Article
Computer Science, Information Systems
Mohamed Jarraya, Sonda Elloumi
Summary: This research focuses on the study of virtual computing laboratories in Desktop-As-A-Service (DAAS) scheduling in a cloud computing environment. The objective is to efficiently schedule the labs in predefined sessions, considering load balancing and host selection. Mathematical models and optimization approaches are proposed, and heuristics are developed to solve large-scale cases. The results demonstrate the compelling performance of the proposed heuristics.
COMPUTER COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Babar Ali, Muhammad Adeel Pasha, Saif ul Islam, Houbing Song, Rajkumar Buyya
Summary: Fog computing serves as a complementary solution to centralized cloud infrastructure by extending computing resources to the network edge to address communication latency issues in traditional cloud computing. Volunteer computing leverages user-owned idle resources to reduce maintenance costs for high-performance computing, and when combined with volunteer-supported FC (VSFC), it can optimize latency, energy consumption, and network usage.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Bing Tang, Gilles Fedak
Summary: This paper proposes a hybrid storage framework called WukaStore, which integrates stable and volatile storage to offer scalable, configurable, and reliable big data storage service. By configuring different storage strategies, WukaStore can meet user requirements and provide cost-effective storage solutions.
IEEE TRANSACTIONS ON BIG DATA
(2022)
Article
Computer Science, Information Systems
Elham Alsadoon
Summary: This study investigated the extent to which the expectation confirmation model can predict the intention of students to continue using Virtual Desktop Infrastructure (VDI). The results showed that satisfaction and perceived usefulness are significant factors in predicting students' intention to continue using VDI. The study also recommends further research in the field of VDI to explore other factors that contribute to continued use.
Article
Computer Science, Software Engineering
Nupur Jangu, Zahid Raza
Summary: This work proposes a Smart Admission Control strategy utilizing volunteer-enabled Fog-Cloud computing (SAC-VFC) to address the challenges of improper selection of volunteer nodes (VNs) in volunteer computing (VC) approaches. The VNs are selected based on grey TOPSIS ranking and tasks are scheduled using the Improved Jellyfish Algorithm (IJFA). Simulation study suggests the superior performance of SAC-VFC over peers in terms of average delay, average makespan, success rate of tasks, and tasks satisfying the deadline metrics.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Theory & Methods
J. Damian Segrelles Quilis, German Molto, Ignacio Blanquer
Summary: Traditional training on Grid technologies has limitations, leading to the proposal of a Project Based Learning framework. A Cloud-based tool has been implemented to provide Grid infrastructures as a Service with enhanced scalability and administration capabilities, achieving a high impact in the teaching-learning process.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2021)
Article
Computer Science, Information Systems
Farooq Hoseiny, Sadoon Azizi, Mohammad Shojafar, Rahim Tafazolli
Summary: Volunteer computing is a distributed computing approach where volunteers share resources to handle large tasks. Task scheduling algorithms play a crucial role in efficiently utilizing computing resources and reducing costs in heterogeneous volunteer computing systems.
ACM TRANSACTIONS ON INTERNET TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Kyuhyup Lee, Joonghwan Shin, Soonwook Kwon, Chung-Suk Cho, Suwan Chung
Summary: This study introduces the VDI system recently used in other industries to improve operations in the BIM environment of architectural design companies. It aims to provide initial application for small to medium-sized design firms and validates the KBimVdi system through selected projects using BIM for design work.
APPLIED SCIENCES-BASEL
(2021)
Article
Energy & Fuels
Caishan Guo, Fengji Luo, Zexiang Cai, Zhao Yang Dong
Summary: Cloud computing platforms and data centers are critical in modern society, acting as large energy consumers in power grids. By integrating on-site renewable energy sources and storage systems, data centers can become energy prosumers. Future research will focus on the integration of data centers and smart grids to optimize energy consumption and actively participate in grid planning and operation.
