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Joint Fuzzy Relays and Network-Coding-Based Forwarding for Multihop Broadcasting in VANETs
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In vehicular ad hoc networks (VANETs), due to the limited radio propagation range of wireless devices, many safety applications require a multihop broadcast protocol to disseminate traffic warning information. However, providing an efficient multi-hop forwarding of broadcast messages has been a challenging problem due to vehicle movement, limited wireless resources, and unstable signal strength. In this paper we propose a broadcast protocol that can provide a low message overhead and a high packet dissemination ratio. The proposed scheme uses a fuzzy logic algorithm to choose the next hop relay nodes and uses network coding to improve the packet dissemination ratio without increasing the message overhead. By using the fuzzy logic algorithm, the protocol can choose the best relay node by taking intervehicle distance, vehicle velocity, and link quality into account. Network coding is used to improve the packet reception ratio by utilizing the broadcast nature of wireless channels. We show the effectiveness of the proposed scheme by using both theoretical analysis and computer simulations.
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... To make relay selection more adaptive to network changes, artificial intelligence based mechanisms are designed. Fuzzy logic has been used in [4] and [25], which makes decision according to distance, moving direction and speed of vehicles. However, fuzzy logic is also dependent on thresholds and weights to be set in the rule base for making inferences. ...
... Probabilistic Assumptions / rules Local models trained prediction [20], [22] are not adaptable with different networks Fuzzy to network and the global model logic [4], [25] changes can cater network changes ...
... In this case, vehicle i is assigned as a relay node RLY at h = 1. All other Deep learning [7] Transmission power Fuzzy logic [25] × × Probabilistic prediction [22] × Link Stability [23] × Channel quality PoQF [20] × PoFL × × × vehicles continue to compete for becoming RLY at further hops until the message is forwarded up to h max number of hops. a) Privacy of PoFL based Message Dissemination: Table IV lists the parameters required to be shared by neighbor vehicles in various multi-hop relay selection approaches. ...
Message exchange among vehicles plays an important role in ensuring road safety. Emergency message dissemination is usually carried out by broadcasting. However, high vehicle density and mobility usually lead to challenges in message dissemination such as broadcasting storm and low probability of packet reception. This paper proposes a federated learning based blockchain-assisted message dissemination solution. Similar to the incentive-based Proof-of-Work consensus in blockchain, vehicles compete to become a relay node (miner) by processing the proposed Proof-of-Federated-Learning (PoFL) consensus which is embedded in the smart contract of blockchain. Both theoretical and practical analysis of the proposed solution are provided. Specifically, the proposed blockchain based federated learning results in more number of vehicles uploading their models in a given time, which can potentially lead to a more accurate model in less time as compared to the same solution without using blockchain. It also outperforms the other blockchain approaches for message dissemination by reducing 65.2% of time delay in consensus, improving at least 8.2% message delivery rate and preserving privacy of neighbor vehicle more efficiently. The economic model to incentivize vehicles participating in federated learning and message dissemination is further analyzed using Stackelberg game model.
... To make relay selection more adaptive to network changes, artificial intelligence based mechanisms are designed. Fuzzy logic has been used in [4] and [25], which makes decision according to distance, moving direction and speed of vehicles. However, fuzzy logic is also dependent on thresholds and weights to be set in the rule base for making inferences. ...
Message exchange among vehicles plays an important role in ensuring road safety. Emergency message dissemination is usually carried out by broadcasting. However, high vehicle density and mobility lead to challenges in message dissemination such as broadcasting storm and low probability of packet reception. This paper proposes a federated learning based blockchain-assisted message dissemination solution. Similar to the incentive-based Proof-of-Work consensus in blockchain, vehicles compete to become a relay node (miner) by processing the proposed Proofof-Federated-Learning (PoFL) consensus which is embedded in the smart contract of blockchain. Both theoretical and practical analysis of the proposed solution are provided. Specifically, the proposed blockchain based federated learning results in more vehicles uploading their models in a given time, which can potentially lead to a more accurate model in less time as compared to the same solution without using blockchain. It also outperforms other blockchain approaches in reducing 65.2% of time delay in consensus, improving at least 8.2% message delivery rate and preserving privacy of neighbour vehicle more efficiently. The economic model to incentivize vehicles participating in federated learning and message dissemination is further analysed using Stackelberg game. The analysis of asymptotic complexity proves PoFL as the most scalable solution compared to other consensus algorithms in vehicular networks.
