Review
Computer Science, Hardware & Architecture
Wael Khallouli, Jingwei Huang
Summary: Scheduling plays a crucial role in cloud computing systems, with challenges including multi-dimensional resource demands, job heterogeneity, diversity of computing resources, and fairness among multiple tenants. Using machine learning solutions for resource management is a promising direction for the future of intelligent resource schedulers.
JOURNAL OF SUPERCOMPUTING
(2022)
Review
Computer Science, Interdisciplinary Applications
Abhijeet Mahapatra, Kaushik Mishra, Rosy Pradhan, Santosh Kumar Majhi
Summary: Cloud computing faces issues in resource allocation, task scheduling, and communication latency. To address these challenges, various computing paradigms have emerged and a novel computing architecture that combines these paradigms has been proposed. This article provides a comprehensive overview of these paradigms and outlines future research directions.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Computer Science, Information Systems
Karima Saidi, Dalal Bardou
Summary: There is increasing interest in distributed models for addressing resource allocation issues in Cloud computing environments. Two main approaches include task scheduling and VM-to-Physical Machine mapping. These aspects are closely related to the crucial issue of energy consumption in Cloud computing. A systematic review of recent literature was conducted to analyze the challenges and current state of research, as well as highlight new opportunities and provide guidance for future research in this field. This work aims to advance resource allocation in Cloud computing environments.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Information Systems
Hayder Faeq Alhashimi, M. H. D. Nour Hindia, Kaharudin Dimyati, Effariza Binti Hanafi, Nurhizam Safie, Faizan Qamar, Khairul Azrin, Quang Ngoc Nguyen
Summary: This paper provides a comprehensive review of resource management in 6G HetNets, aiming to give crucial background and propose effective solutions for the challenges in this field. It examines recent work in power allocation, user association, mode selection, and spectrum allocation, and identifies the most severe challenges and proposes suitable solutions. Several open issues and emerging research areas are also highlighted.
Article
Computer Science, Theory & Methods
Yanghua Peng, Yixin Bao, Yangrui Chen, Chuan Wu, Chen Meng, Wei Lin
Summary: In this article, a DL-driven scheduler called DL2 is proposed for DL clusters, which adopts a joint supervised learning and reinforcement learning approach to dynamically adjust resource allocation. The implementation of DL2 on Kubernetes demonstrates superior performance compared to traditional schedulers in terms of average job completion time.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2021)
Article
Computer Science, Information Systems
Xiaoxue Geng, Wenxiao Zhao
Summary: This paper introduces a distributed gradient-free algorithm for solving a distributed resource allocation problem, showing strong convergence and generating estimates close to the optimal solution. The effectiveness of the algorithm is verified through numerical experiments.
SCIENCE CHINA-INFORMATION SCIENCES
(2022)
Article
Engineering, Civil
Xiantao Jiang, F. Richard Yu, Tian Song, Victor C. M. Leung
Summary: In this work, a comprehensive summary of video streaming over VANETs is provided, focusing on challenges such as latency, reliability, and security. The survey covers related works, background knowledge, resource allocation schemes, optimization tools, and enabling technologies for video streaming in VANETs. Challenges and future research directions are also discussed.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Chemistry, Physical
Christoph Wulf, Matthias Beller, Thomas Boenisch, Olaf Deutschmann, Schirin Hanf, Norbert Kockmann, Ralph Kraehnert, Mehtap Oezaslan, Stefan Palkovits, Sonja Schimmler, Stephan A. Schunk, Kurt Wagemann, David Linke
Summary: Modern research methods generate significant scientific data, but access to high-quality data remains limited in many fields. Implementing the FAIR data concept in the catalysis community could dramatically improve this situation. The German NFDI initiative aims to establish a comprehensive research data infrastructure across all scientific disciplines.
