Article
Chemistry, Analytical
Jinho Park, Kwangsue Chung
Summary: An edge collaboration scheme based on resource prediction is proposed to improve QoE by estimating computing resource usage, probabilistically collaborating with other edge servers, and achieving high success rate and low completion time.
Article
Computer Science, Information Systems
Guang Peng, Huaming Wu, Han Wu, Katinka Wolter
Summary: This article proposes three constrained multiobjective evolutionary algorithms (CMOEAs) for solving IoT-enabled computation offloading problems in collaborative edge and cloud computing networks. These algorithms consider time and energy consumption, and aim to improve efficiency and optimization through a combination of search algorithms and constraint handling mechanisms.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Review
Computer Science, Information Systems
Mohammed Laroui, Boubakr Nour, Hassine Moungla, Moussa A. Cherif, Hossam Afifi, Mohsen Guizani
Summary: The Internet of Things (IoT) enables communication between devices and digital assets over a network without human intervention. Traditional cloud computing is not efficient in analyzing large amounts of data quickly, prompting the proposal of edge computing to decentralize data processing to solve this issue. Edge computing supports IoT applications requiring quick response times, leading to improved energy consumption and resource utilization.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Habiba Mohamed, Eyhab Al-Masri, Olivera Kotevska, Alireza Souri
Summary: This paper proposes OpERA, a multi-layered edge-based resource allocation optimization framework that supports heterogeneous edge devices. It optimizes resource allocation by capturing offloadable task requirements, reducing costs and energy consumption, and increasing the likelihood of successful task offloading.
Article
Computer Science, Information Systems
Yulei Wu
Summary: The Internet of Things is widely utilized in various critical sectors, requiring efficient data processing. AI-powered cloud-edge orchestration provides crucial computing support for IoT applications.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Multidisciplinary Sciences
Tonghe Wang, Songpu Ai, Junwei Cao, Yuming Zhao
Summary: The architecture of cloud-edge collaboration can improve the efficiency of IoT systems. In practice, the motivation for participants to take over computational tasks from others is often lacking. To mitigate this issue, this paper designs a distributed strategy for the trading of computational resources.
Article
Computer Science, Information Systems
Miaojiang Chen, Tian Wang, Shaobo Zhang, Anfeng Liu
Summary: This paper proposes a learning-based mobile fog scheme with deep deterministic policy gradient algorithm to improve the fog resource provisioning performance of mobile devices. The scheme models offloading computing as Markov Decision Processes, realizing offloading among different network states without knowing the transition probabilities, and uses the DDPG algorithm to address the state spaces explosion issue and learn an optimal offloading policy on distributed mobile fog computing. Simulation results show significant improvement in performance compared to traditional methods.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Mohammad Aazam, Sherali Zeadally, Eduardo Feo Flushing
Summary: Advancements in networking and mobile technologies have enabled the development of intelligent services, however, tasks like machine learning on edge devices may lead to higher energy consumption.
Article
Computer Science, Artificial Intelligence
Marek Pawlicki, Aleksandra Pawlicka, Rafal Kozik, Michal Choras
Summary: Cloud computing, edge computing, and Internet-of-Things have significantly impacted people's lives, but their security should not be taken for granted. These paradigms are constantly under attack, and the potential breaches can have severe consequences. This systematic review aims to analyze the overlap of attacks in cloud, edge, and IoT and provide solutions and countermeasures to enhance their security. It fills the gap by constructing a concise threat catalogue and offering a more universal approach to ensure the safety of the entire ecosystem.
