Article
Telecommunications
Shanidul Hoque, Wasim Arif, Debarati Sen
Summary: This paper investigates the performance measuring parameters of spectrum handoff in cognitive radio networks, considering the impact of mobility and service time distributions. The proposed model is validated and compared through simulation and analysis.
VEHICULAR COMMUNICATIONS
(2022)
Article
Chemistry, Analytical
Vikas Srivastava, Parulpreet Singh, Praveen Kumar Malik, Rajesh Singh, Sudeep Tanwar, Fayez Alqahtani, Amr Tolba, Verdes Marina, Maria Simona Raboaca
Summary: A cognitive radio network (CRN) is an intelligent network that can detect unoccupied spectrum space without interfering with the primary user (PU). This study proposes the use of a metaheuristic algorithm based on machine learning, namely the support vector machine-based red deer algorithm (SVM-RDA), to dynamically check for available channels during spectrum handoff (SHO). The results show that the suggested method offers improved system performance with fewer handoffs.
Article
Computer Science, Information Systems
Maxime Mroue, Abbass Nasser, Benoit Parrein, Ali Mansour, Chamseddine Zaki, Eduardo Motta Cruz
Summary: This paper discusses a battery-powered Internet of Things assisting Cognitive Radio network and introduces an Eligibility Score-based strategy for managing data exchange to extend the battery life of end nodes.
INTERNET OF THINGS
(2021)
Article
Computer Science, Artificial Intelligence
Kaleem Arshid, Zhang Jianbiao, Iftikhar Hussain, Muhammad Salman Pathan, Muhammad Yaqub, Abdul Jawad, Rizwan Munir, Fahad Ahmad
Summary: This study proposes a second priority user transmission system using cooperative spectrum sensing, which achieves energy efficiency, improved sensing performance, increased throughput, and reduced handoff time through optimized energy usage and the utilization of a threshold approach.
EGYPTIAN INFORMATICS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Rodney Martinez Alonso, David Plets, Margot Deruyck, Luc Martens, Glauco Guillen Nieto, Wout Joseph
Summary: This paper presents a novel wireless network optimization algorithm for cognitive radio networks based on a cloud sharing-decision mechanism, which significantly reduces network power consumption, exposure, and spectrum usage. Compared to traditional designs, the cloud-based architecture achieved better results even in worst-case scenarios.
Article
Engineering, Electrical & Electronic
Sudipta Dey, Iti Saha Misra
Summary: This paper introduces a new spectrum handoff algorithm and continuous short-sensing strategy to improve the overall throughput of secondary users in a cognitive radio network. By deriving the minimum length of the target channel sequence based on network-specific parameters, and finding the optimum channel search time to minimize handoff delay, the proposed scheme enhances the performance of the network. Simulation results demonstrate increased throughput and improved mean opinion scores for different video applications, as well as increased maximum simultaneous calls for VoIP applications.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Imran Khan, Fahd N. Al-Wesabi, Marwa Obayya, Anwer Mustafa Hilal, Manar Ahmed Hamza, Mohammed Rizwanullah, Fahad Ahmed Al-Zahrani, Hirofumi Amano, Samih M. Mostafa
Summary: With the rapid development of wireless communication technology, cognitive radio (CR) has become a key technology to effectively utilize spectrum resources. Spectrum sensing, which includes the precise detection and identification of primary user (PU) signals, is crucial for cognitive radio. Classical sensing algorithms, such as energy detection and matched filter detection, have their limitations. The combination of multiple-input multiple-output (MIMO) with CR improves spectral efficiency and utilization. An iterative technique based on semidefinite programming (SDP) and minimum mean squared error (MMSE) is proposed to best utilize the PU spectrum while minimizing overall transmit power. Furthermore, a new method for max-min fairness beamforming is also proposed, which outperforms existing algorithms in terms of transmitted power and signal-to-interference plus noise ratio (SINR).
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Computer Science, Hardware & Architecture
Praveen Gorla, Vinay Chamola, Vikas Hassija, Nirwan Ansari
Summary: The 5G technology utilizes MIMO for increasing capacity and efficiency of the network, requiring effective resource management for reliable services, where blockchain technology plays a promising role to resolve spectrum under-utilization.
