Article
Computer Science, Information Systems
Rojalina Priyadarshini, Rabindra Kumar Barik
Summary: Fog computing provides additional support to the cloud environment, but enterprises are uncertain about using it due to security and privacy concerns. This paper proposes a source-based DDoS defense mechanism that uses Software Defined Networking to detect and mitigate DDoS attacks.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Review
Computer Science, Hardware & Architecture
Abhishek Narwaria, Arka Prokash Mazumdar
Summary: Software-Defined Wireless Sensor Networks (SDWSN) is a promising technology that addresses the challenges of wireless networks, particularly Wireless Sensor Networks (WSN). SDWSN enables WSN to be programmable, configurable, multi-functional, and flexible at run-time. However, it faces challenges such as network management, energy efficiency, controller implementation, placement, and security.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Green & Sustainable Science & Technology
Zhenqiang Feng
Summary: This paper introduces the advantages of combining fog computing with cloud computing, and proposes an optimized cache algorithm and a wireless sensor network based on Lo Ra WAN. The innovative algorithm and data collection method in the article can effectively improve cache space utilization, extend the survival time of sensor networks, and ensure data accuracy.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Computer Science, Information Systems
Chandana Roy, Ruelia Saha, Sudip Misra, Dusit Niyato
Summary: This article proposes a software-defined fog architecture, Soft-Health, for IoT-based healthcare applications. By using a wireless body area network for continuous patient monitoring and allocating information to appropriate fog/cloud based on criticality index, the risk of deterioration in patient health can be reduced.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Ernando Batista, Gustavo Figueiredo, Cassio Prazeres
Summary: The Internet of Things enables the coordination and orchestration of numerous physical and virtual objects connected to the Internet. This paper proposes a solution for load balancing in IoT applications using Software-Defined Networks. It addresses the challenges posed by unstable network infrastructure and processing overload on IoT devices.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Rabie A. Ramadan, Md. Haidar Sharif, Eissa Jaber Alreshidi, Md. Haris Uddin Sharif, Ibrahim Furkan Ince, Hiqmet Kamberaj, Ahmed Y. Khedr
Summary: This paper discusses the importance of fog computing in IoT applications and explores ways to optimize the placement of multi-sink nodes in fog networks to improve efficiency and energy savings. Novel solutions like the Window Nondominant Set, Evaluation Based Approach, Harris Hawks Optimizer, and Modified HHO are proposed to address challenges in fog networks. Experimental results are used to evaluate the performance of these algorithms in terms of power consumption, runtime, packet loss, and localization error.
Article
Computer Science, Artificial Intelligence
Gauri Kalnoor, S. Gowrishankar
Summary: The proposed work aims to design an intelligent intrusion detection system using machine learning models to identify and protect IoT networks from attacks. Experimental results show that the Markov model performs well in the I-IDS IoT network, achieving a 100% detection rate and low false alarm rate.
Article
Computer Science, Hardware & Architecture
S. Suja Golden Shiny, S. Sathya Priya, K. Murugan
Summary: This paper proposes a solution for prolonging the lifetime of sensor networks by processing data within the network and selecting appropriate nodes to execute reducer functions, reducing communication costs significantly.
Article
Engineering, Electrical & Electronic
Jagdeep Singh, Parminder Singh, Mustapha Hedabou, Neeraj Kumar
Summary: Fog computing is a new technology that provides accessibility of computing resources close to end-users, addressing the limitations of network bandwidth and delay in cloud computing. Resource allocation is crucial for managing resources in a fog computing environment. However, traditional techniques do not meet the low latency requirements of modern fog computing applications. This article proposes a resource allocation technique for SDN-enabled fog computing with Collaborative Machine Learning (CML), which reduces execution time, energy consumption, and latency.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Kai Liu, Ke Xiao, Penglin Dai, Victor C. S. Lee, Songtao Guo, Jiannong Cao
Summary: This paper introduces a fog computing empowered architecture and scheduling algorithm for data dissemination in vehicular ad-hoc networks, aiming to minimize service delay through cooperative service and improve data transmission efficiency.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
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.
