Article
Chemistry, Analytical
Xavi Masip-Bruin, Eva Marin-Tordera, Sergi Sanchez-Lopez, Jordi Garcia, Admela Jukan, Ana Juan Ferrer, Anna Queralt, Antonio Salis, Andrea Bartoli, Matija Cankar, Cristovao Cordeiro, Jens Jensen, John Kennedy
Summary: The cloud continuum, formed by the combination of fog computing, edge computing, and cloud computing, requires novel management strategies to coordinate and efficiently manage resources from the edge to the cloud. This management framework design poses various research challenges and has spurred many global initiatives.
Review
Computer Science, Information Systems
Elham Fazel, Hamid Esmaeili Najafabadi, Mohammad Rezaei, Henry Leung
Summary: Fog computing enables real-time information processing on the native net, while Mist Computing principles are not mature enough for practical use. Clustering methods for fog nodes can address limitations in device resources, but challenges remain in developing real-time applications and implementing collaborative clustering techniques on IoT-mist networks.
INTERNET OF THINGS
(2023)
Review
Chemistry, Analytical
Yogeswaranathan Kalyani, Rem Collier
Summary: Cloud Computing has limitations in ultra-low latency, high bandwidth, security, and real-time analytics when dealing with large amounts of data, where Fog and Edge Computing offer solutions. The use of Cloud, Fog, and Edge in smart agriculture applications is increasing, with this article aiming to review current works in this area. The review identifies relevant research, proposes a new architecture model, and discusses components, communication protocols, challenges, and future research directions in smart agriculture.
Article
Computer Science, Hardware & Architecture
Shehenaz Shaik, Sanjeev Baskiyar
Summary: The fog computing paradigm is a solution for deploying large-scale Internet of Things environments and low-latency real-time services. It utilizes compute nodes distributed across vast geographical areas and closer to users and data sources compared to the cloud. Efficient placement of services is crucial in infrastructure environments with both cloud and fog nodes to satisfy resource requirements and improve performance.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2022)
Article
Computer Science, Information Systems
Quy Vu Khanh, Nam Vi Hoai, Anh Dang Van, Quy Nguyen Minh
Summary: History has shown that healthcare and medical systems are crucial for the advancement of science and technology. In the past decades, there has been an explosive growth of ehealth applications, with cloud computing dominating e-healthcare systems and various domains. However, the high response time of cloud-based e-health systems presents a primary barrier.
INTERNET OF THINGS
(2023)
Article
Chemistry, Analytical
Ahmed M. Alwakeel
Summary: With the advancement of technologies, cloud computing becomes essential. Fog computing and edge computing are emerging cloud technologies aiming to simplify complexities of cloud computing and utilize local network computing capabilities. However, using these technologies introduces security and privacy challenges which require countermeasures to mitigate their impact.
Review
Computer Science, Information Systems
Gunjan Beniwal, Anita Singhrova
Summary: This paper presents a systematic literature review of IoT gateways, specifically focusing on smart gateways. The review categorizes gateways into basic and smart types, with smart gateways further divided into passive, semi-automated, and fully-automated categories. The paper analyzes 67 selected articles out of 2347 based on well-defined criteria, providing comprehensive insights into the working and functionalities of IoT gateways. The review identifies research gaps, open issues, and suggests future prospects for advanced research.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Review
Computer Science, Information Systems
Amjad Ullah, Tamas Kiss, Jozsef Kovacs, Francesco Tusa, James Deslauriers, Huseyin Dagdeviren, Resmi Arjun, Hamed Hamzeh
Summary: IoT systems have become essential in various domains, leading to the need for Cloud-to-Things computing. In recent years, there has been significant attention on the development of orchestration systems. This paper gathers research in this field, proposing a taxonomy and conceptual framework to analyze existing work.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2023)
Article
Automation & Control Systems
Juan Wang, Di Li, Yueming Hu
Summary: This article proposed a fog nodes deployment strategy based on space-time characteristics (TSBP) to minimize computing response time and achieve load balancing for intelligent manufacturing systems. By using the discrete differential evolution algorithm, the optimal fog nodes deployment solution was searched and validated on a candy packaging intelligent production line prototype platform.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Chemistry, Analytical
Adrian Orive, Aitor Agirre, Hong-Linh Truong, Isabel Sarachaga, Marga Marcos
Summary: The fast growth in the amount of connected devices has enabled the emergence of Edge computing, which provides lower latencies compared to Cloud computing. Combining Cloud and Edge computing can meet the quality of service requirements for complex applications. However, orchestrating applications in the Cloud-Edge computing faces new challenges that need to be solved to fully utilize this layered infrastructure. This paper proposes an architecture that dynamically orchestrates applications in the Cloud-Edge continuum, focusing on the application's quality of service.