Article
Computer Science, Theory & Methods
Zheng Li, Pedro Pinacho-Davidson, Monserrat Martinez-Marin, Guillermo Cabrera-Vives, Yiqun Chen, Maria Andrea Rodriguez, Albert Y. Zomaya, Rajiv Ranjan
Summary: The article introduces the concept of free-of-charge metacomputing and its application in cloud computing, proposing a unique form called bonus computing. Through empirical validation and application extension, the effectiveness of bonus computing is demonstrated. The authors believe that bonus computing makes a significant contribution to the educational community.
Article
Chemistry, Multidisciplinary
Dmitry A. Zaitsev, Tatiana R. Shmeleva, David E. Probert
Summary: The correctness of networking protocols is crucial for cybersecurity, and recent developments in computing and communication grids have led to the need for verification of protocols for any number of devices. The introduction and study of infinite Petri nets have provided a new approach to analyzing computing and communication grid structures. Software generators for infinite Petri net models have been developed, and special classes of graphs like packet transmission directions and blockings have been introduced and studied for protocol analysis.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Theory & Methods
Jose Angel Morell, Enrique Alba
Summary: The combination of edge computing and federated learning, known as federated edge learning, provides a solution for processing and protecting a large amount of data from interconnected devices. This research focuses on adapting to the changing environment through asynchronous learning and utilizing volunteer device resources for shared model training.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Hongying Dong, Aaron T. Kinfe, Jiakai Yu, Qi Liu, Dan Kilper, Ronald D. Williams, Malathi Veeraraghavan
Summary: This article explores the feasibility of applying virtual-desktop computing to residential users through an objective study. It introduces new metrics to evaluate the performance of user-received applications. The results indicate the potential adaptability of certain commercial solutions to residential virtual-desktop computing.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Energy & Fuels
Hongyang Zhang, Rui Sun
Summary: By integrating Smart Grid (SG) into Cloud-Fog (CF) technology, it is possible to improve the quality and continuity of power distribution, achieve low delay, great performance, improved safety, and lower operating costs.
Review
Computer Science, Information Systems
Surabhi Kaul, Yogesh Kumar, Uttam Ghosh, Waleed Alnumay
Summary: Nature inspired algorithms play a vital role in solving diverse optimization problems by improving task efficiency and reducing energy consumption and costs. Various computing techniques benefit from these algorithms and have seen significant improvements in results.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Editorial Material
Computer Science, Software Engineering
Hai Jin, Xipeng Shen, Robert Lovas, Xiaofei Liao
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2020)
Article
Computer Science, Software Engineering
Istvan Pintye, Eszter Kail, Peter Kacsuk, Robert Lovas
Summary: The paper discusses reference architectures for big data and machine learning, focusing on the application of Apache Spark cluster, Jupyter framework, and Occopus cloud-agnostic orchestrator tool. The approach has been demonstrated and validated through a text classification application on the Hungarian academic research infrastructure.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Virology
Gabor Kemenesi, Safia Zeghbib, Balazs A. Somogyi, Gabor Endre Toth, Krisztian Banyai, Norbert Solymosi, Peter M. Szabo, Istvan Szabo, Adam Balint, Peter Urban, Robert Herczeg, Attila Gyenesei, Agnes Nagy, Csaba Istvan Pereszlenyi, Gergely Csaba Babinszky, Gabor Dudas, Gabriella Terhes, Viktor Zoldi, Robert Lovas, Szabolcs Tenczer, Laszlo Kornya, Ferenc Jakab
Article
Computer Science, Interdisciplinary Applications
Eniko Nagy, Robert Lovas, Istvan Pintye, Akos Hajnal, Peter Kacsuk
Summary: This paper discusses the importance and application of reference architectures for Big Data, machine learning, and stream processing, focusing on the Apache Spark platform and the cloud-agnostic orchestration tool Occopus. The new generation reference architectures can be configured flexibly according to available resources and cloud providers, supporting multi-cloud deployment, and have been successfully applied in projects at the Hungarian Institute for Political Science.
