Article
Computer Science, Hardware & Architecture
Jose Santos, Tim Wauters, Bruno Volckaert, Filip De Turck
Summary: In the context of Smart Cities, Fog Computing serves as the theoretical foundation for distributed cloud infrastructure, although its acceptance is still in early stages. Low Power Wide Area Networks (LPWANs) show great potential but face challenges in deployment and management. A new IoT service allocation problem formulation, considering SFC concepts and various LPWAN technologies, is proposed in this article.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2021)
Review
Computer Science, Theory & Methods
Yaser Mansouri, M. Ali Babar
Summary: This article discusses the challenges faced by cloud computing paradigms in the era of IoT and the emergence of edge computing paradigms to address these challenges. It emphasizes the importance of virtualization techniques and factors influencing the selection of virtualization types in IoT frameworks. The research also compares state-of-the-art studies in the IoT domain and investigates the performance of deploying virtualized computing and networking resources in an edge-cloud environment.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2021)
Article
Computer Science, Information Systems
Phu Lai, Qiang He, John Grundy, Feifei Chen, Mohamed Abdelrazek, John Hosking, Yun Yang
Summary: Edge computing offers lower end-to-end latency and enables real-time, latency-sensitive applications to be deployed on servers closer to end-users. This article focuses on the cost-effectiveness of user allocation solutions, aiming to maximize the number of users allocated to edge servers and minimize the required number of servers to reduce operating costs. A heuristic approach is proposed to efficiently find sub-optimal solutions to large-scale user allocation problems.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Mathematics
Tariq Ahamed Ahanger, Fadl Dahan, Usman Tariq, Imdad Ullah
Summary: IoT-Edge-Fog Computing proposes a decentralized computing model for time-sensitive tasks. However, task allocation among dispersed Edge Computing nodes remains a challenge with existing techniques. This study presents a Quantum Computing-inspired optimization technique for efficient task allocation in an Edge Computing environment and employs a QC-Neural Network Model for predicting optimal computing nodes. Simulations with 6, 10, 14, and 20 Edge nodes were conducted, showing a 5.02% improvement in prediction efficiency and a 2.03% error reduction compared to state-of-the-art techniques.
Article
Computer Science, Information Systems
Binayak Kar, Widhi Yahya, Ying-Dar Lin, Asad Ali
Summary: The diverse computing paradigms of cloud, edge, and fog are needed to handle the vast amount of data generated by IoT devices. However, each paradigm has its own advantages and limitations. Cloud computing provides high computational power and storage capacity but suffers from high latency. Edge and fog computing offer lower latency but with limited capacity and coverage. A federation between these paradigms is required to meet the requirements of IoT devices and optimize traffic offloading.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)
Review
Computer Science, Information Systems
Ronita Rezapour, Parvaneh Asghari, Hamid Haj Seyyed Javadi, Shamsollah Ghanbari
Summary: This paper conducts a comprehensive study on the security challenges in fog computing and different approaches to address them using the Systematic Literature Review (SLR) approach. It offers a technical taxonomy for fog security challenges and strategies in terms of six aspects, and classifies existing research techniques and available solutions in fog computing from 2014 to 2021. The study also discusses the strengths and weaknesses of each indicated fog security approach and provides future motivational directions and open issues in this field.
COMPUTER SCIENCE REVIEW
(2021)
Article
Computer Science, Artificial Intelligence
Carlos Guerrero, Isaac Lera, Carlos Juiz
Summary: Fog computing, as a new computational paradigm, has emerged to reduce network usage and latency in the IoT. This paper provides a comprehensive review of recent research works on genetic-based fog resource optimization. The authors propose a taxonomy for optimizing fog infrastructures and classify 70 papers accordingly. They evaluate the papers based on their genetic optimization design and outline the benefits and limitations of each work. The study concludes that more research efforts are needed to address current challenges and improve the design and deployment of genetic algorithms in fog domains.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Information Systems
Neetu Raveendran, Huaqing Zhang, Lingyang Song, Li-Chun Wang, Choong Seon Hong, Zhu Han
Summary: The number of devices connected to the Internet of Things (IoT) is growing rapidly globally. To meet the heterogeneous needs of the fifth generation (5G) networks, an integrated network function virtualization (NFV) and fog computing resource allocation framework is crucial for IoT.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Chemistry, Analytical
Rayan A. Alsemmeari, Mohamed Yehia Dahab, Badraddin Alturki, Abdulaziz A. Alsulami, Raed Alsini
Summary: This paper addresses the challenges of resource allocation and service allocation in the Internet of Things (IoT) and proposes priority-based and sort-based service allocation techniques. Experimental results show that these techniques can reduce data communication and minimize fog resource wastage while maintaining resource utilization.
