Radu Prodan

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Papers by Radu Prodan

ARTICONF decentralized social media platform for democratic crowd journalism

Social Network Analysis and Mining, Sep 14, 2023

Media production and consumption behaviors are changing in response to new technologies and deman... more Media production and consumption behaviors are changing in response to new technologies and demands, giving birth to a new generation of social applications. Among them, crowd journalism represents a novel way of constructing democratic and trustworthy news relying on ordinary citizens arriving at breaking news locations and capturing relevant videos using their smartphones. The ARTICONF project as reported by Prodan (Euro-Par 2019: parallel processing workshops, Springer, 2019) proposes a trustworthy, resilient, and globally sustainable toolset for developing decentralized applications (DApps) to address this need. Its goal is to overcome the privacy, trust, and autonomy-related concerns associated with proprietary social media platforms overflowed by fake news. Leveraging the ARTICONF tools, we introduce a new DApp for crowd journalism called MOGPlay. MOGPlay collects and manages audiovisual content generated by citizens and provides a secure blockchain platform that rewards all stakeholders involved in professional news production. Besides live streaming, MOGPlay offers a marketplace for audiovisual content trading among citizens and free journalists with an internal token ecosystem. We discuss the functionality and implementation of the MOGPlay DApp and illustrate four pilot crowd journalism live scenarios that validate the prototype. Crowd journalism • Citizen-generated content • Decentralized app • Social media • Marketplace * Radu Prodan

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Towards an Environment for Efficient and Transparent Virtual Machine Operations: The ENTICE Approach

Zenodo (CERN European Organization for Nuclear Research), Oct 3, 2016

Cloud computing is based on Virtual Machines (VM) or containers, which provide their own software... more Cloud computing is based on Virtual Machines (VM) or containers, which provide their own software execution environment that can be deployed by facilitating technologies on top of various physical hardware. The use of VMs or containers represents an efficient way to automatize the overall software engineering and operation life-cycle. Some of the benefits include elasticity and high scalability, which increases the utilization efficiency and decreases the operational costs. VMs or containers as software artifacts are created using provider-specific templates and are stored in proprietary or public repositories for further use. However, technology specific choices may reduce their portability, lead to a vendor lock-in, particularly when applications need to run in federated Clouds. In this paper we present the current state of development of the novel concept of a VM repository and operational environment for federated Clouds named ENTICE. The ENTICE environment has been designed to receive unmodified and functionally complete VM images from its users, and transparently tailor and optimise them for specific Cloud infrastructures with respect to their size, configuration, and geographical distribution, such that they are loaded, delivered, and executed faster and with improved QoS compared to their current behaviour. Furthermore, in this work a specific use case scenario for the ENTICE environment has been provided and the underlying novel technologies have been presented.

format_quoteThe ENTICE environment tailors and optimizes unmodified VM images for various Cloud infrastructures, enhancing loading speed and execution quality.format_quote

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Multi-objective Service Oriented Network Provisioning in Ultra-Scale Systems

Lecture Notes in Computer Science, 2018

The paradigm of ultra-scale computing has been recently pushed forward by the current trends in d... more The paradigm of ultra-scale computing has been recently pushed forward by the current trends in distributed computing. This novel architecture concept is focused towards a federation of multiple geographically distributed heterogeneous systems under a single system image, thus allowing efficient deployment and management of very complex architectures applications. To enable sustainable ultra-scale computing, there are multiple major challenges, which have to be tackled, such as, improved data distribution, increased systems scalability, enhanced fault tolerance, elastic resource management, low latency communication and etc. Regrettably, the current research initiatives in the area of ultra-scale computing are in a very early stage of research and are predominantly concentrated on the management of the computational and storage resources, thus leaving the networking aspects unexplored. In this paper we introduce a promising new paradigm for cluster-based Multi-objective service-oriented network provisioning for ultra-scale computing environments by unifying the management of the local communication resources and the external inter-domain network services under a single point of view. We explore the potentials for representing the local network resources within a single distributed or parallel system and combine them together with the external communication services.

format_quoteIntroduces a new paradigm for multi-objective service-oriented network provisioning, combining local and external network management.format_quote

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SMART: a Tool for Trust and Reputation Management in Social Media

Zenodo (CERN European Organization for Nuclear Research), Aug 30, 2021

Social media platforms are becoming increasingly popular and essential for next-generation connec... more Social media platforms are becoming increasingly popular and essential for next-generation connectivity. However, the emergence of social media also poses critical trust challenges due to the vast amount of created and propagated content. This paper proposes a data-driven tool called SMART for trust and reputation management based on community engagement and rescaled sigmoid model. SMART's integrated design adopts a set of expert systems with a unique inference logic for trust estimation to compute weighted trust ratings of social media content. SMART further utilizes the trust ratings to compute user reputation and represent them using a sigmoid curve that prevents infinite accumulation of reputation ratings by a user. We demonstrate the SMART tool prototype using a pilot social media application and highlight its user-friendly interfaces for trustworthy content exploration.

format_quoteSMART leverages a rescaled sigmoid model for computing reputation ratings, integrating local and global user reputations for improved trust management.format_quote

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A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing

Telecommunications Policy, 2010

Cloud Computing is emerging today as a commercial infrastructure that eliminates the need for mai... more Cloud Computing is emerging today as a commercial infrastructure that eliminates the need for maintaining expensive computing hardware. Through the use of virtualization, clouds promise to address with the same shared set of physical resources a large user base with different needs. Thus, clouds promise to be for scientists an alternative to clusters, grids, and supercomputers. However, virtualization may induce significant performance penalties for the demanding scientific computing workloads. In this work we present an evaluation of the usefulness of the current cloud computing services for scientific computing. We analyze the performance of the Amazon EC2 platform using micro-benchmarks and kernels.While clouds are still changing, our results indicate that the current cloud services need an order of magnitude in performance improvement to be useful to the scientific community.