Article
Computer Science, Information Systems
Xiangdong Jia, Shengnan Cao, Mangang Xie
Summary: This study proposes a novel status update information system with two sensors and one destination, taking into account wireless energy harvesting diversity, status update transmission diversity, and HARQ-CC diversity. By developing a sensor energy harvesting model and deriving the average age of information for the dual-sensor system, it is shown that the proposed system outperforms traditional single-sensor systems in terms of energy harvesting efficiency and average age of information.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Noureddine Moussa, Sondes Khemiri-Kallel, Abdelbaki El Belrhiti El Alaoui
Summary: This paper proposes a Hierarchical Data Routing Strategy (HDRS) for fog-enabled WSNs, which achieves high energy-efficiency, reliability, and response time, and is adaptable to the addition and removal of faulty nodes. The evaluation using the forest fire detection application demonstrates that HDRS outperforms quality of service-based routing protocol in terms of network lifetime and response time.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2022)
Article
Chemistry, Analytical
Antonio Marcos Almeida Ferreira, Leonildo Jose de Melo de Azevedo, Julio Cezar Estrella, Alexandre Claudio Botazzo Delbem
Summary: With the development of mobile communications and the IoT, reducing latency in IoT networks has become crucial. This research aims to simulate a hybrid network of sensors related to public transport in Sao Carlos - SP using Contiki-NG and select the most suitable place to deploy an IoT sensor network. Performance tests were conducted on five scenarios, and MADM algorithms were applied to generate a multicriteria decision ranking. The results show that scenario four is the most viable option based on the TOPSIS and VIKOR decision-making algorithms.
Article
Computer Science, Theory & Methods
Noureddine Moussa, Edmond Nurellari, Kebira Azbeg, Abdellah Boulouz, Karim Afdel, Lahcen Koutti, Mohamed Ben Salah, Abdelbaki El Belrhiti El Alaoui
Summary: This paper proposes an application-specific Routing Protocol based on Reinforcement Learning (RL) for Software Defined Network (SDN)-enabled WSN forest fire detection (RPLS). The protocol optimizes energy consumption and ensures real time responsiveness by using a clustering algorithm and RL-based reward function. Simulation results show significant improvements in network operational lifetime and response time.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Nadia Mumtaz, Naveed Ejaz, Shabana Habib, Syed Muhammad Mohsin, Prayag Tiwari, Shahab S. Band, Neeraj Kumar
Summary: This paper discusses the generation of big video data in smart cities and focuses on violence detection using deep learning approaches. The paper provides an overview of deep sequence learning methods and localization strategies for violence detection. It also explores the initial image processing and machine learning-based violence detection literature and their advantages and disadvantages. Additionally, the paper discusses datasets and proposes future directions in the violence detection domain based on in-depth analysis of previous methods.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Review
Computer Science, Information Systems
Deepanshi, Ishan Budhiraja, Deepak Garg, Neeraj Kumar, Rohit Sharma
Summary: SARS-CoV-2 is an infected disease caused by one of the variants of Coronavirus which emerged in December 2019. It is declared a pandemic by WHO in March 2020. COVID-19 outbreak has put the world on a halt and is a major threat to the public health system. Despite of numerous efforts, precautions and vaccination the infection has grown rapidly in the world.
COMPUTER COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Ashwin Verma, Pronaya Bhattacharya, Deepti Saraswat, Sudeep Tanwar, Neeraj Kumar, Ravi Sharma
Summary: Recently, UAVs have been used for COVID-19 vaccine distribution to address fake vaccine issues. The authors propose a blockchain-assisted UAV vaccine distribution scheme based on sixth-generation enhanced ultra-reliable low latency communication (6G-eRLLC). The scheme utilizes a public Solana blockchain setup for user registration, vaccine request, and distribution, ensuring scalable transactions. With an intelligent edge offloading scheme, UAV swarms are deployed to deliver vaccines to nodal centers, showing significant improvements in service latency, energy reduction, UAV coverage, and storage cost compared to 5G uRLLC communication and Ethereum network.