... In [20], a bi-directional stable communication (BDSC) multi-hop broadcast scheme is proposed, which uses beacon messages to estimate the link quality of neighbors and assigns forwarding sequence and forwarding delay to candidate forwarders according to link quality. Wu et al. [21] propose a joint fuzzy relays and network coding-based forwarding (FUZZBR-NC) protocol, which uses a fuzzy logic algorithm to select the next-hop relay node based on the distance, mobility, and RSSI information of the neighbor nodes. FUZZBR-NC selects two forwarding nodes each time to forward packets simultaneously, and uses network coding to improve the packet dissemination ratio. ...
Beacon messages and emergency messages in vehicular ad hoc networks (VANETs) require a lower delay and higher reliability. The optimal MAC protocol can effectively reduce data collision in VANETs communication, thus minimizing delay and improving reliability. In this paper, we propose a Q-learning MAC protocol based on detecting the number of two-hop neighbors. The number of two-hop neighbors in highway scenarios is calculated with very little overhead using the beacon messages and neighbor locations to reduce the impact of hidden nodes. Vehicle nodes are regarded as agents, using Q-learning and beacon messages to train the near-optimal contention window value of the MAC layer under different vehicle densities to reduce the collision probability of beacon messages. Furthermore, based on the contention window value after training, a multi-hop broadcast protocol combined with contention window adjustment for emergency messages in highway scenarios is proposed to reduce forwarding delay and improve forwarding reliability. We use the trained contention window value and the state information of neighboring vehicles to assign an appropriate forwarding waiting time to the forwarding node. Simulation experiments are conducted to evaluate the proposed MAC protocol and multi-hop broadcast protocol and compare them with other related protocols. The results show that our proposed protocols outperform the other related protocols on several different evaluation metrics.
... With the rapid popularity of smart terminals, more and more advanced applications such as pilotless automobile, telemedicine and smart home, etc, have emerged [1]- [4]. Accordingly, both the number of connected devices and the volume of mobile data traffic have undergone an exponential growth in the past decade, highly demanding a substantial improvement in the capacity of mobile networks [5], [6]. ...
With the rapid popularity of smart terminals, the device-to-device(D2D) communication is recognized as one of the most promising techniques in the fifth-generation(5G) communications networks due to its capabilities of substantially improving the spectral efficiency, relieving the traffic burden in the base stations(BSs), and reducing the terminals’ power consumptions, etc. By properly activating some D2D links(DLs), the sum data rate of the D2D-aided cellular networks(CNs) can be substantially improved. However, constrained by the severe interference imposed on the conventional cellular users (CUs) by the activating D2D users (DUs), the sum data rate of the D2D-aided CNs cannot be unlimitedly improved in a crude way of simply increasing the number/density of DLs. In other words, there must exist a maximum/optimal number of activating DLs in terms of the sum data rate, as revealed in this paper. By identifying the maximum/optimal number of activating DLs, the closed-form expressions for sum data rates of both cellular links(CLs) and DLs can be obtained. Numerical results show that the optimum number of activating DLs, as a function of several critical parameters such as DU’s transmit power, signal-to-interference-plus-noise ratio threshold and outage probability of CLs/DLs, etc, can be determined by implementing the proposed algorithms.
... The media content demand of vehicular users is a major type of data traffic. In this context, the safety-related information shares the vast majority since the driving safety is always the first thing to concern, no matter human or intelligent vehicles [2][3][4][5]. In order to satisfy such content demand efficiently, vehicular content caching methods have been proposed [6]. ...
The safety driving-related content demands of vehicular users increase rapidly, especially with the development of the autonomous driving. It is significantly necessary to obtain the high-precision safety related transportation information of an area when vehicles are drove there, whether or not they are controlled by human being. However, vehicular content caching can bring issues in distributed-fashion, such as high response delay and low content response ratio because of the poor traffic condition and the obstructions of buildings. As a consequence, we adopt UAVs (Unmanned Aerial Vehicles) to assist the driving safety-related content caching for vehicles. Besides, since the power energy and the caching storage of UAVs are limited, it is needed to design an optimal caching scheme to guarantee the driving safety-related content demand of vehicular users as well as reduce the energy consumption of UAVs. In this paper, we propose a novel deep Q-learning based air-assisted vehicular caching scheme to respond to the driving safety-related content requests of vehicular users. First, a three-layered content response architecture is introduced, where an airship is leveraged to take charge of the scheduling of UAVs to improve the content response. Then, a multi-objective mathematical model is built to describe the specific problem of the proposed scheme. Finally, deep Q-learning is applied to solve the multi-objective problem by learning from the history content requests of vehicular users. Extensive experiments have been conducted which show the proposed scheme outperforms its counterparts in terms of content hit ratio, response delay, being scheduled probability and packet buffering time.
