In the face of issues such as privacy leakage and malicious attacks, blockchain-based asynchronous federated learning emerges as a promising solution, not only capable of protecting user privacy and resisting malicious attacks but also ...

With the development of IoT, the concept of intelligent services has gradually come to the fore. Intelligent services usually involve a large number of computation intensive tasks with data dependencies that are often modelled as directed acyclic ...

Today’s advancement in Vehicular Ad-hoc Networks (VANET) constitutes a cornerstone in ensuring traffic safety in Intelligent Transportation Systems (ITS). In this context, vehicle-to-vehicle (V2V) communications are a pivotal enabler for road ...

• We propose a DID-based reputation scheme for VANET compliant with ETSI standards.
• We provide the research community with the first ETSI-compliant V2V dataset.
• We implement and evaluate DIVA in 5G-enabled scenarios proving its ...

• A novel data-driven root cause analysis framework for learning root.
• cause graphs (RCGs) from time-to-event (TTE) data.
• A framework for simulating realistic TTE data from structural causal.
• models for root cause investigations.

Data-driven approaches to root cause analysis (RCA) have received at- tention recently due to their ability to exploit increasing data availability for more effective root cause identification in complex processes. Advancements in the field of ...

Cloud Computing Environment (CCE) has gained considerable attention in recent years because of scalability, flexibility, and cost-effectiveness. Workflow scheduling, a critical aspect of CCE, involves assigning tasks of a workflow to suitable ...

In this study, we introduce a novel method, “TransVAE-PAM”, for the classification of fake news articles, tailored specifically for the Indian context. The approach capitalizes on state-of-the-art contextual and sentence transformer-based embedding models ...

Real-time and embedded systems are shifting from single-core to multi-core platforms, on which software must be parallelized to fully utilize the computation power of multi-core hardware. Most current real-time parallel tasks can be modeled as ...

The proliferation of Internet of Things (IoT) devices, generating massive amounts of heterogeneous distributed data, has pushed toward edge cloud computing as a promising paradigm to bring cloud capabilities closer to data sources. In many cases ...

• Identify and discuss the main factors in designing and developing FL at the edge.
• Describe how DLTs can be used to tackle the targeted design challenges.
• Propose a novel architecture that leverages IOTA and IPFS to enable FL at the ...

High-Performance Computing (HPC) is essential to support the advance in multiple research and industrial fields. Despite the recent growth in processing and networking power, the HPC Data Centers (DCs) are finite, and should be carefully managed ...

• We researched the DAG-based workflows scheduling considering both the users’ and HPC DC’s perspectives.
• We proposed, implemented and analyzed an AC RL scheduler to select the appropriated combination of queueing policies.
• The AC RL ...

Cross-domain applications are rapidly adopting blockchain techniques for immutability, availability, integrity, and interoperability. However, for most applications, global consensus is unnecessary and may not even provide sufficient guarantees.

We ...

The Byzantine Fault Tolerance (BFT) protocol is a long-standing topic. Recently, a lot of efforts have been made in the research of asynchronous BFT. However, the existing solutions cannot adapt well to the flexible network environment, and suffer ...

Modern cyber-physical embedded systems are characterized by a range of intricate functionalities that are subject to tight timing constraints. Unfortunately, traditional sequential task models and uniprocessors solutions are not suitable for this ...

Skin cancer is one of the fatal cancers worldwide. Early detection of this disease can significantly increase the survival rate. In this study, a multi-modal and soft attention based hybrid deep learning model is proposed for automated ...

• Soft attention-based multi-modal network is proposed for multi-label classification.

Many scientific workflows can be modeled as a Directed Acyclic Graph (henceforth mentioned as DAG) where the nodes represent individual tasks, and the directed edges represent data and control flow dependency between two tasks. Due to the large volume of ...

A scientific workflow is modeled as a Directed Acyclic Graph where the nodes represent individual tasks and the directed edges represent the dependency relationship between two tasks. Scheduling a workflow to achieve certain goal(s) (e.g.; ...

Runtime systems can significantly reduce the cognitive complexity of scientific applications, narrowing the gap between systems engineering and domain science in HPC. One of the most important angles in this is automating data migration in a ...

At present, the traditional methods of calculating the worst response time upper bounds for direct acyclic graph (DAG) task scheduling on heterogeneous multi-core platforms suffer from problems such as nonself-sustainability, too many ...

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• Patient-Reported-Outcome-Measures are filled out by patients to assess their health.
• We found it was possible to reduce the PROM question burden with Bayesian Networks.
• We present a systematic approach for building PROM BNs that ...

Patient Reported Outcome Measures (PROMs) are questionnaires completed by patients about aspects of their health status. They are a vital part of learning health systems as they are the primary source of information about important outcomes that ...

Graph structure is widely used in network design, path planning, relational processing, electronic circuit design, and power grid tide management. However, the complexity and variety of relationships between different data objects create ...

Scheduling in computing environments such as homogeneous and heterogonous is very challenging and faces various difficulties computationally. This computing needs an optimal method that decides how to allocate and execute the tasks on a computing ...