Article
Chemistry, Analytical
Anna Kaszuba-Checinska, Radoslaw Checinski, Piotr Gajewski, Jerzy Lopatka
Summary: The paper discusses the issue of waveform construction for mobile ad hoc networks with cognitive radio (MANET-CR), focusing on the importance of spectrum sensing and sharing for the effectiveness of this technique. The experiments show that utilizing sensing and cognitive management mechanisms can efficiently utilize the spectrum while maintaining reasonable management overhead costs.
Article
Computer Science, Information Systems
Guangqian Peng, Wei Wu
Summary: This paper investigates fusion schemes based on IRS-enhanced CSS, including soft combination and hard combination. Closed-form expressions for the average probability of detection are derived, showing that IRS-enhanced CSS outperforms other schemes in terms of detection performance. The proposed OSC scheme is superior to K-rank.
Article
Chemistry, Analytical
Bashayer Othman Aloufi, Wajdi Alhakami
Summary: Cognitive radio is a highly investigated technique in wireless networks that solves the spectrum shortage problem and enhances network performance and security. This paper proposes a lightweight MAC protocol for CR-WSNs, which achieves secure and mutual authentication. The protocol is proven to be immune to passive and active attacks through simulation and formal verification.
Article
Engineering, Electrical & Electronic
Malgorzata Wasilewska, Hanna Bogucka, H. Vincent Poor
Summary: This article explores reliable and secure spectrum sensing in cognitive radio using federated learning. It discusses the motivation, architectures, and algorithms of federated learning in spectrum sensing. It provides an overview of security and privacy threats on these algorithms and presents possible countermeasures. The article also includes illustrative examples and offers design recommendations for future cognitive radios.
IEEE COMMUNICATIONS MAGAZINE
(2023)
Article
Chemistry, Analytical
Deepanramkumar Pari, Jaisankar Natarajan
Summary: This research proposes a new approach that integrates 6G cognitive radio network and Internet of connected vehicles, addressing spectrum scarcity, communication reliability, and security issues through blockchain authentication, improved algorithms, and deep learning technology.
Article
Computer Science, Information Systems
D. Raghunatha Rao, T. Jayachandra Prasad, M. N. Giri Prasad
Summary: This paper proposes the use of the gannet optimization algorithm (GOA) to enable spectrum sensing (SS) in orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR). Through simulation, efficient CR communication without interference is ensured. The proposed GOA is employed to determine weights and make decisions, achieving effective CR communication. The research is evaluated using performance metrics such as mean square error and bit error rate.
Article
Computer Science, Information Systems
Pooja Ahuja, Preeti Sethi, Naresh Chauhan
Summary: Cognitive radio technology provides a solution to spectrum scarcity while introducing new security challenges.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Amandeep Kaur, Krishan Kumar
Summary: Due to the growing demand for wireless communication networking, the radio spectrum has become overcrowded. Cognitive Radio (CR) technology is considered a promising solution to address spectrum scarcity by dynamically and efficiently utilizing unused spectrum bands. However, selecting the optimal network remains a challenge for CR networks. Intelligent spectrum management techniques are needed for dynamic spectrum management in CR networks.
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
(2022)
Article
Sociology
Krishan Kumar
Summary: This article argues that one of the best ways to understand China's Belt and Road Initiative is to see it in the context of China's two-thousand-year history as an empire. By examining the characteristics of the Chinese Empire and the tribute system, the article aims to shed some light on the intentions behind the initiative proposed by Chinese leadership.
THEORY AND SOCIETY
(2022)
Article
Computer Science, Information Systems
Amandeep Kaur, Krishan Kumar
Summary: This paper investigates the issue of efficient utilization of wireless spectrum and proposes a resource allocation scheme based on multi-agent reinforcement learning. The scheme integrates machine learning and cognitive radio technology while benefiting from cloud computing support to improve performance.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Engineering, Electrical & Electronic
Mani Shekhar Gupta, Krishan Kumar
Summary: The heterogeneity nature of networks and group mobility are important characteristics that need to be studied in 5G vehicular cognitive radio networks. A novel network selection technique is proposed to overcome congestion caused by group mobility and improve network throughput.
PHYSICAL COMMUNICATION
(2022)
Article
Computer Science, Information Systems
Mani Shekhar Gupta, Krishan Kumar
Summary: This paper proposes a technique for achieving optimal resource selection in CR networks, which addresses the issue of spectrum scarcity through an auction framework and Stackelberg game.