Article
Computer Science, Information Systems
Omar Rafik Merad-Boudia, Sidi Mohammed Senouci
Summary: ESMA is an efficient and secure multi-dimensional data aggregation scheme that encrypts data into a single Paillier ciphertext for improved efficiency. It adopts the Paillier cryptosystem in a fog computing architecture for privacy protection and utilizes batch verification technique for efficient authentication. Furthermore, ESMA is fault tolerant and can adapt to various types of queries, providing performance analysis on cost efficiency, scalability, and resistance to security attacks.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Omed Hassan Ahmed, Joan Lu, Qiang Xu, Aram Mahmood Ahmed, Amir Masoud Rahmani, Mehdi Hosseinzadeh
Summary: This paper introduces an opposition-based hybrid discrete optimization algorithm, DMFO-DE, for scheduling scientific workflows in fog computing environments to optimize energy consumption and improve performance.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Anna-Valentini Michailidou, Anastasios Gounaris, Moysis Symeonides, Demetris Trihinas
Summary: Our work aims to address the increasing demand for performing complex analytics jobs close to edge devices, while considering data quality as an optimization objective. We propose a hybrid solution that improves global task allocation by trading off latency and extent of quality checks, showing significant improvement over existing solutions in experimental evaluations.
INFORMATION SYSTEMS
(2022)
Article
Automation & Control Systems
Lokman Altin, Haluk Rahmi Topcuoglu, Fikret Sadik Gurgen
Summary: This study presents a multi-objective task scheduling model and algorithm for fog computing, incorporating two task clustering mechanisms to reduce data transfer costs. Empirical evaluations validate the effectiveness of the proposed algorithm and the importance of the integrated extensions.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Faisal Haider, Decheng Zhang, Marc St-Hilaire, Christian Makaya
Summary: The paper proposes an exact model for planning and designing fog networks, aiming to minimize network delay and traffic sent to the cloud center through three optimization techniques: weighted sum, hierarchical, and trade-off methods. Computational results show an increase in delay, traffic, and solution time as the problem size increases, with the weighted sum method achieving the best trade-off results for delay and traffic.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2021)
Article
Computer Science, Information Systems
Seyedeh Negar Afrasiabi, Amin Ebrahimzadeh, Carla Mouradian, Sepideh Malektaji, Roch H. H. Glitho
Summary: In this paper, a component migration strategy in an NFV-based hybrid cloud/fog system is proposed, taking into account the mobility of both end-users and fog nodes. The problem is mathematically modeled and a deep reinforcement learning approach is proposed to achieve rapid decision-making. Simulation results show that the proposed scheme performs well and outperforms existing algorithms in terms of application delay and migration costs.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Gianmarco Garrisi, Cristina Cervello-Pastor
Article
Chemistry, Multidisciplinary
Miranda McClellan, Cristina Cervello-Pastor, Sebastia Sallent
APPLIED SCIENCES-BASEL
(2020)
Article
Computer Science, Hardware & Architecture
Irian Leyva-Pupo, Cristina Cervello-Pastor
Summary: This study addresses the placement and chaining problem of 5G User Plane Functions in a Multi-access Edge Computing environment by formulating a multi-objective ILP model and introducing two heuristic solutions for enhancing solution efficiency.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2022)
Article
Chemistry, Analytical
Alejandro Llorens-Carrodeguas, Stefanos G. Sagkriotis, Cristina Cervello-Pastor, Dimitrios P. Pezaros
Summary: This study proposes a scheduler optimized for energy-constrained SBC clusters, achieving fewer event rejections, less deadline violations, and a significant reduction in energy consumption across the cluster compared to existing schedulers.
Article
Chemistry, Analytical
Alejandro Llorens-Carrodeguas, Irian Leyva-Pupo, Cristina Cervello-Pastor, Luis Pineiro, Shuaib Siddiqui
Summary: This paper investigates dynamic scaling and load balancing of transparent virtualized network functions (VNFs) and proposes a SDN-based solution. Through experiments, the feasibility of the solution was validated, showing that SDN controllers and OFS offer flexibility to implement various strategies for load balancing, scaling, and monitoring.