Article
Automation & Control Systems
Lulu Chen, Zhihui Lu, Ai Xiao, Qiang Duan, Jie Wu, Patrick C. K. Hung
Summary: This paper proposes an ORHRC model that utilizes machine learning techniques to provide resource configuration recommendations for heterogeneous workloads in a fog computing-based smart factory environment. The model learns a recommendation model by leveraging the characteristics and execution time of workloads on fog servers with different configurations, and outperforms state-of-the-art methods in terms of average prediction accuracy.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Sergio Moreschini, Fabiano Pecorelli, Xiaozhou Li, Sonia Naz, David Hastbacka, Davide Taibi
Summary: This work conducts a systematic mapping study of the literature on the concept of cloud continuum, investigating the different definitions and how they have evolved. The main outcome is a complete definition that merges all the common aspects of cloud continuum, providing practitioners and researchers with a better understanding of what it is.
Review
Computer Science, Information Systems
Shahnawaz Ahmad, Iman Shakeel, Shabana Mehfuz, Javed Ahmad
Summary: Deep learning has become the Gold Standard in machine learning, achieving remarkable results in various complex cognitive tasks. However, the bottleneck of cloud computing arises due to the enormous data produced by IoT applications and the need for quick response time and enhanced privacy. The latest trend is to move data processing and analytics to the network edge using a decentralized distributed architecture, and utilize machine learning to improve efficiency and security.
COMPUTER SCIENCE REVIEW
(2023)
Article
Computer Science, Hardware & Architecture
Shehenaz Shaik, Jacob Hall, Clayton Johnson, Qian Wang, Robert Sharp, Sanjeev Baskiyar
Summary: This paper introduces a new simulator called PFogSim, which is developed to test fog computing configurations of various sizes with fog nodes distributed over large geographical areas and interconnected over one or more network links. PFogSim allows for a multi-layered fog environment design and enables testing of fog nodes and network links of different capacities.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2022)
Article
Computer Science, Hardware & Architecture
Ming-Tuo Zhou, Tian-Feng Ren, Zhi-Ming Dai, Xin-Yu Feng
Summary: By proposing a fog computing framework and an improved genetic scheduling algorithm, it is possible to optimize the scheduling and resource allocation of tasks in smart factories, leading to improved production efficiency.
MOBILE NETWORKS & APPLICATIONS
(2023)
Article
Chemistry, Analytical
Iure Fe, Rubens Matos, Jamilson Dantas, Carlos Melo, Tuan Anh Nguyen, Dugki Min, Eunmi Choi, Francisco Airton Silva, Paulo Romero Martins Maciel
Summary: This paper proposes a modeling method for auto-scaling mechanisms in cloud infrastructure using a stochastic Petri net, and adopts an adaptive search metaheuristic algorithm to discover critical trade-offs between performance and cost. The research results demonstrate the feasibility of this method in practice and its ability to help achieve optimized-quality solutions and operational management for cloud services.
Article
Chemistry, Analytical
Francisco Airton Silva, Carlos Brito, Gabriel Araujo, Iure Fe, Maxim Tyan, Jae-Woo Lee, Tuan Anh Nguyen, Paulo Romero Martin Maciel
Summary: This study focuses on modeling the reliability and availability of medical computing infrastructure during the COVID-19 pandemic, proposing reliability and availability models using stochastic Petri net (SPN). Analysis results show that different configurations in smart hospitals have varying impacts on the operational availability of medical sensor networks, with configuration C achieving the highest availability of 99.64%.
