Routing in Vehicular Ad Hoc Networks (VANETs) is a challenging problem. While geographic routing protocols are preferred for VANETs due to their scalability, they are focused on finding next-hop ...nodes closer to the destination without considering their current load or network traffic. In addition, routing decisions based on only one-hop neighbors information might be less optimal since they do not consider the availability of further suitable nodes for forwarding. Thus, such selected next-hop nodes may become overloaded with too much traffic that exceeds their available bandwidth, and may even result in significant packet losses if no other node suitable for forwarding can be found. In this paper, we propose a novel geographic routing protocol named Geo-LU. The proposed protocol improves the routing performance by extending the local view of the network topology at the current forwarder to include two-hop neighbor information. Moreover, it utilizes our proposed link utility (LU) measure. LU considers the utility of a two-hop neighbor link by considering the minimum residual bandwidth on that link and its packet loss rate. By incorporating two-hop neighbor information and our proposed LU measure, the proposed protocol, Geo-LU, can react appropriately to the increased network traffic and to the frequent topology dis-connectivity in VANETs as confirmed by our simulation results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Vehicular ad hoc networks (VANETs) are envisioned as the future of intelligent transportation systems, which enable various kinds of applications aiming at improving road safety and transportation ...efficiency. Uni-cast routing is required for many of these applications. As VANET is expected to be massive in terms of number of nodes and amount of generated information, geographic routing protocols are considered the most suitable for such network owing to their scalability. Due to VANETs' extremely dynamic topology and variable channel condition, multiple metrics related to vehicles' mobility, link quality, and bandwidth availability need to be considered to make more informed and reliable routing decisions. However, some of these metrics might oppose each other. While the main forwarding strategy in geographic routing selects nodes closer to the destination to maximize distance progress, these nodes are most probably located at the border of the communication range where the probability of link breakage increases. Furthermore, the continuous selection of these nodes without considering their available bandwidth might result in higher packet delays and losses. This paper proposes a novel routing protocol based on fuzzy logic systems, which can help in coordinating and analyzing contradicting metrics. The proposed routing protocol combines multiple metrics considering vehicles' position, direction, link quality, and achievable throughput to select the most suitable next-hop for packet forwarding. Results from our simulation experiments of relatively dense urban environments show remarkable performance improvements in terms of packet delivery ratio, end-to-end delay, and total network throughput.
A Drone-Aided Blockchain-Based Smart Vehicular Network Cheema, Muhammad Asaad; Shehzad, Muhammad Karam; Qureshi, Hassaan Khaliq ...
IEEE transactions on intelligent transportation systems,
07/2021, Volume:
22, Issue:
7
Journal Article
Peer reviewed
Open access
The staggering growth of the number of vehicles worldwide has become a critical challenge resulting in tragic incidents, environment pollution, congestion, etc. Therefore, one of the promising ...approaches is to design a smart vehicular system as it is beneficial to drive safely. Present vehicular system lacks data reliability, security, and easy deployment. Motivated by these issues, this paper addresses a drone-enabled intelligent vehicular system, which is secure, easy to deploy and reliable in quality. Nevertheless, an increase in the number of operating drones in the communication networks makes them more vulnerable towards the cyber-attacks, which can completely sabotage the communication infrastructure. To tackle these problems, we propose a blockchain-based registration and authentication system for the entities such as drones, smart vehicles (SVs) and roadside units (RSUs). This paper is mainly focused on the blockchain-based secure system design and the optimal placement of drones to improve the spectral efficiency of the overall network. In particular, we investigate the association of RSUs with the drones by considering multiple communication-related factors such as available bandwidth, maximum number of links a drone can support, and backhaul limitations. We show that the proposed model can easily be overlaid on the current vehicular network reaping benefits of secure and reliable communications.
In multi-party interactive live streaming, each user can act as both the sender and the receiver of a live video stream. Designing adaptive bitrate (ABR) algorithm for such applications poses three ...challenges: (i) due to the interaction requirement among the users, the playback buffer has to be kept small to reduce the end-to-end delay; (ii) the algorithm needs to decide what is the bitrate to receive and what is the set of bitrates to send ; (iii) the delay and quality requirements between each pair of users may differ, for instance, depending on whether the pair is interacting directly with each other. To address these challenges, we first develop a quality of experience (QoE) model for multi-party live streaming applications. Based on this model, we design MultiLive , an adaptive bitrate control algorithm for the multi-party scenario. MultiLive models the many-to-many ABR selection problem as a non-linear programming problem. Solving the non-linear programming equation yields the target bitrate for each pair of sender-receiver. To alleviate system errors during the modeling and measurement process, we update the target bitrate through the buffer feedback adjustment. To address the throughput limitation of the uplink, we cluster the ideal streams into a few groups, and aggregate these streams through scalable video coding for transmissions. We also deploy the algorithm on a commercial live streaming platform that provides such services for more than 2300 users. The experimental results show that MultiLive outperforms the fixed bitrate algorithm, with 2-<inline-formula> <tex-math notation="LaTeX">5\times </tex-math></inline-formula> improvement in average QoE. Furthermore, the end-to-end delay is reduced to around 100 ms, much lower than the 400 ms threshold recommended for video conferencing.