IEEE SENSORS JOURNAL
(2023)
Article
Computer Science, Hardware & Architecture
Dan Tang, Xiyin Wang, Xiong Li, Pandi Vijayakumar, Neeraj Kumar
Summary: Low-rate denial of service (LDoS) attacks exploit network protocol vulnerabilities to launch periodic bursts, severely impacting TCP application quality of service. Current coarse-scale detection methods are ineffective. To accurately detect LDoS attacks, an adaptive Kohonen Network based fine-grained detection (AKN-FGD) model is proposed. The AKN-FGD scheme achieves accurate detection with high detection performance and adaptability, outperforming other methods.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2023)
Article
Construction & Building Technology
Bin Yang, Yihang Liu, Pengju Liu, Faming Wang, Xiaogang Cheng, Zhihan Lv
Summary: This study used a deep learning-based computer vision method for indoor occupancy detection and proposed an occupant-centric control strategy based on the monitored occupant number to regulate supply air parameters and outdoor air volume for energy saving purposes. The results showed that compared to the traditional control strategy, the proposed strategy improved comfort by 43%-73%, maintained acceptable air quality, kept CO2 concentration below 700 ppm, and saved energy by 2.3%-8.1%. It was also found that the lower the occupancy, the greater the improvement in comfort and energy savings.
BUILDING AND ENVIRONMENT
(2023)
Article
Automation & Control Systems
Yajie Wang, Yu-an Tan, Thar Baker, Neeraj Kumar, Quanxin Zhang
Summary: Industry 5.0 aims to merge the cognitive computing capabilities of DNNs with human resourcefulness in collaborative operations. However, DNNs are vulnerable to adversarial attacks, bringing risks to Industrial AIoT systems. To solve these problems, we propose two novel deep fusion methods.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Rajat Chaudhary, Neeraj Kumar
Summary: Software-Defined Internet of Vehicles (SD-IoV) is an emerging technology used in modern intelligent transportation systems. The goal of SD-IoV is to provide seamless connectivity with low latency and high-speed data transfer. However, the challenges of high power consumption and secure data transfer arise due to the increased density of connected vehicles using the Internet. In this paper, a joint power optimization and secrecy ensured scheme known as SecGreen is proposed to address these issues.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Information Systems
Bo Fang, Junxin Chen, Yu Liu, Wei Wang, Ke Wang, Amit Kumar Singh, Zhihan Lv
Summary: With the advancement of wearable devices, collecting single lead ECG waves continuously has become more comfortable. This paper proposes a dual-channel neural network for atrial fibrillation (AF) detection from a single lead ECG wave. The method includes data preprocessing and a dual-channel neural network. A two-stage denoising procedure is utilized to handle the high noise and disturbance commonly present in ECG wave data collected by wearables. The results on the 2017 PhysioNet/CinC Challenge database confirm the effectiveness of the proposed method for AF detection, with F1 values of 0.83, 0.90, and 0.75 for AF rhythm, normal rhythm, and other rhythms, respectively. The method also outperforms some state-of-the-art counterparts.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Computer Science, Information Systems
Nan Bao, Jiajun Du, Chengyang Wu, Duo Hong, Junxin Chen, Robert Nowak, Zhihan Lv
Summary: This paper presents a contactless and real-time respiration monitoring system, called Wi-Breath, based on off-the-shelf WiFi devices. The system monitors respiration using both the amplitude and phase difference of WiFi channel state information (CSI). A signal selection method based on a support vector machine (SVM) algorithm is proposed to improve the accuracy of respiration detection. Experimental results show that Wi-Breath achieves an accuracy of 91.2% and reduces the average error by 17.0% compared to state-of-the-art counterparts.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Computer Science, Information Systems
Ashish Singh, Kakali Chatterjee, Anish Kumar Singh, Neeraj Kumar
Summary: Mobile-edge computing (MEC) is a new architecture providing services at the network edge, with potential applications in healthcare for remote patient monitoring, diagnosis, and treatment. However, there are security and privacy concerns related to remote data access, including unauthorized access and data leakage, which can make the system inconvenient, untrusted, less suitable, and vulnerable.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Peiying Zhang, Yi Zhang, Neeraj Kumar, Ching-Hsien Hsu
Summary: Due to geographical factors and resource constraints, the traditional Internet architecture cannot meet the needs of the space-air-ground-integrated network (SAGIN) resource layout in the Industrial Internet of Things (IIoT) service. This article proposes a latency-sensitive VNE algorithm based on deep reinforcement learning (DDRL-VNE) in the SAGIN environment to efficiently arrange network resources and meet the quality of service requirements of users. Experimental results effectively illustrate the effectiveness of the algorithm in the SAGIN resource allocation problem.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Civil
