Faculty Publications
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Item Congestion control mechanisms in vehicular networks: A perspective on Internet of vehicles (IoV)(Elsevier, 2022) Patil, A.; Muthuchidambaranathan, P.; Shet, N.S.V.Developing congestion control in highly mobile vehicular networks is a challenging task. The network of vehicles or heavy vehicles uses different data for communication depending on the required application. These networks are one of the main components of the Internet of Things (IoT), and the aim is to connect every vehicle to every other vehicle for the purpose of improving the user’s quality of life. To provide better network accessibility, channel utilization, and speedy delivery of the information over these networks, congestion control plays a significant role. In this chapter, we present various congestion control mechanisms for vehicular networks by considering different applications in these networks. The decentralized and centralized mechanisms are presented and their use in different types of vehicular networks is also suggested. In the end, we have listed some challenges to help researchers to expand their research in this area. © 2022 Elsevier Inc.Item Improving Download Throughput by Saving the Transmission Bandwidth in Vehicular Networks(Springer Verlag, 2019) Patil, A.; Shet, N.S.V.Internet of vehicles focuses on globalization of vehicular networks by providing better communication means between vehicles and other infrastructures also between vehicles and human. The efficient data transfer between moving vehicles as well as between vehicles and roadside units is one of the current demands of vehicular network standards. Index coding has proven its significance in reducing number of transmissions in wireless networks. In this paper, we focus on satisfying demands of multiple clients with reduced number of transmissions at server. The proposed contention-based protocol uses index coding to reduce transmissions. Multiple files can be transmitted in a single file using index coding, which eventually reduce transmissions and also save transmission bandwidth. The effect of vehicle speed and available number of clients on the system throughput is presented in this paper. Simulation results show that our proposed design achieves higher throughput than IEEE 1609.4 and VEMMAC, and it also saves the transmission bandwidth at server, since multiple files are transmitted in a single transmission. © 2019, King Fahd University of Petroleum & Minerals.Item A hierarchical blockchain architecture for secure data sharing for vehicular networks(Springer Science and Business Media B.V., 2023) Srinivasan, K.S.; Divakarla, U.; Chandrasekaran, K.; Reddy, K.H.K.Data sharing is common phenomenon between the stakeholders within an organization and it is vital to sustain in the context of application. Internet of Things (IoT) is an umbrella of all applications’ online services like smart city, smart agriculture, smart grid and smart vehicles. In case of autonomous vehicular network (AVN), the data generated by vehicles, sensing units and road side units (RSU) is sensitive in nature so, secure data sharing (SDS) in AVN is the prime importance. In the area of SDS, Blockchain is gaining popularity which is an immutable distributed ledger technology and emerged as one of the prime solutions towards secure data sharing. As an innovative contribution, we proposedBlockchain based hierarchical secure data sharing model for sharing within vehicular network (VN). The proposed architecture is able to share road traffic related information e.g., road conditions, traffic congestion with the nearby vehicles and other stakeholders in the vehicular network. The performance of the proposed model is analyzed by using a simulation study and the efficacy of the simulated results outperforms than that of existing models. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.Item Optimized security algorithm for connected vehicular network(Emerald Publishing, 2023) Choudhary, D.Purpose: As the number of devices that connect to the Internet of Things (IoT) has grown, privacy and security issues have come up. Because IoT devices collect so much sensitive information, like user names, locations, phone numbers and even how they usually use energy, it is very important to protect users' privacy and security. IoT technology will be hard to use on the client side because IoT-enabled devices do not have clear privacy and security controls. Design/methodology/approach: IoT technology would be harder to use on the client side if the IoT did not offer enough well-defined ways to protect users’ privacy and security. The goal of this research is to protect people's privacy in the IoT by using the oppositional artificial flora optimization (EGPKC-OAFA) algorithm to generate the best keys for the ElGamal public key cryptosystem (EGPKC). The EGPKC-OAFA approach puts the most weight on the IEEE 802.15.4 standard for MAC, which is the most important part of the standard. The security field is part of the MAC header of this standard. In addition, the MAC header includes EGPKC, which makes it possible to make authentication keys as quickly as possible. Findings: With the proliferation of IoT devices, privacy and security have become major concerns in the academic world. Security and privacy are of the utmost importance due to the large amount of personally identifiable information acquired by IoT devices, such as name, location, phone