Article
Computer Science, Information Systems
Ishtiaq Wahid, Sadaf Tanvir, Masood Ahmad, Fasee Ullah, Ahmed S. AlGhamdi, Murad Khan, Sultan S. Alshamrani
Summary: Vehicular ad hoc networks (VANETs) are becoming increasingly important in the field of intelligent transportation systems, with continuous research and proposed routing schemes to enhance functionality. Surveys of routing schemes proposed in the past eight years help new scholars understand the existing state-of-the-art systems and analyze them.
Article
Computer Science, Information Systems
Ammar Hawbani, Xingfu Wang, Ahmed Al-Dubai, Liang Zhao, Omar Busaileh, Ping Liu, Mohammed A. A. Al-Qaness
Summary: This study proposes a solution to the problem of multicriteria multihop routing in vehicular ad hoc networks (VANETs) and introduces the HERO protocol, which shows promising performance in terms of delivery success ratio, delivery delay, and communication overhead.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Engineering, Civil
Ping Liu, Xingfu Wang, Ammar Hawbani, Bei Hua, Liang Zhao, Zhi Liu
Summary: This article introduces the challenges and solutions for data transmission in Vehicular Ad Hoc Networks (VANETs). It proposes leveraging the beacon mechanism to realize traffic awareness, instead of using control packets. The feasibility of this approach is demonstrated through mathematical analysis and a concrete protocol to address technical challenges. Extensive simulation results show that the proposed protocol outperforms existing technologies in terms of packet delivery ratio, average delivery time, and network overhead.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Lanlan Rui, Zhibo Yan, Zuoyan Tan, Zhipeng Gao, Yang Yang, Xingyu Chen, Huiyong Liu
Summary: This paper proposes an intersection-based QoS routing algorithm for vehicular ad hoc networks (VANETs), which addresses issues of local optimization in the routing process. The algorithm considers connectivity, delay, and communication quality in the selection of the next intersection, and utilizes reinforcement learning for the selection of the next hop vehicle. Simulation results demonstrate that the proposed algorithm outperforms other routing algorithms in terms of packet delivery ratio and transmission delay.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Jian Shen, Chen Wang, Aniello Castiglione, Dengzhi Liu, Christian Esposito
Summary: This paper proposes a novel routing protocol for vehicular ad hoc networks, called trustworthiness evaluation-based routing protocol (TERP), which calculates the trustworthiness of each individual using cloud computing and selects reliable forward nodes based on the trustworthiness to complete the route. The simulation results show that the protocol has good performance in terms of packet delivery ratio, normalized routing overhead, and average end-to-end delay.
IEEE TRANSACTIONS ON BIG DATA
(2022)
Article
Engineering, Civil
Long Luo, Li Sheng, Hongfang Yu, Gang Sun
Summary: A V2X routing protocol based on intersections is proposed, utilizing Q-learning and real-time monitoring to optimize routing decisions through multidimensional Q-tables and an improved greedy strategy, reducing communication overhead and latency to ensure reliable packet transmission.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Leticia Lemus Cardenas, Ahmad Mohamad Mezher, Pablo Andres Barbecho Bautista, Juan Pablo Astudillo Leon, Monica Aguilar Igartua
Summary: Vehicular networks rely on intelligent routing protocols to enhance safety and efficiency, with an increasing trend towards using machine learning algorithms for data-driven predictions. The proposed ML-based routing protocol for VANETs demonstrates improved performance in urban scenarios, reducing packet losses and delays even in complex environments.
Article
Telecommunications
Farooque Hassan Kumbhar, Soo Young Shin
Summary: The proposed scheme utilizes VAR(2) to achieve autonomous trust and select routes with the longest connectivity time for efficient message delivery. Simulation results show that the proposed routes have connectivity times of 100 to 400 seconds within three to four hops, achieving 6 to 15% packet delivery ratio, which are more efficient compared to existing schemes.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Farooque Hassan Kumbhar, Soo Young Shin
Summary: The sixth-generation cellular networks incorporate artificial intelligence and machine learning to enable proactive communications and predictive decision making, promoting the Internet of Vehicles concept. The existing vehicular communications face challenges in unreliable communication links due to multihop ad hoc communications and high mobility environment. This study highlights the importance of communication route compatibility and proposes a machine learning and analytical compatibility-based ad hoc routing protocol to estimate and predict compatibility time for route selection.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Dinesh Mavaluru, Murali Krishna Enduri, Akila Thiyagarajan, Satish Anamalamudi, Karthik Srinivasan, Chettupally Anil Carie, Bayapa Reddy Narapureddy
Summary: This paper presents an AI-based reactive routing protocol to improve network throughput and minimize the impact of node mobility, spectrum mobility, link traffic load, and end-to-end network traffic load on vehicular image transmission. Additionally, the performance of the proposed routing protocol is compared with existing proactive and reactive routing protocols in vehicular ad hoc IoT networks.
Article
Computer Science, Information Systems
Farooque Hassan Kumbhar, Soo Young Shin
Summary: The study investigates the use of machine learning-based classifications in VANETs for improved routing and message delivery efficiency. By leveraging a fog node architecture, higher packet delivery ratio and longer connectivity were achieved.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Information Systems
Rezoan Ahmed Nazib, Sangman Moh
Summary: Vehicular-ad hoc networks (VANETs) are important, and reinforcement learning (RL) algorithms can improve the efficiency of VANET routing.