Review
Computer Science, Information Systems
Wanying Guo, Nawab Muhammad Faseeh Qureshi, Isma Farah Siddiqui, Dong Ryeol Shin
Summary: This paper provides a review on cooperative communication resource allocation techniques in 5G networks. It discusses strategies, core technologies, network models, and resource allocation algorithms. The review systematically organizes relevant insights and presents a comprehensive discussion on the applications and challenges of cooperative communication in 5G networks.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Jianhua Liu, Xin Wang, Shigen Shen, Guangxue Yue, Shui Yu, Minglu Li
Summary: In this article, interactions between a sensor device-edgeVM pair and a DDoS attacker are investigated using a game-theoretic framework, under the constraints of task time, resource budget, and incomplete knowledge of machine learning tasks processing time. A Bayesian Q-learning game is used to model the strategic resource allocation problem between the sensor device-edgeVM pair and the attacker, and a greedy Q-learning algorithm is proposed for dependable resource allocation against DDoS attacks. Numerical simulation results show the superiority of the proposed mechanism in the sensor edge cloud under incomplete information for DDoS attacks.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Lei Zhang, Hu Xiong, Qiong Huang, Jiguo Li, Kim-Kwang Raymond Choo, Jiangtao Li
Summary: This paper provides a critique of cryptographic schemes designed for securing sensitive data in the cloud computing environment, as well as outlining research opportunities in the use of cryptographic techniques in cloud computing.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Review
Computer Science, Hardware & Architecture
Mallikarjun Reddy Dorsala, V. N. Sastry, Sudhakar Chapram
Summary: The paper surveys literature on Blockchain-based cloud services and explores how Blockchain technology enhances reliability and transparency in cloud computing. The literature is classified into three categories, investigating various areas including Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service. The authors believe this survey will aid in reengineering cloud data centers in the future.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Article
Chemistry, Analytical
Rickson Pereira, Azzedine Boukerche, Marco A. C. da Silva, Luis H. Nakamura, Heitor Freitas, Geraldo P. Rocha Filho, Rodolfo Meneguette
Summary: Intelligent Transport Systems aim to improve transportation quality for a more comfortable and safer trip. Mobile clouds can assist in handling resource management, yet the high mobility and dynamic topology of vehicular networks pose challenges. By proposing a mechanism based on FOGs, a more balanced allocation of resources to provide a higher number of services has been achieved.
Article
Computer Science, Artificial Intelligence
Parsi Kalpana, S. Nagendra Prabhu, Vijayakumar Polepally, D. B. Jagannadha Rao
Summary: This paper introduces a novel resource allocation technique, combining Exponential Weighted Moving Average and Spider Monkey Optimization algorithm, to achieve more efficient utilization of cloud resources and cost control. The technique also includes a server switching model to reduce power consumption by switching servers when resources are idle.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Brice Ekane, Tu Dinh Ngoc, Boris Teabe, Daniel Hagimont, Noel De Palma
Summary: This paper introduces a mechanism called FlexVF, which dynamically allocates and switches between VFs and paravirtualized networking based on network activity monitoring, improving VM network performance by 75% without affecting network operation.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Review
Computer Science, Information Systems
Guto Leoni Santos, Diego de Freitas Bezerra, Elisson da Silva Rocha, Leylane Ferreira, Andre Luis Cavalcanti Moreira, Glauco Estacio Goncalves, Maria Valeria Marquezini, Akos Recse, Amardeep Mehta, Judith Kelner, Djamel Sadok, Patricia Takako Endo
Summary: This paper provides a systematic review of SFC placement advances in distributed scenarios, examining works from the past decade and focusing on deployment strategies in distributed scenarios.
JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT
(2022)
Article
Computer Science, Information Systems
Assis T. de Oliveira Filho, Eduardo Freitas, Pedro R. X. do Carmo, Djamel H. J. Sadok, Judith Kelner
Summary: This paper evaluates the overhead of deploying Virtual Network Functions and using network active measurement tools, and discovers that parameters have different impacts on Round-Trip Time (RTT) and their effects change according to combinations. The results can help Cloud administrators understand the impact of virtualization technologies and related factors on network performance.
COMPUTER COMMUNICATIONS
(2022)
Article
Energy & Fuels
Andrea Maria N. C. Ribeiro, Pedro Rafael X. do Carmo, Patricia Takako Endo, Pierangelo Rosati, Theo Lynn
Summary: This study investigates various models for predicting energy consumption in warehouses, including machine learning and deep learning methods. The results show that the XGBoost model performs best for short-term energy consumption forecasting, while the ARIMA model performs the worst.
Article
Computer Science, Information Systems
Guto Leoni Santos, Pierangelo Rosati, Theo Lynn, Judith Kelner, Djamel Sadok, Patricia Takako Endo
Summary: The study compared the performance of deep learning and traditional machine learning methods in predicting mobile Internet traffic, finding that DL models outperformed ML models, with LSTM performing better than GRU. Variations in performance were observed across different clusters within the city.
INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT
(2022)
Article
Computer Science, Information Systems
Iago Richard Rodrigues, Gibson Barbosa, Assis Oliveira Filho, Carolina Cani, Marrone Dantas, Djamel H. Sadok, Judith Kelner, Ricardo Silva Souza, Maria Valeria Marquezini, Silvia Lins
Summary: This study introduces an intelligent system to address safety issues in human-robot collaboration using deep and machine learning techniques. The system consists of two modules: collision detection and worker's clothing detection, which were evaluated separately, showing high efficiency in supporting safe human-robot collaboration.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Automation & Control Systems
Iago Richard Rodrigues, Gibson Barbosa, Assis Oliveira Filho, Carolina Cani, Djamel H. Sadok, Judith Kelner, Ricardo Souza, Maria Valeria Marquezini, Silvia Lins
Summary: Human-robot collaboration is becoming more common in modern daily activities and a new mechanism for detecting collisions is proposed. Using deep learning models and ensemble learning system, the proposed system can effectively detect collisions with an average accuracy of 89.81% in a well-controlled environment.
JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS
(2022)
Article
Robotics
Djamel Sadok, Daniel Bezerra, Marrone Dantas, Gabriel Reis, Pedro Leuchtenberg, Carolina Ledebour, Ricardo Souza, Silvia Lins, Maria Marquezini, Judith Kelner
Summary: This work presents the development of RBOT, a robot-driven radio base station maintenance system, aimed at reducing maintenance costs and addressing challenges in 5G microcell deployment and maintenance tasks. The system operates based on a robotic arm on the RBS front plane and utilizes convolutional neural networks for faulty cable classification and manipulation.
INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS
(2022)
Correction
Robotics
Djamel Sadok, Daniel Bezerra, Marrone Dantas, Gabriel Reis, Pedro Leuchtenberg, Carolina Ledebour, Ricardo Souza, Silvia Lins, Maria Marquezini, Judith Kelner
INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Elisson da Silva Rocha, Patricia Takako Endo
Summary: This study compares four segmentation algorithms for dental segmentation in panoramic radiograph and evaluates their results. The DoubleU-Net model performs the best with 96.591% accuracy and 92.886% Dice using the dataset with data augmentation. The Nano-Net model also achieves results close to the literature without data augmentation.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Hardware & Architecture
Diego de Freitas Bezerra, Victor Wanderley Costa de Medeiros, Glauco Estacio Goncalves
Summary: The popularization of the Internet of Things has brought about different monitoring and control solutions in various economic sectors. In the field of agriculture, this technology has enabled the monitoring of essential environmental variables and the control of devices to meet crop requirements, thereby increasing productivity. This study presents the development of an agricultural greenhouse controller using Discrete Event System techniques, which includes self-configuring mechanisms and prevents conflicting rules from violating control objectives. The controller was validated through simulation and achieved thermal comfort for crops under different control scenarios, while also providing increased energy efficiency compared to other approaches.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2022)
Review
Computer Science, Information Systems
Eduardo Freitas, Assis T. de Oliveira Filho, Pedro R. X. do Carmo, Djamel Sadok, Judith Kelner
Summary: The path a packet takes in the Linux Kernel has been established for a long time, but with the introduction of new paradigms, complexity has increased. Fast Packet Processing Frameworks have emerged to solve the issues of low delay and high bandwidth services. However, each technology provides different methods and solutions, leading to different benefits and trade-offs. This work proposes a taxonomy to classify these solutions into hardware, software, and virtualization categories, and evaluates their applicability in real-world scenarios based on four criteria.
COMPUTER COMMUNICATIONS
(2022)
Article
Automation & Control Systems
Gibson Barbosa, Marrone Dantas, Assis Tiago de Oliveira Filho, Iago Richard Rodrigues, Daniel Bezerra, Djamel Sadok, Judith Kelner, Ricardo Souza
Summary: Intelligent industry and IoT rely on sensors for monitoring and information exchange. Deploying more sensors in an environment offers additional benefits, but managing the large amounts of data and multiple input sources requires significant resources. This work proposes a fuzzy scheduler that evaluates processing and accuracy levels in a Multi-Agent System environment to determine the relevance of each agent and improve service level metrics.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Patricia Takako Endo, Guto Leoni Santos, Maria Eduarda de Lima Xavier, Gleyson Rhuan Nascimento Campos, Luciana Conceicao de Lima, Ivanovitch Silva, Antonia Egli, Theo Lynn
Summary: Public health interventions during the COVID-19 pandemic have led to increased use of the Internet for health information, but also increased the spread of false information. In Brazil, fake news about COVID-19 vaccines, particularly related to government communications, was prevalent. Machine learning and deep learning techniques can be used to identify fake news in Brazilian Portuguese online communications, and analyzing stop words within the messages can improve the performance of the models. Random Forest achieved the best results among the machine learning models, while Bi-GRU was the best deep learning model.
BIG DATA AND COGNITIVE COMPUTING
(2022)