Article
Engineering, Electrical & Electronic
Francisco Airton Silva, Iure Fe, Carlos Brito, Gabriel Araujo, Leonel Feitosa, Eunmi Choi, Dugki Min, Tuan Anh Nguyen
Summary: The Internet of Things (IoT) is playing an increasingly important role in ensuring security and well-being, especially in homes and buildings. However, evaluating IoT architectures is crucial due to the complexity and fault-prone nature of sensor networks. This paper proposes a continuous time Markov chain (CTMC) model and presents an improved solution for system availability and downtime based on sensitivity analysis.
ELECTRONICS LETTERS
(2022)
Article
Computer Science, Hardware & Architecture
Tuan Anh Nguyen, Minjune Kim, Jangse Lee, Dugki Min, Jae-Woo Lee, Dongseong Kim
Summary: This paper presents a comprehensive modeling and analysis of time-based switch-over MTD strategies deployed in a SDN, and explores the impact of MTD strategies on system performability metrics. The study can assist in designing and planning the development and adoption of MTD strategies, considering the trade-offs between security and performability assurance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Rubenilson de Sousa, Leonardo Cristian, Leonel Feitosa, Eunmi Choi, Tuan Anh Nguyen, Dugki Min, Francisco Airton Silva
Summary: In the field of urban air mobility (UAM), video streaming platforms have attracted attention from media companies due to their increasing demand for on-demand video streaming services during flights. The availability and performance of the back-end video streaming infrastructure are crucial to provide a satisfactory user experience. Analytical models, such as stochastic Petri nets (SPNs), can be used to evaluate video-on-demand architectures in a cost-effective manner.
APPLIED SCIENCES-BASEL
(2023)
Article
Remote Sensing
Jackson Costa, Rubens Matos, Jean Araujo, Jueying Li, Eunmi Choi, Tuan Anh Nguyen, Jae-Woo Lee, Dugki Min
Summary: To ensure the smooth operation and control of urban air mobility (UAM), it is necessary to develop an accurate vehicle digital twin (DT) that can model the statics and dynamics of the vehicle. However, issues such as the lack of digital twin engines, back-end system engineering, and fault-tolerant mechanisms need to be addressed for effective UAM management.
Proceedings Paper
Engineering, Aerospace
Hyungeun Jo, Hoeun Lee, Sangwoo Jeon, Vishnu Kumar Kaliappan, Tuan Anh Nguyen, Dugki Min, Jae-Woo Lee
Summary: With recent technological developments, the value and usefulness of the UAS (unmanned aerial system) have been recognized in various fields. This study proposes the improved Multi-Actor-Attention-Critic (iMAAC) approach, a modified multi-agent reinforcement learning method for urban air mobility logistic services. A virtual simulation environment based on Unity is created to validate the suggested method, and the results show a higher learning rate compared to other landmark reinforcement algorithms when utilized in multi-agent systems.
PROCEEDINGS OF THE 2021 ASIA-PACIFIC INTERNATIONAL SYMPOSIUM ON AEROSPACE TECHNOLOGY (APISAT 2021), VOL 2
(2023)
Proceedings Paper
Engineering, Aerospace
Vishnu Kumar Kaliappan, Tuan Anh Nguyen, Sang Woo Jeon, Jae-Woo Lee, Dugki Min
Summary: Enhancing intelligence in the development of UAVs and applying swarm fleets in urban applications without human intervention is the focus of this paper. The proposed B-DMARL framework utilizes AI-based bio-inspired algorithms and reinforcement learning methods to achieve group coordination, collision avoidance and task execution in dynamic environments. Simulation results show that the proposed methods have improved learning rate and reward signal.
PROCEEDINGS OF THE 2021 ASIA-PACIFIC INTERNATIONAL SYMPOSIUM ON AEROSPACE TECHNOLOGY (APISAT 2021), VOL 2
(2023)
Article
Chemistry, Analytical
Luis Guilherme Silva, Israel Cardoso, Carlos Brito, Vandirleya Barbosa, Bruno Nogueira, Eunmi Choi, Tuan Anh Nguyen, Dugki Min, Jae Woo Lee, Francisco Airton Silva
Summary: This paper proposes a novel method to evaluate VANET-based Vehicle Communication and Control (VCC) architectures, which uses stochastic elements to mirror VANET scenarios, enhancing network robustness and dependability.