Article
Computer Science, Hardware & Architecture
Irian Leyva-Pupo, Cristina Cervello-Pastor, Christos Anagnostopoulos, Dimitrios P. Pezaros
Summary: This paper addresses the problem of dynamic user plane function placement and chaining reconfiguration (UPCR) in a MEC environment to cope with user mobility while guaranteeing cost reductions and acceptable quality of service (QoS). The proposed heuristic algorithm, dynamic priority and cautious UPCR (DPC-UPCR), provides near-optimal solutions within significantly shorter times than the mathematical model. Additionally, the scheduling mechanism based on optimal stopping theory outperforms baseline solutions in terms of the number of reconfiguration events and QoS levels.
Article
Computer Science, Hardware & Architecture
Alejandro Llorens-Carrodeguas, Cristina Cervello-Pastor, Francisco Valera
Summary: This paper addresses the deployment of virtual network functions using single-board computers (SBCs) in a multi-cluster system. It proposes an intelligent controller based on deep reinforcement learning to optimize energy consumption and resource utilization in SBCs.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Telecommunications
Leonardo Ochoa-Aday, Cristina Cervello-Pastor, Adriana Fernandez-Fernandez
DIGITAL COMMUNICATIONS AND NETWORKS
(2020)
Correction
Computer Science, Information Systems
Alejandro Santoyo-Gonzalez, Cristina Cervello-Pastor
Article
Computer Science, Information Systems
Ivan Vidal, Borja Nogales, Francisco Valera, Luis F. Gonzalez, Victor Sanchez-Aguero, Eduardo Jacob, Cristina Cervello-Pastor
Article
Computer Science, Information Systems
Alejandro Santoyo-Gonzalez, Cristina Cervello-Pastor
Proceedings Paper
Computer Science, Hardware & Architecture
Irian Leyva-Pupo, Cristina Cervello-Pastor, Alejandro Llorens-Carrodeguas
WIRED/WIRELESS INTERNET COMMUNICATIONS, WWIC 2019
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Irian Leyva-Pupo, Cristina Cervello-Pastor, Alejandro Llorens-Carrodeguas
DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Alejandro Llorens-Carrodeguas, Cristina Cervello-Pastor, Irian Leyva-Pupo
DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE
(2019)
Article
Computer Science, Information Systems
Leonardo Ochoa-Aday, Cristina Cervello-Pastor, Adriana Fernandez-Fernandez
Article
Computer Science, Hardware & Architecture
Zihang Zhen, Xiaoding Wang, Hui Lin, Sahil Garg, Prabhat Kumar, M. Shamim Hossain
Summary: In this paper, a blockchain architecture based on dynamic state sharding (DSSBD) is proposed to solve the problems caused by cross-shard transactions and reconfiguration. By utilizing deep reinforcement learning, the number of shards, block spacing, and block size can be dynamically adjusted to improve the performance of the blockchain. The experimental results show that the crowdsourcing system with DSSBD has better performance in terms of throughput, latency, balancing, cross-shard transaction proportion, and node reconfiguration proportion, while ensuring security.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Gabriel F. C. de Queiroz, Jose F. de Rezende, Valmir C. Barbosa
Summary: Multi-access Edge Computing (MEC) is a technology that enables faster task processing at the network edge by deploying servers closer to end users. This paper proposes the FlexDO algorithm to solve the DAG application partitioning and offloading problem, and compares it with other solutions to demonstrate its superior performance in various test scenarios.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shahid Latif, Wadii Boulila, Anis Koubaa, Zhuo Zou, Jawad Ahmad
Summary: In the field of Industrial Internet of Things (IIoT), networks are increasingly vulnerable to cyberattacks. This research introduces an optimized Intrusion Detection System based on Deep Transfer Learning (DTL) for heterogeneous IIoT networks, combining Convolutional Neural Networks (CNNs), Genetic Algorithms (GA), and ensemble techniques. Through rigorous evaluation, the framework achieves exceptional performance and accurate detection of various cyberattacks.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Rongji Liao, Yuan Zhang, Jinyao Yan, Yang Cai, Narisu Tao
Summary: This paper proposes a joint control approach called STOP to guarantee user-perceived deadline using curriculum-guided deep reinforcement learning. Experimental results show that the STOP scheme achieves a significantly higher average arrival ratio in NS-3.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Miguel Rodriguez-Perez, Sergio Herreria-Alonso, J. Carlos Lopez-Ardao, Raul F. Rodriguez-Rubio
Summary: This paper presents an implementation of an active queue management (AQM) algorithm for the Named-Data Networking (NDN) architecture and its application in congestion control protocols. By utilizing the congestion mark field in NDN packets, information about each transmission queue is encoded to achieve a scalable AQM solution.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Angel Canete, Mercedes Amor, Lidia Fuentes