Article
Computer Science, Information Systems
Xiangyi Chen, Yuanguo Bi, Guangjie Han, Dongyu Zhang, Minghan Liu, Han Shi, Hai Zhao, Fengyun Li
Summary: This article proposes a distributed computation offloading scheme to provide computational support to large-scale IoT nodes and optimize the energy efficiency of multiple UAVs. It utilizes a real-time intelligent positioning algorithm to obtain precise location information of IoT nodes, and a distributed computation offloading and path planning algorithm to reduce the energy consumption of UAVs. A closed-form theoretical analysis model is developed to demonstrate performance guarantee related to energy efficiency.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Xiaojian Zhu, MengChu Zhou
Summary: Mobile-edge computing reduces workload and network delay by deploying computational resources near devices, focusing on user experience and cost reduction for service providers. Research on joint cloudlet deployment and task offloading aims to minimize energy consumption, task response delay, and deployed cloudlets, using a modified optimization algorithm to find tradeoff solutions. The algorithm's superiority is confirmed through extensive simulations.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Xiaoheng Deng, Xinjun Pei, Shengwei Tian, Lan Zhang
Summary: The advent of 5G has brought new opportunities for Industrial Internet of Things (IoT) to leapfrog beyond current capabilities. However, the growing IoT has also attracted adversaries who develop new malware attacks on IoT applications. Deep-learning-based methods are expected to combat these sophisticated malwares, but they are not feasible for battery-powered end devices like Android smartphones. Edge computing enables near-real-time analysis of IoT data by shifting computation-intensive tasks to nearby edge servers. However, coordinating the task offloading among multiple users is challenging due to varying channel conditions and latency requirements. To address these challenges, we propose a hierarchical security framework for IoT malware detection that leverages the computation capacity and proximity benefits of edge computing. We also provide a delay-aware computational offloading strategy and construct a coordinated representation learning model, called Two-Stream Attention-Caps, to capture evolving malware attack patterns. Experimental results demonstrate superior detection performance compared to state-of-the-art systems on four benchmark datasets.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Hyeonseok Seo, Hyeontaek Oh, Jun Kyun Choi, Sangdon Park
Summary: With the development of IoT, there is an increased demand for delay-sensitive applications, leading to the emergence of mobile-edge computing (MEC) as a promising technology. This article proposes a differential pricing scheme to reflect the user's usage of server computational resources and suggests optimal offloading and pricing strategies. Numerical results demonstrate the effectiveness of the proposed scheme in improving the efficiency of edge server's computational resources.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Dan Wang, Yalu Bai, Gang Huang, Bin Song, F. Richard Yu
Summary: In this paper, we propose a cache-aided MEC (CA-MEC) offloading framework for joint optimization of communication, computing, and caching resources in the MEC-enabled IoT. We formulate the problem as a multiagent decision problem and apply the deep graph convolution reinforcement learning method to learn optimal strategies cooperatively. Simulations demonstrate that our method is highly effective for computation offloading and resource allocation, achieving superior results in a large-scale network.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Software Engineering
Jiashu Wu, Hao Dai, Yang Wang, Shigen Shen, Chengzhong Xu
Summary: This article proposes a profit and cost-oriented optimization model for edge-cloud computation offloading, taking into account task heterogeneity, load balancing, and profit from computation tasks. An improved Moth-flame optimizer, PECCO-MFI, is introduced to address the complexity and non-differentiability of the optimization objective, and is integrated into the edge-cloud environment. Comprehensive experiments demonstrate the superior performance of the proposed method in optimizing the task offloading model under the edge-cloud environment.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Chemistry, Analytical
Aikaterini I. Griva, Achilles D. Boursianis, Shaohua Wan, Panagiotis Sarigiannidis, Konstantinos E. Psannis, George Karagiannidis, Sotirios K. Goudos
Summary: The implementation of smart networks has been greatly advanced by the development of IoT, with LoRa being a prominent technology due to its long-distance transmission capabilities with low power consumption. This study simulated various environments to assess network performance based on different factors and parameters. Path loss model, deployment area size, transmission power, spreading factor, number of nodes and gateways, and antenna gain significantly affect the energy consumption and data extraction rate of LoRa networks. The research performed simulations using the FLoRa framework in OMNeT++, investigating rural and urban environments, as well as a parking area model. The results emphasize the importance of optimizing key parameters for the deployment of smart networks.
Article
Computer Science, Interdisciplinary Applications
George Amponis, Thomas Lagkas, Konstantinos Tsiknas, Panagiotis Radoglou-Grammatikis, Panagiotis Sarigiannidis
Summary: The Transmission Control Protocol (TCP) is a widely used reliable, connection-oriented, congestion control mechanism in both wired and wireless networks. However, the standard TCP congestion control mechanism performs poorly in high-mobility wireless networking scenarios. To address this issue, this paper compares various TCP variants and introduces a new variant called Swarm HTCP (S-HTCP), specifically designed for Flying Ad hoc Networks (FANETs) consisting of Unmanned Aerial Vehicles (UAVs). The simulation evaluation shows that S-HTCP outperforms other variants in high-mobility network conditions.
