Delay-Constrained Data Aggregation in VANETs

Zhu, Yanmin; Zhao, Qingwen; Zhang, Qian

doi:10.1109/tvt.2014.2335232

Cited by 19 publications

(9 citation statements)

References 32 publications

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“…Numerous data collection solutions have been proposed in vehicular networks, most of which consider metrics such as end-to-end delay, collection ratio, and communication cost. Using dynamic programming, the authors in [14] constructed a data aggregation tree with a waiting time budget at each node, producing much lower transmission overhead while achieving the same QoS performance as other schemes. The delaybounded routing protocols presented in [15] provided a routing scheme that satisfies user-defined delay requirements while maintaining a low level of channel utilization.…”

Section: B Data Collection In Vehicular Networkmentioning

confidence: 99%

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Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

Landfeldt

Song

et al. 2020

IEEE Trans. Veh. Technol.

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Vehicles equipped with sensors can participate in mobile crowdsourcing applications. Vehicular Ad Hoc Networks (VANETs) based on Dedicated Short Range Communication (DSRC) are used to carry sensing data. However, multi-hop transmissions for gathering data to Road Side Units (RSUs) in VANETs suffer from low data rate and long end-to-end delay, which can hardly meet the QoS requirements of delay-sensitive services. This triggers the consideration of constituting a DSRC and Cellular-Vehicle-to-Everything (C-V2X) hybrid vehicular network. Nevertheless, using cellular links to carry traffic can cause high cellular bandwidth costs. In this paper, we propose a Traffic Differentiated Clustering Routing (TDCR) mechanism in a Software Defined Network (SDN)-enabled hybrid vehicular network. The proposed mechanism includes a centralized one-hop clustering approach and a data delivery optimization method. Particularly, the optimization is to make a tradeoff between cellular bandwidth cost and end-to-end delay, for Cluster Heads (CHs) delivering their aggregated data either by multi-hop Vehicle-to-Vehicle (V2V) transmissions or by cellular networks. Since the problem is proven to be NP-hard, a two-stage heuristic algorithm is designed. We carry out simulations to evaluate the performance of our data collection scheme and the results show that it performs better than traditional mechanisms.

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Section: B Data Collection In Vehicular Networkmentioning

confidence: 99%

“…The amount of aggregated traffic carried by a link should not exceed its capacity. Capacity constraints C a (14) and C b (15) are for V2V links and cellular links, respectively. Each traffic flow has a delay constraint D k which is reflected in constraint (16).…”

Section: B Optimization Problemmentioning

confidence: 99%

Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

Landfeldt

Song

et al. 2020

IEEE Trans. Veh. Technol.

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“…Another scheme from Ref. 18 focuses on the delay-constrained data aggregation problem in VANETs for maximizing the amount of collected information. The chain heuristic, which finds a set of paths for each destination within the delay limit, is proposed to meet delay bound for multicast networks (see Refs.…”

Section: Related Workmentioning

confidence: 99%

Burst Transmission and Frame Aggregation for VANET Communications

Lai¹,

Lin²,

Kuo³

2017

IJNDC

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In vehicular ad hoc networks (VANETs), due to highly mobile and frequently changing topology, available resources and transmission opportunities are restricted. To address this, we propose a burst transmission and frame aggregation (FAB) scheme to enhance transmission opportunity (TXOP) efficiency of IEEE 802.11p. Aggregation and TXOP techniques are useful for improving transmission performance. FAB aggregates frames in the relay node and utilizes the TXOP to transmit these frames to the next hop with a burst transmission. Simulation results show that the proposed FAB scheme can significantly improve the performance of inter-vehicle communications.

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“…A sensing process consists of a series of sensing tasks for collecting the same kind of sensing data (i.e. air quality, noise level, or traffic status, GPS trajectories, [26][27][28] radio signal strength.) [29][30][31][32][33] A sensing process is divided by time slots, shown in Figure 2.…”

Section: System Modelmentioning

confidence: 99%

Evolutionary stable participation game of smartphones in crowdsourced sensing

Weng

Chen

Sun

2016

International Journal of Distributed Sensor Networks

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It is crucial to stimulate active participation of smartphone workers in crowdsourced sensing systems. This is due to the fact that it takes a smartphone worker considerable cost in terms of dedicated smartphone resources, human intervention, and possible privacy breach. Many incentive mechanisms have been proposed. However, existing incentive mechanisms suffer a serious common problem: they all assume full rationality of smartphone worker. Such fully rational smartphone workers are often too idealized! A smartphone worker may not be able to get the complete information and hence fails to compute the optimal strategy. In the real world, however, smartphone workers are usually bounded rational. Being bounded rational, a smartphone worker would not change the current strategy until its utility becomes too low. In this article, we propose an evolutionary stable participation game framework for crowdsourced sensing systems with smartphone workers of bounded rationality. Based on the evolutionary dynamics, we design and implement an evolutionary stable participation mechanism. It is proved that the system converges to an evolutionary equilibrium, which is globally asymptotically stable and robust to any degree of perturbations of the workers. Extensive simulation results show that the evolutionary participation mechanism leads the system to an evolutionary equilibrium quickly.

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Delay-Constrained Data Aggregation in VANETs

Cited by 19 publications

References 32 publications

Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

Burst Transmission and Frame Aggregation for VANET Communications

Evolutionary stable participation game of smartphones in crowdsourced sensing

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