Summary: This paper proposes an energy-aware placement of service function chains of Virtual Network Functions (VNFs) and a resource-allocation solution for heterogeneous edge infrastructures. The solution has been integrated with an open source management and orchestration project and has been successfully applied to augmented reality services, achieving significant reduction in power consumption and ensuring quality of service compliance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Sachin Kadam, Kaustubh S. Bhargao, Gaurav S. Kasbekar
Summary: This paper discusses the problem of estimating the node cardinality of each node type in a heterogeneous wireless network. Two schemes, HSRC-M1 and HSRC-M2, are proposed to rapidly estimate the number of nodes of each type. The accuracy and efficiency of these schemes are proven through mathematical analysis and simulation experiments.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Jean Nestor M. Dahj, Kingsley A. Ogudo, Leandro Boonzaaier
Summary: The launch of commercial 5G networks has opened up opportunities for heavy data users and highspeed applications, but traditional monitoring and evaluation techniques have limitations in the 5G networks. This paper presents a cost-effective hybrid analytical approach for detecting and evaluating user experience in real-time 5G networks, using statistical methods to calculate the user quality index.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Ali Nauman, Haya Mesfer Alshahrani, Nadhem Nemri, Kamal M. Othman, Nojood O. Aljehane, Mashael Maashi, Ashit Kumar Dutta, Mohammed Assiri, Wali Ullah Khan
Summary: The integration of terrestrial and satellite wireless communication networks offers a practical solution to enhance network coverage, connectivity, and cost-effectiveness. This study introduces a resource allocation framework that leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to improve energy efficiency. Through the use of a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG), the proposed approach optimizes user association, cache design, and transmission power control, resulting in enhanced energy efficiency and reduced time delays compared to existing methods.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Wu Chen, Jiayi Zhu, Jiajia Liu, Hongzhi Guo
Summary: With advancements in technology, large-scale drone swarms will be widely used in commercial and military fields. Current application methods are mainly divided into autonomous methods and controlled methods. This paper proposes a new framework for global coordination through local interaction.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Peiying Zhang, Zhihu Luo, Neeraj Kumar, Mohsen Guizani, Hongxia Zhang, Jian Wang
Summary: With the development of Industry 5.0, the demand for network access devices is increasing, especially in areas such as financial transactions, drone control, and telemedicine where low latency is crucial. However, traditional network architectures limit the construction of low-latency networks due to the tight coupling of control and data forwarding functions. To overcome this problem, researchers propose a constraint escalation virtual network embedding algorithm assisted by Graph Convolutional Networks (GCN), which automatically extracts network features and accelerates the learning process to improve network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Review
Computer Science, Hardware & Architecture
P. Anitha, H. S. Vimala, J. Shreyas
Summary: Congestion control is crucial for maintaining network stability, reliability, and performance in IoT. It ensures that critical applications can operate seamlessly and that IoT devices can communicate efficiently without overwhelming the network. Congestion control algorithms ensure that the network operates within its capacity, preventing network overload and maintaining network performance.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Shunmugapriya Ramanathan, Abhishek Bhattacharyya, Koteswararao Kondepu, Andrea Fumagalli
Summary: This article presents an experiment that achieves live migration of a containerized 5G Central Unit module using modified open-source migration software. By comparing different migration techniques, it is found that the hybrid migration technique can reduce end-user service recovery time by 36% compared to the traditional cold migration technique.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Fatma Foad Ashrif, Elankovan A. Sundararajan, Rami Ahmad, Mohammad Kamrul Hasan, Elaheh Yadegaridehkordi
Summary: This article introduces the development and current status of authentication protocols in 6LoWPAN, and proposes an innovative perspective to fill the research gap. The article comprehensively surveys and evaluates AKA protocols, analyzing their suitability in wireless sensor networks and the Internet of Things, and proposes future research directions and issues.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)
Article
Computer Science, Hardware & Architecture
Pranjal Kumar Nandi, Md. Rejaul Islam Reaj, Sujan Sarker, Md. Abdur Razzaque, Md. Mamun-or-Rashid, Palash Roy
Summary: This paper proposes a task offloading policy for IoT devices to a mobile edge computing system, aiming to balance device utility and execution cost. A meta heuristic approach is developed to solve the offloading problem, and the results show its potential in terms of task execution latency, energy consumption, utility per unit cost, and task drop rate.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2024)