... Fuzzy logic-based systems can intelligently analyze different metrics even if they are inexact and opposing to one another, improve the decision-making process, and reduce the computation delays [24]. Recently, it comes as no surprise that fuzzy logic has been shown to be effective for VANET broadcast [25][26][27][28][29]. ...
In vehicular Ad Hoc Networks (VANETs), smart data dissemination is crucial for efficient exchange of traffic and road information. Given the dynamic nature of VANET, the challenge is to design an adaptive multi-hop broadcast scheme that achieves high reachability while efficiently utilizing the bandwidth by reducing the number of redundant transmissions. In this paper, we propose a novel intelligent fuzzy logic based density and distribution adaptive broadcast protocol for VANETs. The proposed protocol estimates the spatial distribution of vehicles in the network employing the Nearest Neighbor Distance method, and uses it to adapt the transmission range to enhance reachability. To reduce packet collisions, the protocol intelligently adapts the contention window size to the network density and spatial distribution. Bloom filter technique is used to reduce the overhead resulting from the inclusion of the neighbor IDs in the header of the broadcast message, which is needed in identifying the set of potential rebroadcasting vehicles. Our simulation results confirmed the effectiveness of the proposed scheme in enhancing reachability while efficiently utilizing bandwidth.
... R represents the transmission range of node. [20]. s n is the received signal strength of neighbor node n, s thr is the threshold value of the signal strength that can be received. ...
Vehicular named data networking (VNDN) has the data-centric and in-network caching advantages that are in line with the requirements of multi-hop content retrieval in vehicular ad hoc networks (VANETs). Some current restrictive forwarding strategies utilize single-path forwarding to mitigate the Interest broadcast storm in VNDN. However, these strategies do not provide any reliable mechanism for Interest and Data forwarding to address the problem of low performance caused by the dynamic and unreliable VANETs communication environment. In this paper, we propose a packet forwarding strategy based on optimal and backup (PFOB) for VNDN. For Interest, PFOB establishes a single-path forwarding with high reliability and reachability by increasing the signal strength and node-degree criterion and retransmission mechanism. For Data, PFOB provides a reliable multi-path backup forwarding mechanism without additional network overhead. Simulation results show that PFOB can effectively improve the Interest satisfaction ratio, reduce the number of application retransmissions, and reduce the Interest satisfaction delay compared to the current strategies.
... Many intelligent clustering schemes for VANETs were elaborated. 12,[24][25][26] Unfortunately, all these works apply passive intervehicle distances as one of main metrics used to select CHs. That is, these distances do not take into consideration the safe intervehicle distances which assist drivers to avoid collisions thus generating clusters' instability and frequent CHs reelections leading to higher overheads. ...
Vehicular ad hoc network (VANET) nodes are characterized by their high mobility and by exhibiting different mobility patterns. Therefore, VANET clustering schemes are required to account for the mobility parameters among neighboring nodes to produce relatively stable clustering schemes. In this article, we propose a novel cluster‐head (CH) selection scheme for VANETs. This scheme is based on a fuzzy logic‐powered, k‐hop distributed clustering algorithm. It deals efficiently with scalability and stability issues of VANETs and is able to achieve highly stable clustering topologies as compared with other schemes. Our proposed clustering scheme strives to maintain a safe intervehicle distance as a one prime metric for CH selection. Moreover, a major contribution of our work is the proposal of a novel strategy for constructing fuzzy logic‐based clustering algorithms useful for VANETs. This proposed solution is useful in an Internet of things‐based setting that involves controlled vehicle‐to‐vehicle communication. We first derive mathematically, a new average distance estimation formula that is used as a metric for selecting CHs, leading to safer clusters that avoid collisions with front and rear vehicles. Furthermore, the new proposed scheme creates stable clusters by reducing reclustering overhead and prolonging clusters' lifetimes. We propose a clustering scheme for VANETs that considers the safe interdistance between vehicles as one of important metrics for cluster head selection. We present a new strategy for constructing fuzzy clustering algorithms in VANETs. We first derive mathematically a new average distance estimation scheme that is used as metric to select cluster heads which provide safe clusters. This contributes to avoiding collisions and creating stable clusters by reducing reclustering overhead and prolonging cluster lifetime.