The dispersion that arises when packets traverse a network carries information that can reveal relevant network characteristics. Using a fluid-flow model of a bottleneck link with first-in first-out ...multiplexing, accepted probing tools measure the packet dispersion to estimate the available bandwidth, i.e., the residual capacity that is left over by other traffic. Difficulties arise, however, if the dispersion is distorted compared to the model, e.g., by non-fluid traffic, multiple bottlenecks, clustering of packets due to interrupt coalescing, and inaccurate time-stamping in general. It is recognized that modeling these effects is cumbersome if not intractable. This motivates us to explore the use of machine learning in bandwidth estimation. We train a neural network using vectors of the packet dispersion that is characteristic of the available bandwidth. Our testing results reveal that even a shallow neural network identifies the available bandwidth with high precision. We also apply the neural network under a variety of notoriously difficult conditions that have not been included in the training, such as randomly generated networks with the multiple bottleneck links and heavy cross traffic burstiness. Compared to two state-of-the-art model-based techniques as well as a recent machine learning-based technique (Yin et al., 2016), our neural network approach shows improved performance. Further, our neural network can effectively control the estimation procedure in an iterative implementation. We also evaluate our method with other supervised machine learning techniques.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In the modern era, with the emergence of the Internet of Things (IoT), big data applications, cloud computing, and the ever-increasing demand for high-speed internet with the aid of upgraded telecom ...network resources, users now require virtualization of the network for smart handling of modern-day challenges to obtain better services (in terms of security, reliability, scalability, etc.). These requirements can be fulfilled by using software-defined networking (SDN). This research article emphasizes one of the major aspects of the practical implementation of SDN to enhance the QoS of a virtual network through the load management of network servers. In an SDN-based network, several servers are available to fulfill users' hypertext transfer protocol (HTTP) requests to ensure dynamic routing under the influence of the SDN controller. However, if the number of requests is directed to a specific server, the controller is bound to follow the user-programmed instructions, and the load on that server is increased, which results in (a) an increase in end-to-end user delay, (b) a decrease in the data transfer rate, and (c) a decrease in the available bandwidth of the targeted server. All of the above-mentioned factors will result in the degradation of network QoS. With the implementation of the proposed algorithm, dynamic active sensing server load management (DASLM), on the SDN controller, the load on the server is shared based on QoS control parameters (throughput, response time, round trip time, etc.). The overall delay is reduced, and the bandwidth utilization along with throughput is also increased.
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Heterogeneous networks (HetNets) are becoming a promising solution for future wireless systems to satisfy the high data rate requirements. This paper introduces a stochastic geometry framework for ...the analysis of the downlink coverage probability in a multi-tier HetNet consisting of a macro-base station (MBS) operating at sub-6 GHz, millimeter wave (mmWave)-enabled unmanned aerial vehicles (UAVs) operating at 28 GHz, and small BSs operating both at mmWave and THz frequencies. The analytical expressions for the coverage probability for each tier have been derived in the paper. Monte Carlo simulations are then performed to validate the analytical expressions. The effectiveness of the HetNet is analyzed on various performance metrics including association and coverage probabilities for different network parameters. We show that the mmWave and THz-enabled cells provide significant improvement in the achievable data rates because of their high available bandwidths, however, they have a degrading effect on the coverage probability due to their high propagation losses.
Quality of Service provisioning for real-time multimedia applications is largely determined by a network’s available bandwidth. Until now, there is no standard method for estimating bandwidth on ...wireless networks. Therefore, in this study, a mathematical model called Modified Passive Available Bandwidth Estimation (MPABE) was developed to estimate the available bandwidth passively on a Distributed Coordination Function (DCF) wireless network on the IEEE 802.11 protocol. The mathematical model developed was a modification of three existing mathematical models, namely Available Bandwidth Estimation (ABE), Cognitive Passive Estimation of Available Bandwidth V2 (cPEAB-V2), and Passive Available Bandwidth Estimation (PABE). The proposed mathematical model gave emphasis on what will be faced to estimate available bandwidth and will help in building strategies to estimate available bandwidth on IEEE 802.11. The developed mathematical model consisted of idle period synchronisation between sender and receiver, the overhead probability occurring in the Medium Access Control (MAC) layer, as well as the successful packet transmission probability. Successful packet transmission was influenced by three variables, namely the packet collision probability caused by a number of neighbouring nodes, the packet collision probability caused by traffic from hidden nodes, and the packet error probability. The proposed mathematical model was tested by comparing it with other relevant mathematical models. The performance of the four mathematical models was compared with the actual bandwidth. Using a series of experiments that have been performed, it was found that the proposed mathematical model is approximately 26% more accurate than ABE, 36% more accurate than cPEABV2, and 32% more accurate than PABE.
To estimate available bandwidth of high-speed lines with high accuracy, we propose PathRefiner, a bandwidth estimation method with two techniques: (1) packet concatenation technique(2) iterative ...resolution refinement technique. It is one of the so-called packet train methods that estimate available bandwidth by transmitting multiple probing packets. (1) The packet concatenation technique virtually generates large packets necessary for estimating available bandwidth on high-speed lines by concatenating multiple packets of MTU size or smaller. (2) The iterative resolution refinement technique improves the resolution of estimation and enables highly accurate estimation of available bandwidth while minimizing the network load for estimation by finding the optimal number of large-sized virtual packets to be concatenated. As a result, the average value of the relative error between the ground truth and the estimated available bandwidth is relatively small (14.4%), confirming that PathRefiner can accurately estimate the available bandwidth of 1 Gbps high-speed lines.
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