ADVANCES IN ENGINEERING SOFTWARE
(2021)
Article
Computer Science, Software Engineering
Gabriele Pierantoni, Tamas Kiss, Alexander Bolotov, Dimitrios Kagialis, James DesLauriers, Amjad Ullah, Huankai Chen, David Chan You Fee, Hai-Van Dang, Jozsef Kovacs, Anna Belehaki, Themistocles Herekakis, Ioanna Tsagouri, Sandra Gesing
Summary: Science gateways are widely used to simplify access to distributed computing infrastructures, but creating and deploying gateways remain a challenge. This paper introduces a novel science gateway framework and verifies its feasibility through two scientific case studies.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Information Systems
Bence Ligetfalvi, Mark Emodi, Jozsef Kovacs, Robert Lovas
Summary: The research aims to improve the reliability of cloud-based infrastructures and accelerate the debugging process with minimal user interactions. By introducing a debugging technique called macrostep, the focus of the study is on the behavior of cloud-based infrastructures during their deployment phase.
Article
Chemistry, Analytical
Gabor Szedo Becker, Robert Lovas
Summary: This paper investigates the nonuniformity issues of two CMOS image sensors for machine vision applications and proposes an optimized hardware architecture to compensate for the nonuniformities. It also discusses performance configurations for different application areas and compares different nonuniformity correction approaches.
Article
Computer Science, Information Systems
Attila Csaba Marosi, Mark Emodi, Attila Farkas, Robert Lovas, Richard Beregi, Gianfranco Pedone, Balazs Nemeth, Peter Gaspar
Summary: This work introduces a scalable, cloud-agnostic, and fault-tolerant data analytics platform for state-of-the-art autonomous systems. It is built using open-source reusable building blocks and can process various feeds of structured and non-structured input data from advanced IoT use cases. The platform is currently used in the National Laboratory for Autonomous Systems in Hungary and has been validated through selected use cases.
Article
Computer Science, Information Systems
Attila Csaba Marosi, Mark Emodi, Akos Hajnal, Robert Lovas, Tamas Kiss, Valerie Poser, Jibinraj Antony, Simon Bergweiler, Hamed Hamzeh, James Deslauriers, Jozsef Kovacs
Summary: The use of mature and validated solutions can save time and cost in introducing new technologies. Reference Architectures are increasingly used in cloud-based systems to improve development speed and reliability. This paper explores their application in overcoming challenges in cloud-based application development, and presents a framework and application example.
Proceedings Paper
Computer Science, Artificial Intelligence
Mark Emodi, Jozsef Kovacs, Robert Lovas, Sandor Szensai
Summary: This paper discusses the increasing demand for computing on General-Purpose Graphics Processing Units (GPGPUs) for machine learning. It provides an overview of GPU virtualization strategies and their fundamental details, highlighting the importance of key features and evaluation in choosing an effective baseline framework.
IEEE 15TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI 2021)
(2021)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Simon J. E. Taylor, Anastasia Anagnostou, Nura Tijjani Abubakar, Tamas Kiss, James DesLauriers, Gabor Terstyanszky, Peter Kacsuk, Jozsef Kovacs, Shane Kite, Gary Pattison, James Petry
2020 WINTER SIMULATION CONFERENCE (WSC)
(2020)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Attila Farkas, Gabor Kertesz, Robert Lovas
2020 IEEE 24TH INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES 2020)
(2020)
Editorial Material
Computer Science, Theory & Methods
Kiho Lim, Christian Esposito, Tian Wang, Chang Choi
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Jesus Carretero, Dagmar Krefting
Summary: Computational methods play a crucial role in bioinformatics and biomedicine, especially in managing large-scale data and simulating complex models. This special issue focuses on security and performance aspects in infrastructure, optimization for popular applications, and the integration of machine learning and data processing platforms to improve the efficiency and accuracy of bioinformatics.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Renhao Lu, Weizhe Zhang, Qiong Li, Hui He, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang, Zenglin Xu, Mamoun Alazab
Summary: Federated Learning allows collaborative training of AI models with local data, and our proposed FedAAM scheme improves convergence speed and training efficiency through an adaptive weight allocation strategy and asynchronous global update rules.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Qiangqiang Jiang, Xu Xin, Libo Yao, Bo Chen
Summary: This paper proposes a multi-objective energy-efficient task scheduling technique (METSM) for edge heterogeneous multiprocessor systems. A mathematical model is established for the task scheduling problem, and a problem-specific algorithm (IMO) is designed for optimizing task scheduling and resource allocation. Experimental results show that the proposed algorithm can achieve optimal Pareto fronts and significantly save time and power consumption.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Weimin Li, Lu Liu, Kevin I. K. Wang, Qun Jin