SIMULATION MODELLING PRACTICE AND THEORY
(2023)
Article
Computer Science, Information Systems
M. Rezwanul Mahmood, Mohammad Abdul Matin, Panagiotis Sarigiannidis, Sotirios K. K. Goudos, George K. K. Karagiannidis
Summary: This paper investigates the application of residual compensation-based ELM (RC-ELM) in designing a receiver for MIMO-NOMA aided IoT systems. By analyzing the BER and EVM performances, the appropriate number of compensation layers for training error minimization is determined. The results show improved BER and EVM performances with the aid of RC-ELM compared to other receivers.
Review
Engineering, Multidisciplinary
Maria Papatsimouli, Panos Sarigiannidis, George F. Fragulis
Summary: Real-time sign language translation systems play a crucial role in facilitating communication for the deaf and hard-of-hearing. Despite the availability of assistive technologies, there is a significant communication gap between sign language users and non-users. Our research aims to analyze recent advancements in real-time sign language translation, particularly in its integration with IoT technology. We conducted a comprehensive analysis of literature and technical reports, providing insights into the current state of the art in this field and discussing the potential for improving communication and inclusivity through the fusion of sign language translation and IoT technology.
Article
Computer Science, Information Systems
Yunxiao Zhang, Pasquale Malacaria, George Loukas, Emmanouil Panaousis
Summary: This work presents a decision support framework called CROSS that provides advice for selecting optimal cyber security controls in smart homes. It considers both traditional cyber attacks and adversarial machine learning attacks and aims to protect both smart home users and service providers.
COMPUTERS & SECURITY
(2023)
Article
Engineering, Electrical & Electronic
Sotirios P. Sotiroudis, Georgia Athanasiadou, George Tsoulos, Panagiotis Sarigiannidis, Christos G. Christodoulou, Sotirios K. Goudos
Summary: The usage of UAVs as FBSs for expanding coverage and assisting cellular networks in 5G and beyond is a promising technology. Path loss prediction is a crucial parameter in cellular network design, and ML-based predictions using ensemble learning techniques offer a more efficient alternative to deterministic ray-tracing models. Our proposed evolutionary tuned stacked ensemble method optimizes the ensemble as a whole, achieving better performance in path loss modeling in electromagnetics.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2023)
Article
Biochemical Research Methods
Ilias Siniosoglou, Vasileios Argyriou, Panagiotis Sarigiannidis, Thomas Lagkas, Antonios Sarigiannidis, Sotirios K. K. Goudos, Shaohua Wan
Summary: Modern healthcare cyberphysical systems rely on distributed AI and Federated Learning to train ML and DL models for various medical fields while protecting sensitive information. However, the local training of federated models sometimes falls short, affecting their optimization and subsequent performance. This work proposes a post-processing pipeline to improve model fairness and accuracy in the FL environment.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Computer Science, Information Systems
Aristeidis Farao, Georgios Paparis, Sakshyam Panda, Emmanouil Panaousis, Apostolis Zarras, Christos Xenakis
Summary: Despite challenges such as lack of data, shortage of automated tasks, fraudulent claims, masquerading attackers, and cyber-security attacks on insurance companies, the article presents INCHAIN, an innovative architecture utilizing Blockchain technology to provide data transparency and traceability. The architecture includes Smart Contracts and Self-Sovereign Identity for automation and robust identification. The research demonstrates a novel and efficient solution to managing cyber insurance, successfully combating fraudulent claims and ensuring proper customer identification and authentication.
