An Interference-Aware Resource Allocation Scheme for Connectivity Improvement in Vehicular Networks

Meng, Yun; Yuan, Dong; Liu, Xinyi; Zhao, Yi

doi:10.1109/access.2018.2867745

Cited by 14 publications

(15 citation statements)

References 19 publications

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“…However, compared to other existing works, our model is the only scheme uses different environment and significantlymaximize the throughput and minimized the collision. In [ 69 ], the RA Scenario system was studied outside the scope in which the network infrastructure allocates resources to vehicles according to the vehicle’s estimated location. The performance of the resource allocation plan is analyzed for unexpected and planned services.…”

Section: Resultsmentioning

confidence: 99%

Channel Allocation for Connected Vehicles in Internet of Things Services

Al-Absi

Sain

et al. 2021

Sensors

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Based on the existing Internet of Vehicles communication protocol and multi-channel allocation strategy, this paper studies the key issues with vehicle communication. First, the traffic volume is relatively large which depends on the environment (city, highway, and rural). When many vehicles need to communicate, the communication is prone to collision. Secondly, because the traditional multi-channel allocation method divides the time into control time slots and transmission time slots when there are few vehicles, it will cause waste of channels, also when there are more vehicles, the channels will not be enough for more vehicles. However, to maximize the system throughput, the existing model Enhanced Non-Cooperative Cognitive division Multiple Access (ENCCMA) performs amazingly well by connected the Cognitive Radio with Frequency Division Multiple Access (FDMA) and Time Division Multiple Access (TDMA) for a multi-channel vehicular network. However, this model induces Medium Access Control (MAC) overhead and does not consider the performance evaluation in various environmental conditions. Therefore, this paper proposes a Distributed Medium Channel Allocation (DMCA) strategy, by dividing the control time slot into an appointment and a safety period in the shared channel network. SIMITS simulator was used for experiment evaluation in terms of throughput, collision, and successful packet transmission. However, the outcome shows that our method significantly improved the channel utilization and reduced the occurrence of communication overhead.

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Section: Resultsmentioning

confidence: 99%

Channel Allocation for Connected Vehicles in Internet of Things Services

Al-Absi

Sain

et al. 2021

Sensors

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“…Graph based interference aware RA strategies have been proposed in [56], [57], where the weights of the edges are assigned according to the interference terms between the Fig. 6.…”

Section: A Ra For Traditional Cellular Systemsmentioning

confidence: 99%

“…6 that their proposed scheme exhibits higher network sum rate than the traditional orthogonal communication mode. In contrast, the work in [57] aims at improving the connectivity of vehicular communications by introducing a metric called connectivity index, which is obtained from the percentage of vehicles in the network being assigned with resources while satisfying the interference constraints. With the aid of the minimum spanning tree approach [75], Meng et al [57] proposed a RA algorithm to improve the connectivity of the network.…”

Section: A Ra For Traditional Cellular Systemsmentioning

confidence: 99%

“…In contrast, the work in [57] aims at improving the connectivity of vehicular communications by introducing a metric called connectivity index, which is obtained from the percentage of vehicles in the network being assigned with resources while satisfying the interference constraints. With the aid of the minimum spanning tree approach [75], Meng et al [57] proposed a RA algorithm to improve the connectivity of the network. Authors in [57] evaluated the performance of the proposed scheme using simulation (using NS-3) where a two-way four-lane road of 1 km with randomly distributed vehicles was considered.…”

Section: A Ra For Traditional Cellular Systemsmentioning

confidence: 99%

“…With the aid of the minimum spanning tree approach [75], Meng et al [57] proposed a RA algorithm to improve the connectivity of the network. Authors in [57] evaluated the performance of the proposed scheme using simulation (using NS-3) where a two-way four-lane road of 1 km with randomly distributed vehicles was considered. The transmission radius of vehicles was assumed to be 50 m, while the speed of the vehicles varied from 20km/h to 60 km/h.…”

Section: A Ra For Traditional Cellular Systemsmentioning

confidence: 99%

See 2 more Smart Citations

A Survey on Resource Allocation in Vehicular Networks

Noor-A-Rahim

Liu

Lee

et al. 2022

IEEE Trans. Intell. Transport. Syst.

114

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Vehicular networks, an enabling technology for Intelligent Transportation System (ITS), smart cities, and autonomous driving, can deliver numerous on-board data services, e.g., road-safety, easy navigation, traffic efficiency, comfort driving, infotainment, etc. Providing satisfactory Quality of Service (QoS) in vehicular networks, however, is a challenging task due to a number of limiting factors such as erroneous and congested wireless channels (due to high mobility or uncoordinated channel-access), increasingly fragmented and congested spectrum, hardware imperfections, and anticipated growth of vehicular communication devices. Therefore, it will be critical to allocate and utilize the available wireless network resources in an ultra-efficient manner. In this paper, we present a comprehensive survey on resource allocation schemes for the two dominant vehicular network technologies, e.g. Dedicated Short Range Communications (DSRC) and cellular based vehicular networks. We discuss the challenges and opportunities for resource allocations in modern vehicular networks and outline a number of promising future research directions.

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Connectivity analysis of directed highway vehicular ad hoc networks using graph theory

Elaraby

Abuelenin

2021

Int J Communication

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Summary Graph theory is a promising approach in handling the problem of estimating the connectivity probability of vehicular ad hoc networks (VANETs). With a communication network represented as graph, graph connectivity indicators become valid for connectivity analysis of communication networks as well. In this article, we discuss two different graph‐based methods for VANETs connectivity analysis showing that they capture the same behavior as estimated using probabilistic models. The study is, then, extended to include the case of directed VANETs, resulting from the utilization of different communication ranges by different vehicles. Overall, the graph‐based methods prove a robust performance, as they can be simply diversified into scenarios that are too complex to acquire a rigid probabilistic model for them.

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An Interference-Aware Resource Allocation Scheme for Connectivity Improvement in Vehicular Networks

Cited by 14 publications

References 19 publications

Channel Allocation for Connected Vehicles in Internet of Things Services

Channel Allocation for Connected Vehicles in Internet of Things Services

A Survey on Resource Allocation in Vehicular Networks

Connectivity analysis of directed highway vehicular ad hoc networks using graph theory

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