28 research outputs found

    A Comparative Survey of VANET Clustering Techniques

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    © 2016 Crown. A vehicular ad hoc network (VANET) is a mobile ad hoc network in which network nodes are vehicles - most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organized nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, information dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation, and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming - the lack of realistic vehicular channel modeling - is identified. The importance of a rigorous and standardized performance evaluation regime utilizing realistic vehicular channel models is demonstrated

    U2RV: UAV-assisted reactive routing protocol for VANETs

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    When it comes to keeping the data routing robust and effective in Vehicular Ad hoc Networks (VANETs), stable and durable connectivity constitutes the keystone to ensure successful point-to-point communication. Since VANETs can comprise all kinds of mobile vehicles moving and changing direction frequently, this may result in frequent link failures and network partitions. Moreover, when VANETs are deployed in a city environment, another problem arises, that is, the existing obstructions (e.g., buildings, trees, hoppers, etc.) preventing the line-of-sight between vehicles, thus degrading wireless transmissions. Therefore, it is more complicated to design a routing technique that adapts to frequent changes in the topology. In order to settle all these problems, in this work, we design a flooding scheme that automatically reacts at each topology variation while overcoming the present obstacles while exchanging data in ad hoc mode with drones that are commonly called Unmanned Aerial Vehicles (UAVs). Also, the aim of this work is to explore well-regulated routing paths providing a long lifetime connectivity based on the amount of traffic and the expiration time of each discovered path, respectively. A set of experiments is carried out using simulation, and the outcomes are confronted with similar protocols based on a couple of metrics. The results clearly show that the assistance of UAVs to vehicles is capable to provide high delivery ratios and low delivery delays while efficiently extending the network connectivity

    Social Clustering of Vehicles Based on Semi-Markov Processes

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    The full text version attached to this record is the authors final peer reviewed version. The publisher's final version of record can be found by following the DOI link.Vehicle clustering is a crucial network managementtask for vehicular networks in order to address the broadcaststorm problem, and also to cope with rapidly changing networktopology. Developing algorithms that createstable clustersis avery challenging procedure because of the highly dynamic movingpatterns of vehicles and the dense topology. Previous approachesto vehicle clustering have been based on either topology-agnosticfeatures, such as vehicle IDs, on hard to set parameters, orhave exploited very limited knowledge of vehicle trajectories.This article develops a pair of algorithms, namelySociologicalPattern Clustering (SPC), andRoute Stability Clustering (RSC),the latter being a specialization of the former that exploit, forthe first time in the relevant literature, the “social behavior”of vehicles, i.e. their tendency to share the same/similar routes.Both methods exploit the historic trajectories of vehiclesgatheredby road-side units located in each subnetwork of a city, anduse the recently introduced clustering primitive ofvirtual forces.The mobility, i.e. mobile patterns of each vehicle are modeledas semi-Markov processes. In order to assess the performanceof the proposed clustering algorithms, we performed a detailedexperimentation by simulation to compare its behavior withthat of high-performance state-of-the-art algorithms, namely, theLow-Id,DDVCandMPBCprotocols. The comparison involvedthe investigation of the impact of a range of parameters onthe performance of the protocols, including vehicle speed andtransmission range as well as the existence and strength of socialpatterns, for both urban and highway-like environments. Allthe received results attested to the superiority of the proposedalgorithms for creating stable and meaningful clusters

    On Adjacent Channel Interference-Aware Radio Resource Management for Vehicle-to-Vehicle Communication

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    Safety applications play an essential role in supporting traffic safety and efficiency in next generation vehicular networks. Typical safety applications require vehicle-to-vehicle (V2V) communication with high reliability and low latency. The reliability of a communication link is mainly determined by the received interference, and broadly speaking, there are two types of interferences: co-channel interference (CCI) and adjacent channel interference (ACI). The CCI is cross-talk between transmitters scheduled in the same time-frequency slot, whereas ACI is interference due to leakage of transmit power outside the intended frequency slot. The ACI is typically not a problem in cellular communication since interference is dominated by CCI due to spectrum re-usage. However, ACI is a significant problem in near-far situations, i.e., when the channel gain from the interferer to receiver is high compared to the channel gain from the intended transmitter. The near-far situation is more common in V2V broadcast communication scenario due to high dynamic range of the channel gain and penetration loss by intermediate vehicles. This thesis investigates the impact of ACI on V2V communication and methods to mitigate it by proper radio resource management (RRM), i.e., scheduling and power control.In [Paper A], we first study ACI models for various transmission schemes and its impact on V2V communication. We propose a problem formulation for a) optimal scheduling as a Boolean linear programming (BLP) problem and b) optimal power control as a mixed Boolean linear programming (MBLP) problem. The objective of the problem formulation is to maximize the connectivity among VUEs in the network. Near-optimal schedules and power values are computed by solving first a) and then b) for smaller size instances of the problem. To handle larger-size instances of the problem, heuristic scheduling and power control algorithms with less computational complexity are proposed. We also propose a simple distributed block interleaver scheduler (BIS), which can be used as a baseline method.In [Paper B], we formulate the joint scheduling and power control problem as an MBLP to maximize the connectivity among VUEs. A column generation method is proposed to address the scalability of the network, i.e., to reduce the computational complexity of the joint problem. Moreover, the scheduling problem is observed to be numerically sensitive due to the high dynamic range of channel values and adjacent channel interference ratio (ACIR) values. Therefore, a novel method is proposed to reduce the sensitivity and compute a numerically stable optimal solution at the price of increased computational complexity.In [Paper C], we extend the RRM problem formulation to include various objectives, such as maximizing connectivity/throughput and minimizing age of information (AoI). In order to account for the fairness, we also formulate the problem to improve the worst-case throughput, connectivity, and AoI of a link in the network. All the problems are formulated as MBLP problems. In order to support a large V2V network, a clustering algorithm is proposed whose computational complexity scale well with the network size. Moreover, a multihop distributed scheduling scheme is proposed to handle zero channel state information (CSI) case