Ilgin Gokasar, Alperen Timurogullari, Sarp Semih Ozkan, Muhammet Deveci, Zhihan Lv
Summary: This paper proposes a modified standard normal deviation (MSND) incident detection algorithm that uses connected autonomous vehicles (CAVs) as data sources and evaluates its efficacy using SUMO Traffic Simulation Software. The results show that the proposed method outperforms other incident detection algorithms in terms of detection rate and integrates well with the Variable Speed Limits (VSL) traffic management method to reduce average density in critical regions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Cybernetics
Hao Zhang, Zonglin Li, Sanya Liu, Tao Huang, Zhouwei Ni, Jian Zhang, Zhihan Lv
Summary: With the proliferation of fake news, detecting and classifying them accurately is crucial to prevent social panic and group polarization. This study proposes a graph attention network-based model that incorporates sentiment analysis, external knowledge comparison, and emotion interaction to extract features from long-form news for fake news classification. The model outperforms existing methods and achieves state-of-the-art accuracy on various datasets.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Telecommunications
Jiabao Wen, Jiachen Yang, Tianying Wang, Yang Li, Zhihan Lv
Summary: In order to efficiently complete a complex computation task, it is necessary to decompose the task into subcomputation tasks that run parallel in edge computing. Wireless Sensor Network (WSN) is an example of parallel computation. A task allocation strategy is needed to reduce energy consumption and balance the load of the network, which is crucial for achieving highly reliable parallel computation in WSN.
DIGITAL COMMUNICATIONS AND NETWORKS
(2023)
Article
Computer Science, Artificial Intelligence
Xiaoyang Zheng, Dongqing Jia, Zhihan Lv, Chengyou Luo, Junli Zhao, Zeyu Ye
Summary: Wind energy is an important part of the power system and accurate wind speed forecasting is essential for its stable and safe utilization. This paper proposes a Legendre multiwavelet-based neural network model, which combines the properties of Legendre multi-wavelets and the self-learning capability of neural networks. The model achieves optimal performance and high prediction accuracy, especially in multi-step prediction.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2023)
Review
Computer Science, Information Systems
Euclides Carlos Pinto Neto, Sajjad Dadkhah, Somayeh Sadeghi, Heather Molyneaux, Ali A. Ghorbani
Summary: The Internet of Things (IoT) has the potential to revolutionize medical treatment in healthcare, but it also faces security threats. Advanced analytics can enhance IoT security, but generating realistic datasets is complex. This research conducts a review of Machine Learning (ML) solutions for IoT security in healthcare, focusing on existing datasets, resources, applications, and challenges, to highlight the current landscape and future requirements.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Duncan Deveaux, Takamasa Higuchi, Seyhan Ucar, Jerome Harri, Onur Altintas
Summary: This paper investigates the ability to predict the risk patterns of vehicles in a roundabout and suggests that constraining knowledge transfer to roundabouts with a similar context can significantly improve accuracy.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Lingjun Zhao, Qinglin Yang, Huakun Huang, Longtao Guo, Shan Jiang
Summary: Metaverse seamlessly integrates the real and virtual worlds, and intelligent wireless sensing technology can serve as an intelligent, flexible, non-contact way to access the metaverse and accelerate the establishment of a bridge between the real physical world and the metaverse. However, there are still challenges and open issues in this field.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Jing Xiong, Hong Zhu
Summary: With the rapid growth of data in the era of IoT, the challenge of data privacy protection arises. This article proposes a federated learning approach that uses collaborative training to obtain a global model without direct exposure to local datasets. By utilizing dynamic masking and adaptive differential privacy methods, the approach reduces communication overhead and improves the converge performance of the model.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Carlos Rubio Garcia, Simon Rommel, Sofiane Takarabt, Juan Jose Vegas Olmos, Sylvain Guilley, Philippe Nguyen, Idelfonso Tafur Monroy
Summary: The reliance on asymmetric public key cryptography and symmetric encryption for cyber-security in current telecommunication networks is threatened by quantum computing technology. Quantum Key Distribution and post-quantum cryptography provide resistance to quantum attacks. This paper proposes two novel hybrid solutions integrating QKD and PQC into TLS for quantum-resistant key exchange.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Annisa Sarah, Gianfranco Nencioni
