Content Downloading with the Assistance of Roadside Cars for Vehicular Ad Hoc Networks

Gong, Haigang; Yu, Lei

doi:10.1155/2017/4863167

Cited by 11 publications

(4 citation statements)

References 22 publications

(26 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Section II-A first discusses the existing studies on task mapping, and the works on trust evaluation in the vehicular VOLUME 4, 2016 The capability of the computational and storage resources of vehicles has increasingly gained attention in the recent years [22]- [26], where several studies have uncovered the potential of idle vehicle resources for the purpose of content distribution [9], [27]- [33]. Realizing the promising future of smart vehicles, various vehicle clustering algorithms have been proposed to harness its potential in the areas of vehicular routing or vehicle resources.…”

Section: Background Studymentioning

confidence: 99%

“…Different vehicles have different parking durations with different spatiotemporal conditions, hence their availability for being part of the fog infrastructure also varies. One of the alternatives to solve this problem is using the clustering concept, as clustering the v-fogs can increase service availability through multiple replications and caching [7]- [9]. Other advantages of clustering include having a cluster head to ease management, apart from minimizing collisions in the communication channel to reduce the communication overhead [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

Rahman

Newaz

et al. 2020

IEEE Access

View full text Add to dashboard Cite

One of the key enablers in serving the applications requiring stringent latency in 5G networks is fog computing as it is situated closer to the end users. With the technological advancement of vehicles' on-board units, their computing capabilities are becoming robust, and considering the underutilization of the off-street vehicles, we envision that the off-street vehicles can be an enormously useful computational source for the fog computing. Additionally, clustering the vehicles would be advantageous in order to improve the service availability. As the vehicles become highly connected, trust is needed especially in distributed environments. However, vehicles are made from different manufacturers, and have different platforms, security mechanisms, and varying parking duration. These lead to the unpredictable behavior of the vehicles where quantifying trust value of vehicles would be difficult. A trust-based solution is necessary for task mapping as a task has a set of properties including expected time to complete, and trust requirements that need to be met. However, the existing metrics used for trust evaluation in the vehicular fog computing such as velocity and direction are not applicable in the off-street vehicle fog environments. In this paper, we propose a framework for quantifying the trust value of off-street vehicle fog computing facilities in 5G networks and forming logical clusters of vehicles based on the trust values. This allows tasks to be shared with multiple vehicles in the same cluster that meets the tasks' trust requirements. Further, we propose a novel task mapping algorithm to increase the vehicle resource utilization and meet the desired trust requirements while maintaining imposed latency requirements of 5G applications. Results obtained using iFogSim simulator demonstrate that the proposed solution increases vehicle resource utilization and reduces task drop noticeably. This paper presents open research issues pertaining to the study to lead the way for future research directions.

show abstract

Section: Background Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

Rahman

Newaz

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The authors of Reference [37] suggest a content downloading method with the help of Roadside cars for Vehicular Ad hoc network. In this research, an efficient content downloading approach is suggested with the assistance of stationary vehicles forming a number of clusters; the vehicles in clusters assist to download the content requested, and pass them to the vehicles in need of it, most especially mobile vehicles.…”

Section: Related Workmentioning

confidence: 99%

Optimal Exploitation of On-Street Parked Vehicles as Roadside Gateways for Social IoV—A Case of Kigali City

Twahirwa

Kasakula

Rwigema

et al. 2020

Journal of Open Innovation: Technology, Market, and Complexity

View full text Add to dashboard Cite

Vehicular Ad Hoc Network (VANET) is a subclass of Mobile Ad Hoc Network that mainly consists of moving and/or stationary vehicles, connected through wireless protocols such as IEEE 802.11p and wireless access in vehicular environments (WAVE). With the evolution of the Internet of Things (IoT), ordinary VANET has turned to the Internet of Vehicles (IoV), with additional social aspects, a novel extension themed SIoV has become common in urban areas. However vehicular wireless communication paradigms exhibit short radio communication. This problem has always been approached by supplementing moving vehicles with stationary Road Side Infrastructures, commonly known as roadside units (RSUs). The penetration of such RSUs on the global market is very low; furthermore, their procurement, deployment, and maintenance costs are prohibitively very high. All mentioned challenges have discouraged the widespread deployment of roadside infrastructure especially within large urban scenarios. With this research, we leverage on-street parked vehicles to allow them to exist as temporal gateways in the case study area. A novel modeling technique is introduced to enable a specific Percentage of parked vehicles to take up the role of roadside gateways for a certain percentage of their parking time. A mobile application is implemented that manages parking duration of the vehicle, based on the arrival, and departure time frames. Two more existing strategies were discussed (road-intersection RSUs deployment approach and Inter-vehicle scheme) to validate our proposed method through comparative studies. To evaluate the network performance evaluation, we compare two performance metrics, that is, Packets success delivery rate, and overall packets throughput under numerous vehicle densities. Using parked vehicles as temporal roadside gateways has demonstrated better results in comparison to intersection based RSUs deployment approach, and free vehicle to vehicle communication approach.

show abstract

“…VANET has two communication scenarios, that is, Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V), [5]. The cooperative content distribution (CCD) is one of promising VANET applications [6,7]. Operations of CCD are explained in the following.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Credit-Based Incentive Protocol for Symbol-Level Network-Coded Cooperative Content Distribution among Vehicular Nodes

Chang

Yen

2018

Applied Sciences

View full text Add to dashboard Cite

In traditional symbol-level network coding (SLNC)-based cooperative content distribution approaches, they ignore nodes in the vehicular ad hoc network (VANET) having various network-coded content pieces and distinct levels of interests and selfishness for different kinds of content data, which further prevents these vehicular nodes from forwarding their content information to other nodes. With these approaches, these nodes suffer from the low ratio and the long latency to receive all content information. In this paper, based on distinct levels of node interests and selfishness on different content information, we first categorize vehicular nodes into four classes, that is, the destination, intermediate, irrelevant and overhearing ones and then designate their associated credit-based incentive approaches. Second, we modify the flow of traditional SLNC-based cooperative content distribution operations and propose the content bitmap to realize the difference of network-coded content pieces among vehicular nodes. Further, we rigidly combine the proposed credit-based incentive approach with the modified SLNC-based cooperative content distribution operations in SocialCode to encourage all classes of vehicular nodes to rise their incentives for sharing content data in the cooperative content distribution process. Finally, we perform NS-2 simulations on a street map of downtown Taipei, Taiwan to exhibit the high efficiency of SocialCode over related credit-based incentive approaches by analyzing the following performance metrics, that is, average decoding percentage, file downloading delay and credits, with respect to different file sizes and total numbers of vehicular nodes. As the best knowledge we have, SocialCode is one of the first few researches that works on the integration between the credit-based incentive protocol and the SLNC-based cooperative content distribution.

show abstract

Content Downloading with the Assistance of Roadside Cars for Vehicular Ad Hoc Networks

Cited by 11 publications

References 22 publications

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

Optimal Exploitation of On-Street Parked Vehicles as Roadside Gateways for Social IoV—A Case of Kigali City

An Integrated Credit-Based Incentive Protocol for Symbol-Level Network-Coded Cooperative Content Distribution among Vehicular Nodes

Contact Info

Product

Resources

About