    Road-based multi-metric forwarder evaluation for multipath video streaming in urban vehicular communication

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    In video streaming over vehicular communication, optimal selection of a video packet forwarder is a daunting issue due to the dynamic nature of Vehicular Ad-hoc NETworks (VANETs)and the high data rates of video. In most of the existing studies, extensive considerations of the essential metrics have not been considered. In order to achieve quality video streaming in vehicular network, important metrics for link connectivity and bandwidth efficiency need to be employed to minimize video packet error and losses. In order to address the aforementioned issues, a Road-based Multi-metric Forwarder Evaluation scheme for Multipath Video Streaming (RMF-MVS) has been proposed. The RMF-MVS scheme is adapted to be a Dynamic Self-Weighting score (DSW) (RMF-MVS+DSW) for forwarder vehicle selection. The scheme is based on multipath transmission. The performance of the scheme is evaluated using Peak Signal to Noise Ratio (PSNR), Structural SIMilarity index (SSIM), Packet Loss Ratio (PLR) and End-to-End Delay (E2ED) metrics. The proposed scheme is compared against two baseline schemes including Multipath Solution with Link and Node Disjoint (MSLND) and Multimedia Multi-metric Map-aware Routing Protocol (3MRP) with DSW (3MRP+DSW). The comparative performance assessment results justify the benefit of the proposed scheme based on various video streaming related metrics

    Reliability and Efficiency of Vehicular Network Applications

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    The DSRC/WAVE initiative is forecast to enable a plethora of applications, classified in two broad types of safety and non-safety applications. In the former type, the reliability performance is of tremendous prominence while, in the latter case, the efficiency of information dissemination is the key driving factor. For safety applications, we adopt a systematic approach to analytically investigate the reliability of the communication system in a symbiotic relationship with the host system comprising a vehicular traffic system and radio propagation environment. To this aim, the¬ interference factor is identified as the central element of the symbiotic relationship. Our approach to the investigation of interference and its impacts on the communication reliability departs from previous studies by the degree of realism incorporated in the host system model. In one dimension, realistic traffic models are developed to describe the vehicular traffic behaviour. In a second dimension, a realistic radio propagation model is employed to capture the unique signal propagation aspects of the host system. We address the case of non-safety applications by proposing a generic framework as a capstone architecture for the development of new applications and the efficiency evaluation of existing ones. This framework, while being independent from networking technology, enables accurate characterization of the various information dissemination tasks that a node performs in cooperation with others. As the central element of the framework, we propose a game theoretic model to describe the interaction of meeting nodes aiming to exchange information of mutual or social interests. An adaptive mechanism is designed to enable a mobile node to measure the social significance of various information topics, which is then used by the node to prioritize the forwarding of information objects

    Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

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    The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs

    Mobile Ad-Hoc Networks

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    Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: vehicular ad-hoc networks, security and caching, TCP in ad-hoc networks and emerging applications. It is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

    Towards reliable geographic broadcasting in vehicular networks

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    In Vehicular ad hoc Networks (VANETs), safety-related messages are broadcasted amongst cars, helping to improve drivers' awareness of the road situation. VANETs’ reliability are highly affected by channel contention. This thesis first addresses the issue of channel use efficiency in geographical broadcasts (geocasts). Constant connectivity changes inside a VANET make the existing routing algorithms unsuitable. This thesis presents a geocast algorithm that uses a metric to estimate the ratio of useful to useless packet received. Simulations showed that this algorithm is more channel-efficient than the farthest-first strategy. It also exposes a parameter, allowing it to adapt to channel load. Second, this thesis presents a method of estimating channel load for providing feedback to moderate the offered load. A theoretical model showing the relationship between channel load and the idle time between transmissions is presented and used to estimate channel contention. Unsaturated stations on the network were shown to have small but observable effects on this relationship. In simulations, channel estimators based on this model show higher accuracy and faster convergence time than by observing packet collisions. These estimators are also less affected by unsaturated stations than by observing packet collisions. Third, this thesis couples the channel estimator to the geocast algorithm, producing a closed-loop load-reactive system that allows geocasts to adapt to instantaneous channel conditions. Simulations showed that this system is not only shown to be more efficient in channel use and be able to adapt to channel contention, but is also able to self-correct suboptimal retransmission decisions. Finally, this thesis demonstrates that all tested network simulators exhibit unexpected behaviours when simulating broadcasts. This thesis describes in depth the error in ns-3, leading to a set of workarounds that allows results from most versions of ns-3 to be interpreted correctly
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