mining and visualization
Machine learning in biomedical data analytics
Deep learning experiences in Life Sciences
Error handling and fault tolerance
Distributed and heterogeneous bioinformatic and medical data management
Big medical and bioinformatic data applications and solutions
Data privacy, security and access control
Development environments for distributed bioinformatic applications
Programming paradigms and tools for bioinformatic applications
Scientific gateways and user environments targeting distributed medical and bioinformatic applications
Interoperability for exchanging data, algorithms and analysis pipelines

Guest editors

Jesus Carretero, University Carlos III of Madrid, Spain. [email protected]

Dagmar Krefting, University of Goettingen, German. [email protected]

Important Dates

Submission portal opens: March 15, 2022

Deadline for paper submission: June 15, 2022

Latest acceptance deadline for all papers: November 15, 2022

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from March 15th 2022. When submitting your manuscript please select the article type VSI: LIFE2022.

29 November 2021

Special Issue on Advances in Data Platform Design, Management, and Optimization

Motivation and Scope

Big data has imposed a paradigm change in the way data is stored, managed, and queried, fostering the evolution of information systems into complex data platforms or ecosystems. Data platforms enable data-intensive storage, computation, and processing of heterogeneous data, but open to the risk of losing control over data. Collecting proper metadata significantly reduces this risk and supports better data management; this enables advanced functionalities such as data understanding and profiling, provenance control, orchestration of processing pipelines, incremental integration, and efficient querying. The challenges begin with the management of metadata itself in terms of the modeling effort, storage, complexity of retrieval activities, and effective exploitation; these problems are further amplified in the age of data science, which witnesses data scientists prevail over data architects.

Since smart and comprehensive support for data scientists and architects to govern the data through the whole life-cycle is still lacking, the candidate papers for this special issue are innovative high-quality contributions positioned at the frontier of research on both theoretical and practitioner advancements of data platforms, with the goal to optimize and simplify the different aspects of (meta)data management and fruition. Besides addressing the Vs of big data, the enabled functionalities must cope with the heterogeneity of storage and computation engines - which include DBMSs supporting multiple data models and cloud storage systems with limited control and predictability – while meeting suitability requirements for less-skilled users.

Topics of interest include, but are not limited to:

Metadata modeling for data platforms
Techniques for metadata discovery and management
Data fabric, data mesh architectures
Advanced search, exploration, and profiling of data and metadata
Semantic enrichment of metadata
Data governance
Data wrangling
DataOps
Provenance and data versioning control
Orchestration and optimization of data transformation pipelines
Data integration and querying in multimodel databases, multistores, and polystores
Query processing, optimization, and performance
Entity resolution and data fusion
Big data management and querying
Artificial intelligence solutions for data platforms
AutoML techniques
Cloud computing and architectures
Advanced architectures for data lakes and data platforms
Analysis, design, implementation, and testing of data platforms
Case studies and project experiences

Guest Editors

Matteo Francia, University of Bologna, Italy. [email protected]

Enrico Gallinucci, University of Bologna, Italy. [email protected]

Patrick Marcel, Université de Tours, France. [email protected]

Stefano Rizzi, University of Bologna, Italy. [email protected]

Important Dates

Submission portal opens: February 1, 2022

Deadline for paper submission: July 31, 2022

Latest acceptance deadline for all papers: December 16, 2022

Manuscript Submission Instructions

29 November 2021

Special Issue on Future-Generation Attack and Defense in Neural Networks

Motivation and Scope

Neural Networks have demonstrated great success in many fields. However, recent studies revealed that neural networks are vulnerable to adversarial attacks. The vulnerability of neural networks, which may hinder their adoption in high-stake scenarios. Thus, understanding their vulnerability and developing robust neural networks have attracted increasing attention. To understand and accommodate the vulnerability of neural networks, various attack and defense techniques have been proposed. Therefore, this special issue focuses on adversarial attacks and defenses in various future-generation neural networks, e.g., CNNs, LSTMs, ResNet, Transformers, BERT, spiking neural networks, and graph neural networks. We invite both reviews and original contributions, on the theory (design, understanding, visualization, and interpretation) and applications of adversarial attacks and defenses, in future-generation natural language processing, computer vision systems, speech recognition, recommender systems, etc.

This special issue focuses on adversarial attacks and defenses in various future-generation neural networks (e.g., CNNs, LSTMs, ResNet, Transformers, BERT, spiking neural networks, and graph neural networks). We invite both reviews and original contributions on the theory (design, understanding, visualization, and interpretation) and applications of adversarial attacks and defenses, in future-generation natural language processing, computer vision systems, speech recognition, recommender systems.

Topics of interest include, but are not limited to:

Novel adversarial attack approaches
Novel adversarial defense approaches
Model vulnerability discovery and explanation
Trust and interpretability of neural network
Attacks and/or defenses in NLP
Attacks and/or defenses in recommender systems
Attacks and/or defenses in computer vision
Attacks and/or defenses in speech recognition
Attacks and/or defenses in physiological computing
Adversarial attack and defense various future-generation applications

Guest Editors

Yang Li, Northwestern Polytechnical University, China. [email protected]

Dongrui Wu, Huazhong University of Science and Technology, China. [email protected]

Suhang Wang, The Pennsylvania State University, USA. [email protected]

Important Dates

Submission Portal Opens: January 20, 2022

Deadline for paper submission: June 20, 2022

Latest acceptance deadline for all papers: October 20, 2022

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue on January 20, 2022. When submitting your manuscript please select the article type VSI: FGADNN.