Cellular Vehicle-to-Everything (C-V2X) Mode 4, developed by 3GPP, supports vehicle-to-vehicle communication without a cellular base station via LTE sidelink. The messages transmitted in the Internet of Vehicles (IoV) include periodic single-hop broadcast Beacon messages and multi-hop broadcast Emergency messages triggered by events. In this paper, we analyze the impact of multi-hop broadcast of Emergency messages in C-V2X Mode 4 on the performance of Beacon messages and propose collision probability models for Beacon messages and Emergency messages. The non-periodicity nature and lower broadcast latency requirement of the multi-hop Emergency messages may cause resource allocation conflicts in the resource selection process of C-V2X Mode 4, thus result in forwarding collision of Emergency messages and collision of subsequent Beacon messages. Therefore, we propose several multi-hop broadcast schemes for Emergency messages to reduce the collision probability by assigning independent resource grants for Emergency messages and adjusting the number of forwarding nodes. The performance of Beacon messages and Emergency messages of several different forwarding schemes proposed are simulated. The simulation results show that the proposed broadcasting schemes significantly improve the performance of Beacon messages and Emergency messages.
Multi-hop broadcasting in Vehicular Ad Hoc Network (VANET) is the basic building block for renovating on-road travel experiences because it supports message dissemination among a large number of travelers in real-time. In order to make forwarding decisions, 1-hop neighbor table is suggested to be maintained at each vehicle by exchanging beacon packets on a periodic basis. However, a network crowded with both data packets and beacons gives rise to broadcast storms, resulting in insignificant resource consumption. Therefore, a beaconless approach would be a better solution that can control packet flow throughout the network, owing to minimizing packet collision and drop rate. Some recent literature that does not rely on beacon information broadcasts ample amounts of data packets, promoting wastage of bandwidth. To handle such issues, a Fuzzy-based Beaconless Probabilistic Broadcasting Algorithms (FBPBA) is proposed to notify vehicles about an event in less broadcasting. It is a receiver oriented broadcast suppression technique, where the forwarding probability of the packets in vehicles’ buffer is decided on the basis of their distance, angular orientation, movement direction and buffer load delay. The resultant probability is used to reschedule the packet. Among all the packets in the vehicle's buffer, the one having the highest priority at an instant is broadcasted first. For accident and advertisement packets, the analysis through simulation reveals that the proposed algorithm outperformed the compared protocols in terms of reachability (Information coverage), average delay and saved rebroadcast.
Mobile peer-to-peer systems have recently got in the lime-light of the research community that is striving to build efficient and effective mobile content addressable networks. Along this line of research, we propose a network coding based file swarming protocol targeting vehicular ad hoc net-works (VANET). We argue that file swarming protocols in VANET should deal with typical mobile network issues such as dynamic topology and intermittent connectivity as well as various other issues that have been disregarded in previous mobile peer-to-peer researches such as addressing, node/user density, non-cooperativeness, and unreliable channel. Through simulation, we show that the efficiency and effectiveness of our protocol allows shorter file downloading time compared to an existing VANET file swarming protocol.
In recent years, new applications, architectures, and technologies have been proposed for vehicular ad hoc networks (VANETs). Regarding traffic safety applications for VANETs, warning messages have to be quickly and smartly disseminated in order to reduce the required dissemination time and to increase the number of vehicles receiving the traffic warning information. In the past, several approaches have been proposed to improve the alert dissemination process in multihop wireless networks, but none of them were tested in real urban scenarios, adapting its behavior to the propagation features of the scenario. In this paper, we present the Profile-driven Adaptive Warning Dissemination Scheme (PAWDS) designed to improve the warning message dissemination process. With respect to previous proposals, our proposed scheme uses a mapping technique based on adapting the dissemination strategy according to both the characteristics of the street area where the vehicles are moving and the density of vehicles in the target scenario. Our algorithm reported a noticeable improvement in the performance of alert dissemination processes in scenarios based on real city maps.
In this chapter, we propose a new architecture for wireless mesh networks. In addition to forwarding packets, routers mix (i.e., code) packets from different sources to increase the information content of each transmission. We show that mixing packets intelligently increases network throughput. Our design is rooted in the theory of network coding. In contrast to prior work on network coding, which is primarily theoretical, the design herein focuses on practical issues. Our system introduces a coding layer between the IP and MAC layers, and integrates it into the current network stack. We evaluate the design using both simulation and prototype implementation, and show that it delivers a large increase in the throughput of congested wireless mesh networks.
In vehicular ad hoc networks (VANETs), a multi-hop broadcast protocol is required to disseminate traffic warning information. Reducing broadcast message overhead while maintaining a high dissemination ratio is a very challenging task. In this paper, we study how to improve the performance of sender-oriented broadcast protocols using network coding. We propose a scheme which uses network coding to improve the packet dissemination ratio without increasing the message overhead. In the proposed scheme, the source node specifies two relay nodes. With cooperation between two relay nodes, the proposed scheme significantly increases the packet reception ratio by utilizing the broadcast nature of wireless channel. We show the effectiveness of the proposed scheme by using both theoretical analysis and computer simulations.