Article
Computer Science, Information Systems
Leticia Lemus Cardenas, Juan Pablo Astudillo Leon, Ahmad Mohamad Mezher
Summary: The Intelligent Transport System (ITS) is becoming a reality as modern vehicles with artificial intelligence techniques enable novel solutions for smart cities. With wireless devices embedded in vehicles, valuable traffic management data can be transmitted for various purposes. Vehicular Ad hoc Networks (VANETs) facilitate wireless communications in vehicles and between vehicles and infrastructure to improve city services. However, routing information in VANETs is challenging due to the mobility and constraints of vehicles. This work proposes a multimetric machine learning-based routing protocol to improve the performance of vehicular networks, using the CatBoost framework and selecting relevant routing metrics.
Article
Computer Science, Hardware & Architecture
Ahmad Mohamad Mezher, Monica Aguilar Igartua
Summary: This paper presents a novel game-theoretical approach for developing a multimetric geographical routing protocol in vehicular ad hoc networks (VANETs), specifically for forwarding video-reporting messages in smart cities. The approach utilizes game theory to analyze and optimize resource allocation problems, resulting in enhanced performance of VANETs in urban scenarios.
Article
Engineering, Civil
Ida Mirzadeh, Mohammad Sayad Haghighi, Alireza Jolfaei
Summary: This paper proposes a trust-aware cognitive framework to filter malicious messages and detect and isolate malicious entities through a supplementary mechanism. The evaluation demonstrates that the proposed scheme outperforms other methods in terms of accuracy and F1 scores.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Hakam Singh, Vipin Rai, Neeraj Kumar, Pankaj Dadheech, Ketan Kotecha, Ganeshsree Selvachandran, Ajith Abraham
Summary: This study introduces an enhanced whale optimization algorithm (EWOA) for clustering problems. By incorporating the position update equations from the water wave optimization algorithm and adding tabu and neighbourhood search mechanisms, the algorithm improves the search space and accelerates the convergence rate. Experimental results demonstrate the applicability and feasibility of the enhancements and the superiority of the proposed EWOA clustering algorithm.
MULTIMEDIA TOOLS AND APPLICATIONS
(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
Computer Science, Theory & Methods
Anichur Rahman, Kamrul Hasan, Dipanjali Kundu, Md. Jahidul Islam, Tanoy Debnath, Shahab S. Band, Neeraj Kumar
Summary: The individual and integrated use of IoT, ICN, and FL in network-related scenarios has gained significant attention in the research community. FL addresses privacy and security issues in a decentralized manner, while ICN retrieves and stores content based on content names rather than addresses. The upcoming 6G networks are expected to support massive IoT devices, and this research highlights the potential of ICN for IoT applications. This study provides a comprehensive survey of FL, IoT, and ICN, and discusses their integration and future directions.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(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
Computer Science, Artificial Intelligence
Jerry W. Sangma, Yogita, Vipin Pal, Neeraj Kumar, Riti Kushwaha
Summary: This article proposes a fuzzy hierarchical clustering method for clustering multiple nominal data streams using the clustering-by-variable approach. The method calculates the fuzzy affinity of data streams to different clusters using normalized cosine similarity and updates the hierarchical clustering structure based on changes in node entropy. Experimental results show that the proposed method outperforms other methods in terms of cluster quality and has great potential in capturing fuzzy clusters.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(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
Engineering, Electrical & Electronic
Na Lin, Dewei Zhao, Liang Zhao, Ammar Hawbani, Mohsen Guizani, Neeraj Kumar
Summary: The software-defined vehicular networking (SDVN) paradigm alleviates the deficiencies brought on by distributed vehicular. In this paper, we propose an adaptive link-state perception scheme (ALPS) for SDVN, which enables the controller to timely obtain the link-state within the beacon interval. ALPS obtains the link-state by detecting packet loss on a link, and includes a link quality evaluation method based on fuzzy logic and an adaptive threshold adjustment method to decrease the detection cost. Simulation results demonstrate that ALPS can effectively reduce packet loss ratio at a low cost.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Tauheed Ahmed, Shabnam Samima, Mohd Zuhair, Hemant Ghayvat, Muhammad Ahmed Khan, Neeraj Kumar
Summary: Safeguards against illegitimate access and identification are necessary in the Internet of Medical Things (IoMT) domain. Existing user identification schemes struggle with impersonation attacks, leaving systems vulnerable. This study explores the use of multimodal biometrics, specifically fingerprint and iris modalities, to develop an identification and access control system for the healthcare ecosystem.
IEEE INTERNET OF THINGS JOURNAL
(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
Computer Science, Information Systems
Sameer Farooq, Priyanka Chawla, Neeraj Kumar
Summary: Cloud technology has revolutionized the computer paradigm by transforming offline systems into powerful interactive ones. However, ensuring security and accessibility of cloud-stored data remains a challenge. This article presents a four-phased security paradigm for safeguarding data from IoT devices transmitted to fog servers.
SECURITY AND PRIVACY
(2023)
Article
Engineering, Civil
Muhammad Ayzed Mirza, Junsheng Yu, Salman Raza, Manzoor Ahmed, Muhammad Asif, Azeem Irshad, Neeraj Kumar
Summary: This paper proposes a mobility, contact, and computational load-aware (MCLA) task offloading scheme for heterogeneous vehicular edge computing networks, which integrates different wireless technologies to improve network performance and meet low-latency and cost constraints. The scheme leverages the computational power of public vehicles and shareable computations from passengers' mobile equipment to enhance computation capacity. Extensive evaluations show that the MCLA scheme significantly improves task turnover ratio by 4%-15% with lower transmission and computation costs of 4.7%-29.8%.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