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MPEG-2 conformance testing for interoperability

Proceedings of COM'96. First Annual Conference on Emerging Technologies and Applications in Communications

Abstract Cable Television Laboratories, Inc., has set up a laboratory to test conformance of cons... more

Evaluation of Storage Placement in Computing Continuum for a Robotic Application

Journal of grid computing, Jun 1, 2024

This paper analyzes the timing performance of a persistent storage designed for distributed conta... more This paper analyzes the timing performance of a persistent storage designed for distributed container-based architectures in industrial control applications. The timing performance analysis is conducted using an in-house simulator, which mirrors our testbed specifications. The storage ensures data availability and consistency even in presence of faults. The analysis considers four aspects: 1. placement strategy, 2. design options, 3. data size, and 4. evaluation under faulty conditions. Experimental results considering the timing constraints in industrial applications indicate that the storage solution can meet critical deadlines, particularly under specific failure patterns. Comparison results also reveal that, while the method may underperform current centralized solutions in fault-free conditions, it outperforms the centralized solutions in failure scenario. Moreover, the used evaluation method

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Cloud storage cost: a taxonomy and survey

World wide web, May 24, 2024

Cloud service providers offer application providers with virtually infinite storage and computing... more Cloud service providers offer application providers with virtually infinite storage and computing resources, while providing cost-efficiency and various other quality of service (QoS) properties through a storage-as-a-service (StaaS) approach. Organizations also use multicloud or hybrid solutions by combining multiple public and/or private cloud service providers to avoid vendor lock-in, achieve high availability and performance, and optimise cost. Indeed cost is one of the important factors for organizations while adopting cloud storage; however, cloud storage providers offer complex pricing policies, including the actual storage cost and the cost related to additional services (e.g., network usage cost). In this article, we provide a detailed taxonomy of cloud storage cost and a taxonomy of other QoS elements, such as network performance, availability, and reliability. We also discuss various cost trade-offs, including storage and computation, storage and cache, and storage and network. Finally, we provide a cost comparison across different storage providers under different contexts and a set of user scenarios to demonstrate the complexity of cost structure and discuss existing literature for cloud storage selection and cost optimization. We aim that the work presented in this article will provide decision-makers and researchers focusing on cloud storage selection for data placement, cost modelling, and cost optimization with a better understanding and insights regarding the elements contributing to the storage cost and this complex problem domain.

format_quoteCost comparison reveals that cloud storage costs vary significantly across providers and tiers, influenced by use scenarios and access patterns.format_quote

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Container-Based Data Pipelines on the Computing Continuum for Remote Patient Monitoring

IEEE Computer, Sep 30, 2023

Diagnosing, treatment, and follow-up care of patients is happening increasingly through telemedic... more Diagnosing, treatment, and follow-up care of patients is happening increasingly through telemedicine, especially in remote areas where direct interaction is hindered. Over the past three years, following the COVID-19 pandemic, the utility of remote patient care has been further field-tested. Tackling the technical challenges of a growing demand for telemedicine requires a convergence of several fields: 1) software solutions for reliable, secure, and reusable data processing, 2) management of hardware resources (at scale) on the Cloud/Fog/Edge Computing Continuum, and 3) automation of DevOps processes for deployment of digital healthcare solutions with patients. In this context, the emerging concept of big data pipelines provides relevant solutions and is one of the main enablers. In what follows, we present a data pipeline for remote patient monitoring and show a real-world example of how data pipelines help address the stringent requirements of telemedicine. Computer

format_quoteTelemedicine's market potential is projected at USD 83.5 billion, growing at a compound annual rate of 24%.format_quote

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Storage Placement in Computing Continuum for a Robotic Application

This paper analyzes the timing performance of a persistent storage designed for distributed conta... more This paper analyzes the timing performance of a persistent storage designed for distributed container-based architectures in industrial control applications. The storage ensures data availability and consistency while accommodating faults. The analysis considers four aspects: 1) placement strategy, 2) design options, 3) data size, and 4) evaluation under faulty conditions. Experimental results considering the timing constraints in industrial applications indicate that the storage solution can meet critical deadlines, particularly under specific failure patterns. Moreover, this evaluation method is applicable for assessing other container-based critical applications with timing constraints that require persistent storage.Further comparison results reveal that, while the method may underperform current centralized solutions under fault-free conditions, it outperforms the centralized solutions in failure scenarios.

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Workflow Trace Archive askalon-new_ee59 trace

BWA (short for Burroughs-Wheeler Alignment tool) is a genomics analysis workflow, courtesy of Sco... more

Workflow Trace Archive askalon-new_ee30 trace

BWA (short for Burroughs-Wheeler Alignment tool) is a genomics analysis workflow, courtesy of Sco... more

WELFake dataset for fake news detection in text data

We designed a larger and more generic Word Embedding over Linguistic Features for Fake News Detec... more We designed a larger and more generic Word Embedding over Linguistic Features for Fake News Detection (WELFake) dataset of 72,134 news articles with 35,028 real and 37,106 fake news. For this, we merged four popular news datasets (i.e. Kaggle, McIntire, Reuters, BuzzFeed Political) to prevent over-fitting of classifiers and to provide more text data for better ML training. Dataset contains four columns: Serial number (starting from 0); Title (about the text news heading); Text (about the news content); and Label (0 = fake and 1 = real). There are 78098 data entries in csv file out of which only 72134 entries are accessed as per the data frame. This dataset is a part of our ongoing research on "Fake News Prediction on Social Media Website" as a doctoral degree program of Mr. Pawan Kumar Verma and is partially supported by the ARTICONF project funded by the European Union's Horizon 2020 research and innovation program.

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