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2022)
Review
Computer Science, Interdisciplinary Applications
Shaveta Dargan, Shally Bansal, Munish Kumar, Ajay Mittal, Krishan Kumar
Summary: Augmented Reality (AR) is a technology that modifies the perception of real-world images by overlaying digital data on them. It has diverse applications in various fields and is distinct from virtual reality.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Computer Science, Information Systems
Umang Ahuja, Sunil Singh, Munish Kumar, Krishan Kumar, Monika Sachdeva
Summary: This paper proposes a deep learning-based technique for automating the task of monitoring social distancing using surveillance cameras. The authors compared the performance of two object detection models and found that YOLOv3 demonstrated efficient performance.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Interdisciplinary Applications
Veenu Rani, Syed Tufael Nabi, Munish Kumar, Ajay Mittal, Krishan Kumar
Summary: Machine learning has made significant advances in image processing. Supervised learning relies on labeled data, while unsupervised learning learns from unlabeled data. Self-supervised learning is a type of unsupervised learning that enhances computer vision tasks. This review article provides an in-depth exploration of self-supervised learning and its applications, discussing terms, learning types, and challenges encountered in the process.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Telecommunications
Amandeep Kaur, Jaismin Thakur, Mukul Thakur, Krishan Kumar, Arun Prakash, Rajeev Tripathi
Summary: This paper investigates Dynamic Spectrum Access (DSA) paradigm with imperfect feedback for multiuser wireless network. It aims to design a distributed Deep Reinforcement Learning (DRL) based scheme with an objective of maximizing network utility. The proposed scheme exhibits robustness against the detrimental effects of the imperfect feedback.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2023)
Article
Telecommunications
Ashok Kumar, Krishan Kumar
Summary: The article introduces a technique that uses deep learning for signal detection and power allocation. By optimizing the solution, it achieves the desired outcome without the need for channel estimation. The experimental results validate the superiority of this method and evaluate its robustness compared to existing approaches.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2022)
Article
Computer Science, Information Systems
Harmandeep Kaur, Shally Bansal, Munish Kumar, Ajay Mittal, Krishan Kumar
Summary: Deep learning models are used to recognize offline handwritten Gurumukhi words with a holistic approach. Three characteristics of word pictures are extracted and used to train a Convolutional Neural Network (CNN). The trained CNN's performance is assessed using five performance measures. The proposed model achieves high accuracy rates surpassing existing state-of-the-art systems.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Alok Negi, Krishan Kumar
Summary: A novel automatic system for identifying human activity on the UTKinect dataset is implemented in this study using Residual learning-based Network ResNet-50 and transfer learning. The experimental results demonstrate excellent generalization capability with a high accuracy of 98.60% and a loss score of 0.02.
INTERNATIONAL JOURNAL OF MULTIMEDIA INFORMATION RETRIEVAL
(2023)
Article
Multidisciplinary Sciences
Meenakshi Mittal, Krishan Kumar, Sunny Behal
Summary: The existing research in network security has used publicly available emulated datasets for validating defense mechanisms. However, the suitability and relevance of these datasets for DDoS defense remain an issue. This paper presents a DDoS-Testbed and an emulation-based dataset for DDoS attacks at the Application and Transport layer. The generated dataset contains a mixture of legitimate traffic, flash traffic, and various DDoS attacks, which can be helpful for validating new DDoS defense mechanisms.
PROCEEDINGS OF THE INDIAN NATIONAL SCIENCE ACADEMY
(2023)
Article
Computer Science, Information Systems
Nidhi Sharma, Krishan Kumar
Summary: The ultra-dense network structure of 5G with dense femto-cells deployment is seen as a solution to the increasing demand for cellular services. An efficient two-stage cluster-based resource allocation scheme is proposed to overcome interferences and achieve efficient resource allocation. It includes a dynamic clustering algorithm and a cloud-based multi-agent reinforcement learning algorithm to improve energy efficiency with a guarantee of quality of service (QoS).
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
(2023)
Article
Telecommunications
Amandeep Kaur, Krishan Kumar, Arun Prakash, Rajeev Tripathi
Summary: In this paper, the authors focus on the resource management optimization problem in IoT systems. They transform it into a Markov Decision Process and propose a Deep Recurrent Reinforcement Learning scheme to solve it. The scheme considers energy-efficiency and deals with partial observability from limited information. They introduce a cooperative framework and a Gated Recurrent Unit layer to improve the resource allocation policy. Extensive simulations demonstrate the superior performance of the proposed scheme in terms of convergence speed and reward, while also highlighting the importance of robust and intelligent design to maintain users' QoS.
IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING
(2023)
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)
