Performance Modeling of Message Dissemination In Vehicular Ad Hoc Networks with Priority

Khabazian, Mehdi; Aı̈ssa, Sonia; Mehmet-Ali, Mustafa

doi:10.1109/jsac.2011.110107

Cited by 96 publications

(57 citation statements)

References 13 publications

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“…As a further development, Khabazian et al [15] presented an analytical model for characterizing the performance measures of information sharing in VSNs under the assumption of two priority classes of traffic. Specifically, the distribution of the number of concurrent transmissions was discussed, as well as numerical results were provided along with simulation results in order to confirm the accuracy of the proposed analysis.…”

Section: A City Information Sharing In Vsnsmentioning

confidence: 99%

Vehicular Sensing Networks in a Smart City: Principles, Technologies and Applications

Wang

Jiang

Zhang

et al. 2018

IEEE Wireless Commun.

165

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Given the escalating population across the globe, it has become paramount to construct smart cities, aiming for improving the management of urban flows relying on efficient information and communication technologies (ICT). Vehicular sensing networks (VSNs) play a critical role in maintaining the efficient operation of smart cities. Naturally, there are numerous challenges to be solved before the wide-spread introduction of VSNs, including the conception of an accurate topological analysis method as well as of a beneficial cooperation mechanism during the process of city-wide information sharing. Hence, in this paper, we construct a VSNs-aided smart city model and appraise a range of intelligent applications in terms of both public services as well as of urban flow management. Then, the information source selection algorithm of a complex network and a reinforcement learning based city information sharing mechanism are considered, complemented by a range of open challenges. Index TermsSmart city, vehicular sensing network (VSN), topological analysis, information sharing mechanism.

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Section: A City Information Sharing In Vsnsmentioning

confidence: 99%

Vehicular Sensing Networks in a Smart City: Principles, Technologies and Applications

Wang

Jiang

Zhang

et al. 2018

IEEE Wireless Commun.

165

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“…Therefore, we define the contact rate of helper h ∈ H by γ h . 1 In the system, we adopt the erasure coding technique [10], [26] to encode the mobile data into a large set of small coded packets, and any sufficient subset of the coded packets can be used to reconstruct the mobile data. Specifically, the coding process takes the original data c of size l c and a given coding rate as the input and then outputs uniformly sized packets of size s p .…”

Section: B Data Offloading and Networking Modelingmentioning

confidence: 99%

“…ITH THE ever-increasing number of vehicles on roads, traffic jams and accidents have become a serious and widespread problem [1]. Partly to alleviate this serious problem, recently, there has been a strong interest in developing vehicular networks that enable wireless communications for vehicles to obtain information and content from the resource located Internet.…”

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confidence: 99%

Coding or Not: Optimal Mobile Data Offloading in Opportunistic Vehicular Networks

Jin

Hanzo

et al. 2014

IEEE Trans. Intell. Transport. Syst.

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Abstract-To cope with explosive vehicular traffic and everincreasing application demands in the vehicular cellular network, opportunistic vehicular networks are used to disseminate mobile data by high-capacity device-to-device communication, which offloads significant traffic from the cellular network. In the current opportunistic vehicular data transmission, coding-based schemes are proposed to address the challenge of opportunistic contact. However, whether coding techniques can be beneficial in the context of vehicular mobile data offloading is still an open question. In this paper, we establish a mathematical framework to study the problem of coding-based mobile data offloading under realistic network assumptions, where 1) mobile data items are heterogeneous in terms of size; 2) mobile users have different interests to different data; and 3) the storage of offloading participants is limited. We formulate the problem as a users' interest satisfaction maximization problem with multiple linear constraints of limited storage. Then, we propose an efficient scheme to solve the problem, by providing a solution that decides when the coding should be used and how to allocate the network resources in terms of contact rate and offloading helpers' storage. Finally, we show the effectiveness of our algorithm through extensive simulations using two real vehicular traces.Index Terms-Erasure coding, mobile data offloading, opportunistic vehicular networks.

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“…For priority processing, the proposal of MAC protocol with priority adjustment [11] and the simulation of MIN with priority routing [12] are studied. And, CAN with priority [13] and ad hoc network with priority [14] are reported. I also reported bus network with two priority levels [15].…”

Section: Introductionmentioning

confidence: 99%

On a Characteristic of Data Transmission with Three or More Priority Levels in Bus Network

Ooki¹

2017

IJCCE

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This paper presents a characteristic of data transmission in bus network in which each datum has a priority and the number of priority levels are three or more. In this bus network, each station is connected to a bus through a switching-hub which establishes a link from a sending station to a receiving station. When the receiving station is sending data or receiving data, the link cannot be established and the sending station has to wait a little waiting time (stand-by time). Then, by defining the link probability as a constant, the bus network is analyzed.Taking note of one of the sending stations with r(r≥3) sending buffers for data with priority, in steady state, a balance equation of the probabilities of the number of waiting data at the ready time of sending is expressed. From the equation, for each priority, probabilities of the number of waiting data, mean of the number of waiting data in the sending buffer and mean waiting time which is the time from the arrival time of a datum at the sending buffer to the beginning time of sending the datum are derived. The calculated values of mean waiting time are illustrated and mean waiting times with priority processing are compared with mean waiting time without priority processing. As a result, the influence of the link probability on data transmission with priority processing is clarified.Key words: Bus network, priority processing, probability of the number of waiting data, mean of the number of waiting data, mean waiting time.

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Performance Modeling of Message Dissemination In Vehicular Ad Hoc Networks with Priority

Cited by 96 publications

References 13 publications

Vehicular Sensing Networks in a Smart City: Principles, Technologies and Applications

Vehicular Sensing Networks in a Smart City: Principles, Technologies and Applications

Coding or Not: Optimal Mobile Data Offloading in Opportunistic Vehicular Networks

On a Characteristic of Data Transmission with Three or More Priority Levels in Bus Network

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