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Mohammed Riyadh Abdmeziem, Amina Ahmed Nacer, Nawfel Moundji Deroues
Summary: Internet of Things (IoT) devices have become ubiquitous and brought the need for group communications. However, security in group communications is challenging due to the asynchronous nature of IoT devices. This paper introduces an innovative approach using blockchain technology and smart contracts to ensure secure and scalable group communications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Robert Sajina, Nikola Tankovic, Ivo Ipsic
Summary: This paper presents and evaluates a novel approach that utilizes an encoder-only transformer model to enable collaboration between agents learning two distinct NLP tasks. The evaluation results demonstrate that collaboration among agents, even when working towards separate objectives, can result in mutual benefits.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Hebert Cabane, Kleinner Farias
Summary: Event-driven architecture has been widely adopted in the software industry for its benefits in software modularity and performance. However, there is a lack of empirical evidence to support its impact on performance. This study compares the performance of an event-driven application with a monolithic application and finds that the monolithic architecture consumes fewer computational resources and has better response times.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Haroon Wahab, Irfan Mehmood, Hassan Ugail, Javier Del Ser, Khan Muhammad
Summary: Wireless capsule endoscopy (WCE) is a revolutionary diagnostic method for small bowel pathology. However, the manual analysis of WCE videos is cumbersome and the privacy concerns of WCE data hinder the adoption of AI-based diagnoses. This study proposes a federated learning framework for collaborative learning from multiple data centers, demonstrating improved anomaly classification performance while preserving data privacy.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Maruf Monem, Md Tamjid Hossain, Md. Golam Rabiul Alam, Md. Shirajum Munir, Md. Mahbubur Rahman, Salman A. AlQahtani, Samah Almutlaq, Mohammad Mehedi Hassan
Summary: Bitcoin, the largest cryptocurrency, faces challenges in broader adaption due to long verification times and high transaction fees. To tackle these issues, researchers propose a learning framework that uses machine learning to predict the ideal block size in each block generation cycle. This model significantly improves the block size, transaction fees, and transaction approval rate of Bitcoin, addressing the long wait time and broader adaption problem.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Rafael Duque, Crescencio Bravo, Santos Bringas, Daniel Postigo
Summary: This paper introduces the importance of user interfaces for digital twins and presents a technique called ADD for modeling requirements of Human-DT interaction. A study is conducted to assess the feasibility and utility of ADD in designing user interfaces, using the virtualization of a natural space as a case study.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Xiulin Li, Li Pan, Wei Song, Shijun Liu, Xiangxu Meng
Summary: This article proposes a novel multiclass multi-pool analytical model for optimizing the quality of composite service applications deployed in the cloud. By considering embarrassingly parallel services and using differentiated parallel processing mechanisms, the model provides accurate prediction results and significantly reduces job response time.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Seongwan Park, Woojin Jeong, Yunyoung Lee, Bumho Son, Huisu Jang, Jaewook Lee
Summary: In this paper, a novel MEV detection model called ArbiNet is proposed, which offers a low-cost and accurate solution for MEV detection without requiring knowledge of smart contract code or ABIs.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Sacheendra Talluri, Nikolas Herbst, Cristina Abad, Tiziano De Matteis, Alexandru Iosup
Summary: Serverless computing is increasingly used in data-processing applications. This paper presents ExDe, a framework for systematically exploring the design space of scheduling architectures and mechanisms, to help system designers tackle complexity.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Chao Wang, Hui Xia, Shuo Xu, Hao Chi, Rui Zhang, Chunqiang Hu
Summary: This paper introduces a Federated Learning framework called FedBnR to address the issue of potential data heterogeneity in distributed entities. By breaking up the original task into multiple subtasks and reconstructing the representation using feature extractors, the framework improves the learning performance on heterogeneous datasets.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