Summary: This article explores the concept of a Slice Broker, an intermediate entity that purchases resources from Infrastructure Providers to offer customized network slices to users. The article proposes a cost-minimization problem and compares it with alternative problems to demonstrate its effectiveness and cost-saving capabilities.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Sumana Maiti, Sudip Misra, Ayan Mondal
Summary: The broadcast proxy re-encryption methods extend traditional proxy re-encryption mechanisms and propose a scheme called MBP for IoT applications. MBP calculates a single re-encryption key for all user groups and uses multi-channel broadcast encryption to reduce security element size. However, it increases computation time for receiver IoT devices. The use of Rubinstein-Stahl bargaining game approach addresses this issue and MBP is secure against selective group chosen-ciphertext attack in the random oracle model.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Pankaj Kumar, Hari Om
Summary: This paper presents NextGenV2V, a protocol for the next-generation vehicular network that achieves authenticated communication between vehicles using symmetric keys and a (2, n)-threshold scheme. The protocol reduces communication overhead and improves authentication delay, ensuring better security. Comparative analysis demonstrates the suitability of NextGenV2V in next-generation vehicular networks.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Eric Ossongo, Moez Esseghir, Leila Merghem-Boulahia
Summary: The implementation of 5G networks allows for the efficient coexistence of heterogeneous services in a single physical virtualized infrastructure. Virtualization of network functions enables more flexible resource management and customizable services. However, the increasing number of connected objects poses challenges in managing physical and virtual resources, requiring intelligent systems to ensure communication quality.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Suvrima Datta, U. Venkanna
Summary: The Internet of Things (IoT) enables real-time sensing and data transmission to make homes smarter. Effective device-type identification methods are crucial as the number of IoT devices continues to grow. In this paper, a P4-based gateway called PiGateway is proposed to classify and prioritize the type of IoT devices. By utilizing a decision tree model and flow rules, PiGateway enables real-time granular analysis and in-network classification of IoT traffic.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Fahad Razaque Mughal, Jingsha He, Nafei Zhu, Saqib Hussain, Zulfiqar Ali Zardari, Ghulam Ali Mallah, Md. Jalil Piran, Fayaz Ali Dharejo
Summary: This paper explores the relationship between heterogeneous cluster networks and federated learning, as well as the challenges of implementing federated learning in heterogeneous networks and the Internet of Things. The authors propose an Intra-Clustered FL (ICFL) model that optimizes computation and communication to select heterogeneous FL nodes in each cluster, enabling efficient processing of asynchronous data and ensuring data security.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Rajesh Kumar, Deepak Sinwar, Vijander Singh
Summary: This paper investigates the coexistence mechanisms between eMBB and URLLC traffic for resource scheduling in 5G. Through examining different approaches and performance metrics, it provides detailed insights for researchers in the field, and highlights key issues, challenges, and future directions.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Giovanni Nardini, Giovanni Stea
Summary: Digital Twins of Networks (DTNs) are proposed as digital replicas of physical entities, enabling efficient data-driven network management and performance-driven network optimization. DTNs provide simulation services for dynamic reconfiguration and fault anticipation, using discrete-event network simulators as the ideal tools. Challenges include centralized vs. distributed implementation, input gathering from the physical network, security issues and hosting. The possibilities of network simulation for what-if analysis are explored, with the concepts of lockstep and branching analysis defined.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Zhaolin Ma, Jiali You, Haojiang Deng
Summary: This paper presents the Distributed In-Network Name Resolution System (DINNRS), which leverages software-defined networking and Information-Centric Networking (ICN) paradigm to provide high scalability and minimal request delay. Our methods, including an enhanced marked cuckoo filter for fast resolving, achieve significant performance gains in simulation experiments.
COMPUTER COMMUNICATIONS
(2024)
Article
Computer Science, Information Systems
Yujie Wang, Ying Wang, Qingqing Liu, Yong Zhang
Summary: This paper proposes a dynamic indoor positioning method based on multi-scale metric learning of the channel state information (CSI). By constructing few-shot learning tasks, this method can achieve dynamic positioning using CSI signals without additional equipment. Experimental results show that compared to commonly used dynamic location and tracking algorithms, the proposed method has higher positioning accuracy and does not accumulate errors.
COMPUTER COMMUNICATIONS
(2024)