INTERNATIONAL JOURNAL OF INFORMATION SECURITY
(2023)
Article
Health Care Sciences & Services
Elina Argyridou, Sokratis Nifakos, Christos Laoudias, Sakshyam Panda, Emmanouil Panaousis, Krishna Chandramouli, Diana Navarro-Llobet, Juan Mora Zamorano, Panagiotis Papachristou, Stefano Bonacina
Summary: Cyber threats are increasing in the health care sector, and health care organizations (HOs) are implementing cybersecurity controls to protect against these threats. However, humans are often the weakest link in cybersecurity, making it important to address the human aspects of cybersecurity. This study introduces a cyber hygiene methodology that uses a survey-based risk assessment approach to raise awareness and recommend human-centric controls tailored to each organization's needs.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Emily Kate Parsons, Emmanouil Panaousis, George Loukas, Georgia Sakellari
Summary: In this paper, a comprehensive survey of cyber risk management processes in the context of IoT is presented, and recommendations for future work are provided. Through the analysis of 39 collected papers, IoT cyber risk management frameworks are studied against four research questions that focus on cyber risk management concepts and human-orientated vulnerabilities. The importance of this work lies in understanding how individuals can impact risk and how humans can be affected by attacks in different IoT domains.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Nikos A. A. Mitsiou, Sotiris A. A. Tegos, Panagiotis D. D. Diamantoulakis, Panagiotis G. G. Sarigiannidis, George K. K. Karagiannidis
Summary: To address the inefficiency in terms of resource utilization of grant-free (GF) protocols, the fast uplink (FU) grant medium-access protocol has been proposed. In this letter, we design a proactive wireless power transfer (WPT) framework for FU grant zero-energy massive machine-type communication. Specifically, zero-energy devices (ZEDs) first harvest energy during the WPT phase and then transmit data based on the FU grant protocol. Moreover, a multi-arm bandit traffic prediction scheme is adopted. Simulation results show that the proposed scheme outperforms GF access.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Computer Science, Information Systems
Maria Tsiodra, Sakshyam Panda, Michail Chronopoulos, Emmanouil Panaousis
Summary: This paper proposes a cybersecurity decision-support framework called CENSOR for optimal cyber security investment. CENSOR takes into account the continuous nature of cyber attacks, uncertainty in vulnerability exploitation time, and optimization of mitigation measures under a limited budget. It evaluates the cost incurred by an organization due to a cyber security breach and derives an analytical expression for the distribution of present value of the cost. It also compares optimal strategies for investment using Set Covering and Knapsack formulations, validating the effectiveness of CENSOR through a case study.
Article
Computer Science, Information Systems
Sotirios K. Goudos, Panagiotis D. Diamantoulakis, Achilles D. Boursianis, Panagiotis Sarigiannidis, Konstantinos E. Psannis, Mohammad Abdul Matin, Shaohua Wan, George K. Karagiannidis
Summary: In this work, we address the problem of joint power allocation and user association for non-orthogonal multiple access (NOMA) in downlink networks based on quality-of-service. Due to its non-convex form and the large number of optimization variables, the problem is challenging and we propose two nature-inspired algorithms with low complexity for solving it. We investigate the impact of different network parameters on increasing users and show that evolutionary algorithms are effective in solving this problem, outperforming randomly generated solutions. Furthermore, the advantages of NOMA over OMA become more evident as the number of users increases.