29 November 2021

Special Issue on Integration of Communication, Computing, Caching and Learning (3C-L) for 6G Wireless Systems

Motivation and Scope

As the explosive growth of smart connected devices and new services with rich experiences, such as truly immersive VR/AR/MR (XR), network traffic volume has been growing exponentially. The traditional network architecture cannot accommodate such user demands in terms of throughput, latency, massive connections, and so forth. Therefore, edge computing technologies are proposed to bring computation and caching resources at the edge of the 6G wireless systems. The combination of communication, computation and caching functionalities endows the next-generation of wireless systems with powerful data processing and caching capabilities, hence enriching the computing and storage experience of mobile users and enabling new applications to be implemented on the network. The allocation and management of communication, computing and caching resources needs to be jointly optimized for improving the quality of service and user experience. However, the high dynamics in terms of channel conditions, user mobility, and the available computation and caching capabilities make it quite challenging to jointly optimize communication, computing and caching resources while also dealing with time-varying network conditions. Artiﬁcial intelligence (AI) is an emerging paradigm in which entities and systems are able to learn and make decisions by imitating biological processes. Modern machine learning is a key enabler to deal with the problems with uncertain, time-variant, and complex features of 6G，including channel modeling, network optimization, resource management, routing, protocol design, and application/user behavior analysis. However, the research on the integration of Communication, Computing, Caching and Learning (3C-L) still is in its infancy with many key problems to be solved.

Topics of interest include, but are not limited to:

AI-based network design and resource allocation for efficient 6G wireless systems
AI for the modeling and analysis of integrating communication, computation and caching in 6G wireless systems
AI for computation offloading in 6G wireless systems
AI for edge caching in 6G wireless systems
Resource management and cross-layer design for AI-based 6G wireless systems
AI-inspired secure and intelligent resource management in 6G wireless systems
Efficient architecture and new protocol design for AI-based wireless systems
Intelligent data processing, communications, and integration in edge intelligence for 6G wireless systems
Efficient resource management for edge intelligence in 6G wireless systems
Performance analysis and evaluation for intelligent 6G wireless systems
Implementation/testbed/deployment for AI-based 6G wireless systems

Guest Editors

Celimuge Wu, University of Electro-Communications, Japan. [email protected]

Schahram Dustdar, Vienna University of Technology, Austria. [email protected]

Yang Yang, Shanghai, Tech University, China. [email protected]

Kuan Zhang, University of Nebraska-Lincoln, USA. [email protected]

Tingting Yang, Dongguan University of Technology, China. yang[email protected]

Yueyue Dai, Nanyang Technological University, Singapore. [email protected]

Important Dates

Submission portal opens: February 28, 2022

Deadline for paper submission: July 1, 2022

Latest acceptance deadline for all papers: December 30, 2022

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue from February 28, 2022. When submitting your manuscript please select the article type VSI: 3C-L for 6G Systems

17 November 2021

Motivation and Scope

The role of AI (Artificial Intelligence), IoT (Internet of Things), and big data continues to increase as the 4th Industrial Revolution progresses. Navigation technology is the most effective application of the three technologies listed above. With the rapid development of wireless devices and appliances, and the emerging applications of IoT, wireless sensing applications have received wide attention in recent years. Given the plethora of location-based services (LBS), indoor localization using WiFi Sensing has piqued the interest of both academia and industry. These can be used in a variety of settings, including healthcare, government, public service, industry, military, retail, and arts and culture. Personal navigation, museum guidance, intrusion detection, wayfinding in a large shopping mall or hospital, asset monitoring, fleet and inventory management, maximizing efficiency in manufacturing or distribution are all examples of location-aware applications. The growing amount of available positioning data facilitates these applications due to ubiquitous connectivity and the IoT.

This special issue aims at addressing the applications of WiFi signals using different metrics (i.e., RSSI and CSI) for indoor localization, human motion detection, human activity recognition, gesture recognition, and other related topics such as privacy and security. New and novel models for WiFi-based sensing applications for smart homes and IoT environments are main topics of this special issue.

Topics of interest include, but are not limited to:

Device-free indoor navigation systems
Indoor positioning/localization
Indoor human motion detection
Human activity recognition (HAR)
Indoor positioning data analytics
Data fusion of indoor positioning distributed sensors;
Fall detection
Privacy-enhancing for WiFi-based sensing systems
IoT monitoring systems
Intrusion detection
Applications for eldercare and vision-impaired using WiFi signals
Location-based services for assisted living applications
Location-based privacy and security for smart environments
Smart home and assisted living environments
Smart indoor security systems

Guest Editors

Robertas Damaševičius, Silesian University of Technology, Poland. [email protected]

Victor Hugo C. de Albuquerque, Federal Institute of Education, Science and Technology of Ceará, ARMTEC Tecnologia em Robótica, Brasil. [email protected]

Mohammed A. A. Al-qaness, Wuhan University, China. [email protected]

Mohamed Abd Elaziz, Zagazig University, Egypt. [email protected]

Important Dates

Submission Portal Opens: January 20, 2022

Deadline for paper submission: January 1, 2023

Latest acceptance deadline for all papers: June 15, 2023

Manuscript Submission Instructions

The FGCS’s submission system (https://www.editorialmanager.com/FGCS/default.aspx) will be open for submissions to our Special Issue starting from April 1, 2022. When submitting your manuscript please select the article type VSI: Exp-AI-IoT-Nav-WiFi.

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