numbers and energy use. Client-side deployment of IoT technologies will be hampered by the absence of well-defined privacy and security solutions afforded by the IoT. The purpose of this research is to present the EGPKC with optimum key generation using the EGPKC-OAFA algorithm for the purpose of protecting individual privacy within the context of the IoT. The EGPKC-OAFA approach is concerned with the MAC standard defined by the IEEE 802.15.4 standard, which includes the security field in its MAC header. Also, the MAC header incorporates EGPKC, which enables the fastest possible authentication key generation. In addition, the best methodology award goes to the OAFA strategy, which successfully implements the optimum EGPKC selection strategy by combining opposition-based (OBL) and standard AFA ideas. The EGPKC-OAFA method has been proved to effectively analyze performance in a number of simulations, with the results of various functions being identified. Originality/value: In light of the growing prevalence of the IoT, an increasing number of people are becoming anxious about the protection and confidentiality of the personal data that they save online. This is especially true in light of the fact that more and more things are becoming connected to the internet. The IoT is capable of gathering personally identifiable information such as names, addresses and phone numbers, as well as the quantity of energy that is used. It will be challenging for customers to adopt IoT technology because of worries about the security and privacy of the data generated by users. In this work, the EGPKC is paired with adversarial artificial flora, which leads in an increase to the privacy security provided by EGPKC for the IoT (EGPKC-OAFA). The MAC security field that is part of the IEEE 802.15.4 standard is one of the areas that the EGPKC-OAFA protocol places a high focus on. The Authentication Key Generation Protocol Key Agreement, also known as EGPKCA, is used in MAC headers. The abbreviation for this protocol is EGPKCA. The OAFA technique, also known as the combination of OBL and AFA, is the most successful method for selecting EGPKCs. This method is recognized by its acronym, OAFA. It has been shown via a variety of simulations that the EGPKC-OAFA technique is a very useful instrument for carrying out performance analysis. © 2022, Emerald Publishing Limited.Item Utilization of Quantum Random Numbers in Crystal-Kyber based Post Quantum Virtual Private Network for Vehicular Communication(Institute of Electrical and Electronics Engineers Inc., 2025) Sawant, S.V.; Rudra, B.Virtual Private Networks (VPN) have greatly contributed towards enhancing the data security of users over the Internet. Even extension of office environment and remote access is possible due to VPNs. However, the current VPN technologies pose a threat from Quantum-Powered Adversaries as these systems can break the Public Key Encryption Schemes used by VPN to share session keys. Moreover, these systems are also capable to guess random numbers generated using Pseudo-random generators. In this paper, we propose a True Random Number based Crystal Kyber Post Quantum Virtual Private Network (PQVPN) and analyse its strength with respect to classical and quantum adversaries. We also present our comparison against other PQVPN solutions and discuss its viability in Vehicular Network. © 2004-2012 IEEE.Item CAR-BRAINet: Sub-6 GHz aided spatial adaptive beam prediction with multi head attention for heterogeneous vehicular networks(Institute of Physics, 2025) Menon, A.G.; Krishnan, P.; Lal, S.Heterogeneous Vehicular Networks (HetVNets) play a crucial role by integrating different communication technologies, such as sub-6 GHz, mm-wave, and DSRC, to meet the diverse connectivity requirements of 5G/B5G vehicular networks. HetVNet helps address humongous user demands, but maintaining a steady connection in highly mobile, real-world conditions remains challenging. Though ample studies have been conducted on beam prediction models, a dedicated solution for HetVNets has been sparsely explored. Hence, developing a reliable beam prediction model, specifically for HetVNets, is necessary. This paper introduces a lightweight deep learning-based model termed ‘CAR-BRAINet’, which consists of convolutional neural networks with a powerful multi-head attention (MHA) mechanism. Existing literature on beam prediction is primarily studied under a limited, idealised vehicular scenario, often overlooking the real-time complexities and intricacies of vehicular networks. Therefore, this study aims to mimic the complexities of a real-time driving scenario by incorporating key factors, such as prominent MAC protocols (3GPP-C-V2X and IEEE 802.11BD), the effect of Doppler shifts under high velocity and varying distance, and SNR levels, into three high-quality dynamic data sets for urban, rural, and highway vehicular networks. CAR-BRAINet achieves a steady improvement of 11.6467% in spectral efficiency, with a 93.1638% lighter architecture compared to existing methods, resulting in a 94.7103% reduction in prediction time. Therefore, demonstrating a precise beam prediction across all vehicular scenarios, with minimal beam overhead. Thus, this study justifies the effectiveness of CAR-BRAINet in complex HetVNets, offering promising performance without relying on mobile users’ location, angle, and antenna dimensions, thereby reducing redundant sensor latency. © 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.