Article
Engineering, Electrical & Electronic
Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Dimitrios Pliatsios, Jorge Querol, Konstantinos Ntontin, Panagiotis Sarigiannidis, Symeon Chatzinotas, Marco Di Renzo
Summary: This survey investigates the envisioned applications and use cases of localization in future 6G wireless systems and analyzes the impact of major technology enablers. System models for millimeter wave, terahertz, and visible light positioning are presented, along with a review of conventional and learning-based localization techniques. The localization problem is formulated, wireless system design is considered, and optimization is investigated. Insights from the analysis highlight important future directions for localization in 6G wireless systems.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2023)
Review
Engineering, Electrical & Electronic
Vasileios P. Rekkas, Lazaros Alexios Iliadis, Sotirios P. Sotiroudis, Achilles D. Boursianis, Panagiotis Sarigiannidis, David Plets, Wout Joseph, Shaohua Wan, Christos G. Christodoulou, George K. Karagiannidis, Sotirios K. Goudos
Summary: Indoor communication and positioning are important applications in the field of indoor Internet of Things. Visible light positioning (VLP) and artificial intelligence (AI) have great potential in indoor location-aware IoT services. This paper reviews the research efforts on the use of AI in VLP, summarizes the current progress, identifies open issues, and proposes future research directions.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2023)
Article
Computer Science, Interdisciplinary Applications
Shivani Sharma, Sateesh Kumar Awasthi
Summary: Vehicular Ad-hoc Network (VANET) is crucial in Intelligent Transportation Systems, and this study proposes a hybrid system utilizing V2V and V2I communications for secure data dissemination in urban scenarios.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Computer Science, Interdisciplinary Applications
Hind Mikram, Said El Kafhali, Youssef Saadi
Summary: Efficient task scheduling in cloud data centers is crucial for optimizing resource utilization and load balance. This paper introduces a hybrid algorithm, HEPGA, that combines particle swarm optimization (PSO) and genetic algorithm (GA) to allocate tasks efficiently and minimize makespan in cloud computing environments. By integrating PSO, GA, and HEFT-based initialization, the algorithm capitalizes on parallel processing capabilities and adapts to varying priorities to enhance resource utilization. Meticulous analysis of the algorithm's performance, considering both makespan and resource utilization, demonstrates its ability to consistently allocate resources and adapt to different optimization goals.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Computer Science, Interdisciplinary Applications
Ping-Chen Chang, Cheng-Fu Huang, Ding-Hsiang Huang
Summary: This paper introduces a novel simulation approach based on minimal cuts to estimate the system reliability of a multistate flow network (MSFN). The approach improves computational efficiency by reducing the number of minimal cuts and preserving saturated minimal cuts. It effectively deals with non-integer demands and demonstrates effectiveness and efficiency in illustrative examples.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Computer Science, Interdisciplinary Applications
Jang Won Bae, Chun-Hee Lee, Jeong-Woo Lee, Seon Han Choi
Summary: In this study, a data-driven agent-based model is proposed for simulating the public bicycle-sharing systems (PBSSs) in Sejong City, South Korea. The model captures users' behavioral characteristics and analyzes their convenience through a bottom-up approach. By extracting parameters from actual operational data and demographic information, the model's accuracy is improved. Model simulations evaluate the utilization and user convenience of Eoulling, providing a viable solution for addressing multiple concerns.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Computer Science, Interdisciplinary Applications
Chong Shi, Junbao Pian, Cong Zhang, Xiao Chen, Yonggang Zhang
Summary: This study presents a novel numerical simulation method for analyzing the mechanisms of pulsed pressure-induced rock fractures. The results show that rock fracturing under impulsive loading is a combined effect of stress waves and high-pressure fluids, with the fluid penetration and splitting action playing important roles in the process.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Computer Science, Interdisciplinary Applications
Junwei Zhang, Zhongwei Chen, Kang Shao
Summary: This study investigated the performance of three constitutive models for rock material in simulation of blast-induced rock cracks, and proposed an optimal blasting parameters design.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Computer Science, Interdisciplinary Applications
Joshua Shakya, Chaima Ghribi, Leila Merghem-Boulahia
Summary: Modeling and simulation of telecommunication networks, especially 5G+ networks, have become increasingly important and challenging. Traditional simulation techniques may not be sufficient to capture the dynamic changes in 5G+ networks, leading researchers to adopt an Agent-based modeling and simulation approach from the perspective of Complex System Science. This study provides insights into the advantages, potential, and challenges of Agent-based simulation in the context of 5G+ networks, and proposes a prospective architecture for a simulator and its evolution into a Digital Twin.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
Article
Computer Science, Interdisciplinary Applications
Sensen Xing, Cheng Wang, Wei Wang, Rui Feng Cao, Anthony Chun Yin Yuen, Eric Wai Ming Lee, Guan Heng Yeoh, Qing Nian Chan
Summary: This paper proposes an extended FFCA model that integrates the natural step length into pedestrian movement, allowing pedestrians to occupy multiple grids and expanding the interaction area. Through simulation of evacuation scenarios, the model accurately reproduces density-velocity relations and matches experimental results. Compared to traditional models, this model generates more reasonable velocity variations and evacuation paths.
SIMULATION MODELLING PRACTICE AND THEORY
(2024)
