An Application-Centric Inter-Vehicle Routing Protocol for Video Streaming over Multi-Hop Urban VANETs

Asefi, Mahdi; Mark, Jon W.; Shen, Xuemin

doi:10.1109/icc.2011.5962635

Cited by 19 publications

(11 citation statements)

References 8 publications

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“…To securely and efficiently accomplish route optimization procedures in VANET, a Batch Binding Update Scheme (BBUS) can be used [54]. To facilitate video frame distortion and streaming start-up delay, an application centric routing framework for real time video transmission over urban multi-hop VANET can be employed [55]. Queuing can be made based on mobility model, spatial traffic distribution and probability of connectivity for sparse and dense VANET scenarios.…”

Section: Routingmentioning

confidence: 99%

Cognitive radio network in vehicular ad hoc network (VANET): A survey

et al. 2016

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Cognitive radio network and Vehicular Ad hoc Network (VANET) are recent emerging concepts in wireless networking. Cognitive radio network obtains knowledge of its operational geographical environment to manage sharing of spectrum between primary and secondary users, while VANET shares emergency safety messages among vehicles to ensure safety of users on the road. Cognitive radio network is employed in VANET to ensure the efficient use of spectrum, as well as to support VANET's deployment. Random increase and decrease of spectrum users, unpredictable nature of VANET, high mobility, varying interference, security, packet scheduling and priority assignment are the challenges encountered in a typical cognitive VANET environment. This paper provides survey and critical analysis on different challenges of cognitive radio VANET, with discussion on the open issues, challenges and performance metrics, for different cognitive radio VANET applications.

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Section: Routingmentioning

confidence: 99%

Cognitive radio network in vehicular ad hoc network (VANET): A survey

et al. 2016

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“…We further consider a sparse network, thus we assume that the mobility of the nodes are independent from each other. Although such an assumption has been already used in previous works [15] [16], it is not applicable for dense vehicular networks. The unidirectional highway model considered is illustrated in Fig.…”

Section: System Model and Analytical Approachmentioning

confidence: 99%

Toward neighborhood prediction using Physical-Layer Network Coding

Ndih

Cherkaoui

2012

2012 IEEE International Conference on Communications (ICC)

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In this paper we investigate the improvements in the capability of neighborhood prediction when the Physical-Layer Network Coding (PLNC) is used for relaying messages in Vehiculars Ad Hoc Networks (VANETs). We compute the probability that a link between two nodes is available at a given time in a three-node cooperative network, and we demonstrate that the use of PLNC, compared to the use of Network Coding (NC)based or traditional routing (TR)-based relaying techniques, leads to a better accuracy of the neighborhood prediction. We also demonstrate that the accuracy of the prediction is tightly related to the mobility model used and that this tight relationship can be relaxed by using PLNC-based relaying neighborhood prediction (PRNP). The results demonstrate that PRNP can improve the accuracy of neighborhood prediction due to the high network capacity of PLNC-based networks.

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“…The scenarios of multimedia streaming service over vehicular networks include vehicle‐to‐vehicle (V2V), vehicle to infrastructure (V2I) or hybrid, that is, the integration of V2V and V2I. On the basis of the aforementioned scenarios, video data are downloaded from the backbone infrastructure to the targeted vehicle via multiple hops . Multi‐hop video transmission over vehicular networks may be easy to suffer high packet loss or frequent path disconnection.…”

Section: Introductionmentioning

confidence: 99%

A buffer‐aware fleet‐based cooperative H.264/SVC streaming over vehicular networks

Lee

Huang

Yang

et al. 2013

Int J Communication

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SUMMARYBecause of of the characteristics of high mobility, time varying and dynamic topology, how to provide multimedia streaming service for connected vehicles becomes one emerging and popular technical research. The motivation of this paper is to utilize cooperation among neighboring vehicles for video streaming's quality improvement over vehicular networks. In the proposed cooperative streaming scenario, a connected vehicle requests a video stream from the Internet by using its 3G/3.5G interface, which may not have enough bandwidth to receive good quality of video. Thus, the vehicle is suggested to ask neighboring members belonging to the same fleet to download the requested video data by using their 3G/3.5G interfaces. Then, neighboring members should forward video data to the requested vehicle by using another wireless technique, for example, dedicated short range communication (DSRC). Regarding the differentiation between the two access networks, that is, 3G/3.5G network and DSRC network, a buffer-aware scheduling mechanism based on layered streaming is designed in this paper to adapt to the networking situation of the vehicular networks. Two selection algorithms are proposed to select neighboring vehicles from the fleet. According to our simulation results, the 3G/3.5G-based selection algorithm is suitable to improve video quality for vehicles at low speeds. On the other hand, the DSRC-based selection algorithm can get better performance when vehicles move at high speeds or too many data are transmitted among vehicles.

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An Application-Centric Inter-Vehicle Routing Protocol for Video Streaming over Multi-Hop Urban VANETs

Cited by 19 publications

References 8 publications

Cognitive radio network in vehicular ad hoc network (VANET): A survey

Cognitive radio network in vehicular ad hoc network (VANET): A survey

Toward neighborhood prediction using Physical-Layer Network Coding

A buffer‐aware fleet‐based cooperative H.264/SVC streaming over vehicular networks

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