Proceedings Paper
Engineering, Aerospace
Tuan Anh Nguyen, Vishnu Kumar Kaliappan, Sangwoo Jeon, Kwon-Su Jeon, Jae-Woo Lee, Dugki Min
Summary: The recent emergence of advanced computing technologies, such as digital twin technology, edge computing, federated learning, and blockchain, has opened up possibilities for the development of urban air mobility (UAM). This study proposes a comprehensive integrated UAM-DT platform called BlockFE-DT, which combines the principles of probabilistic graphical models, federated learning, blockchain, and edge computing. The integration of these technologies is important for the development of UAM-DT systems and addresses key issues such as explainable AI, dependability, and security.
PROCEEDINGS OF THE 2021 ASIA-PACIFIC INTERNATIONAL SYMPOSIUM ON AEROSPACE TECHNOLOGY (APISAT 2021), VOL 2
(2023)
Article
Engineering, Aerospace
Maxim Tyan, Cheol-Kyun Choi, Tuan Anh Nguyen, Jae-Woo Lee
Summary: A deep-learning based algorithm, DL-RED, is developed for solving engineering inverse design problems. The algorithm generates an inverse design deep neural network (IDNN) through hyperparameter selection and training database enhancement. The accuracy and training time are improved by configuring IDNN and iteratively refining the database. The construction of an Airfoil-IDNN is demonstrated, which can generate NACA 4-series airfoils based on target aerodynamic parameters. Two case studies confirm the accuracy of Airfoil-IDNN in generating airfoils with arbitrary parameters and existing airfoils.
INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES
(2023)
Proceedings Paper
Automation & Control Systems
Minseok Jang, Jeongseok Hyun, Taeho Kwag, Chan Gwale, Chanyoung Jeong, Tuan Anh Nguyen, Jae-Woo Lee
Summary: This study proposes a new control framework, called es-DNLC, which uses a deep neural network and exponentially stabilizing control Lyapunov functions for attitude stabilization of a personal aerial vehicle. Experimental results show that es-DNLC can provide higher robustness against disturbances and aerodynamic uncertainties compared to the traditional linear quadratic regulator.
2022 22ND INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2022)
(2022)
Proceedings Paper
Computer Science, Information Systems
Tuan Anh Nguyen, Dugki Min, Eunmi Choi, Iure Fe, Francisco Airton Silva
Summary: This study proposes a hierarchical model to model and evaluate the survivability and resilience of Industrial Internet of Things (IoIT) in order to assist system managers in ensuring the maximum level of survivability and resiliency of industrial processes in smart factories.
2022 IEEE CLOUD SUMMIT
(2022)
Proceedings Paper
Computer Science, Information Systems
Gabriel Araujo, Carlos Brito, Leonel Correia, Tuan Anh Nguyen, Jae Woo Lee, Francisco Airton Silva
Summary: Mobile games are highly popular among young people, especially during the Covid-19 pandemic. The use of edge computing resources is essential in the game industry to ensure non-delayed data transactions. This study proposes a closed queuing network model to evaluate the performance of game execution in mobile edge computing systems. The results show that the number of physical and virtual machines have a similar impact on overall system performance, and making small calibrations to the resources can prevent message loss.
PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND SERVICES SCIENCE (CLOSER)
(2022)
Article
Automation & Control Systems
Vishnu Kumar Kaliappan, Tuan Anh Nguyen, Dugki Min, Jae-Woo Lee, U. Sakthi
Summary: In recent years, there has been a rapid increase in the use of rotorcraft-based unmanned aerial vehicles (RUAV). Researchers have focused on integrating bioinspired techniques to improve intelligence and coordination among multiple RUAVs. Due to limitations in intelligence, these RUAVs can only fly at low altitudes with high maneuverability. To overcome this limitation, it is necessary to develop an advanced intelligent control algorithm that can avoid low altitude obstacles and coordinate flight without collision. This paper proposes an Artificial Intelligence (AI) based steering behavior algorithm that generates a smooth trajectory by avoiding both static and dynamic obstacles. The proposed algorithm is validated using a PC104 embedded board-based HIL (Hardware in the Loop) simulation environment, and is evaluated in various scenarios involving static and dynamic obstacles.
INTELLIGENT AUTOMATION AND SOFT COMPUTING
(2022)