In this paper, we analyze the current binary partition multi-hop broadcast protocol and propose an enhanced solution, namely, Trinary Partition Black-Burst based Broadcast Protocol (3P3B) for Emergency Message (EM) dissemination. 3P3B provides low and constant latency regardless density and size of networks compared to existing solutions. It also enhances message dissemination speed and message progress distance. The main technique in the 3P3B is that 3P3B uses mini-slot DIFS to give a preemptive priority to very urgent EMs and deploys a trinary partition mechanism to select the furthest forwarder of the next communication hop. We prove that 3P3B recues the delay, increases dissemination speed, message progress distance, and outperforms the well-known existing broadcast protocols for EM dissemination in VANET.
This paper proposes a generic geometry-based stochastic model for nonisotropic scattering vehicle-to-vehicle (V2V) Ricean fading channels. With the proposed model, the level crossing rate (LCR) and average fade duration (AFD) are derived. The resultant expressions are sufficiently general and subsume many well-known existing LCRs and AFDs as special cases. The derived LCR and AFD are further investigated in terms of some important parameters, e.g., the shape of the scattering region (two-ring or ellipse), mean angle, angle spread, and directions of movement of the Tx and Rx (same or opposite direction). More importantly, in this paper, the impact of the vehicular traffic density on the LCR and AFD for nonisotropic scattering V2V Ricean fading channels is investigated for the first time. Excellent agreement is observed between the theoretical LCRs/AFDs and corresponding measured data, thus demonstrating the validity and utility of the proposed model.
We propose a rank-based network coding scheme for distributing content in vehicular ad-hoc networks, in which vehicles adaptively broadcast packets based on the content reception status of their neighbors. In contrast to the previous work, CodeOn, vehicles in the proposed method only exchange content reception information in the service channel. The packet injection probability in the proposed method is proportional to the estimated innovation that a vehicle can provide to its neighbors. We also give an analytical model to analyze the system throughput when vehicles apply rank-based network coding to broadcast data. Simulation results demonstrate that the proposed method improves the throughput by more than 32% while maintaining lower end-to-end delay and protocol overhead than the previous work.
In this paper, we propose a secure cooperative data downloading framework for paid services in vehicular ad hoc networks (VANETs). In our framework, vehicles download data when they pass by a road side unit (RSU) and then share the data after they travel out of the RSU's coverage. A fundamental issue of cooperative data downloading is how vehicles effectively share data with each other. We develop an application layer data sharing protocol which coordinates the vehicles to relay data for sharing according to their positions. Such coordinated sharing can avoid collisions in the medium access control (MAC) layer and the hidden terminal issue in multi-hop transmissions. A salient feature of the proposed sharing protocol is that it can guarantee the receipt of the requested data file for each applicant vehicle passing a road side unit. Moreover, we also address security and privacy issues in the process of data downloading and sharing, ensuring applicants' exclusive access to the applied data and privacy of the vehicles involved in the application. We carry out NS2 simulations to thoroughly examine the performance of the proposed cooperative downloading protocol implemented over an 802.11p based VANETs.
In this paper, we propose a new regular-shaped geometry-based stochastic model (RS-GBSM) for non-isotropic scattering wideband multiple-input multiple-output vehicle-to-vehicle (V2V) Ricean fading channels. By correcting the unrealistic assumption widely used in current RS-GBSMs, the proposed model can more practically study the impact of the vehicular traffic density on channel statistics for different time delays. From the proposed model, we derive the Doppler power spectral density (PSD) and find that highly dynamic Doppler spectrum appears for V2V channels. Excellent agreement is achieved between the derived Doppler PSD and measured data, demonstrating the utility of the proposed model. To combat the intercarrier interference (ICI) caused by highly dynamic Doppler spectrum in real orthogonal frequency division multiplexing based V2V systems, this paper proposes a new type of ICI cancellation scheme, named as precoding based cancellation (PBC) scheme. The proposed scheme can be easily implemented into real V2V systems with the same ICI mitigation performance as the current best ICI cancellation scheme that has high complexity. To further improve the performance of the proposed PBC scheme, a new phase rotation aided (PRA) method, namely constant PRA (CPRA) method, is proposed. Compared with the existing PRA method, the CPRA method has better performance and much less implementation complexity. Therefore, the proposed PBC scheme with the CPRA method is the best ICI cancellation scheme for real V2V systems.