Timed bargaining-based opportunistic routing model for dynamic vehicular ad hoc network

Kim, Sung-Wook

doi:10.1186/s13638-016-0516-5

Cited by 11 publications

(12 citation statements)

References 14 publications

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“…Consider the definition of the Nash equilibrium again, and we can have another inequality (12) as below: //Upon broadcasting a packet:…”

Section: □ Theorem 2 E Combination Of Each Node's Bargain Proposal Amentioning

confidence: 99%

“…Since the messages are carried in each active spacer bar's broadcast, no extra retransmission is needed, yielding high MDRs with small communication overhead and short time delay. Besides, a decentralized cooperative bargain game is formulated to offload the task of message recovery regarding each active spacer bar's local resource [12]. e active spacer bars keep on negotiating with each other on which messages to carry until a consensus is achieved, so that they can make consistent movement in the reversible lanes.…”

Section: Introductionmentioning

confidence: 99%

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Cooperative Bargain for the Autonomous Separation of Traffic Flows in Smart Reversible Lanes

et al. 2019

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Spacer bars in the smart reversible lanes make periodically broadcast of messages to share their local observed traffic information with each other. This aims to help other spacer bars acquire the global traffic information and make consistent movement when separating the flows. However, radio interference and vehicles in the traffic may degrade the qualities of wireless communication links and cause frequent message losses in the broadcast. Existing solutions tend to use data forwarding to enhance the message dissemination, which may cause imbalanced load in the spacer bars. For instance, the nodes close to the sink have to forward more messages, whereas the ones far away from the sink have fewer messages for forwarding. The unbalanced distribution of network load has a high risk of blocking the wireless communication links and yield inconsistent movement in the reversible lanes. In this paper, we propose a Cooperative Bargain (CoB) scheme where each spacer bar carries some received messages to help other spacer bars recover their lost messages. Since the spacer bars can only acquire the local information, we formulate a cooperative bargain game to negotiate how to allocate the task of message recovery with a balanced network load until a consensus is achieved. CoB is evaluated with the real-world Wi-Fi communication traces in Isti/rural. Simulation results show that CoB can recover an average of 98.6% messages within 100 milliseconds in a 50-node network. CoB does not require the global network information but it can still achieve a comparable performance to other broadcast schemes.

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“…Consider the definition of the Nash equilibrium again, and we can have another inequality (12) as below: //Upon broadcasting a packet:…”

Section: □ Theorem 2 E Combination Of Each Node's Bargain Proposal Amentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cooperative Bargain for the Autonomous Separation of Traffic Flows in Smart Reversible Lanes

et al. 2019

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“…e main goal of VRS is to transmit data from a source vehicle to a destination vehicle via wireless multihop transmission techniques. In the wireless multihop transmission technique, the intermediate vehicles in a routing path should relay data as soon as possible from the source to destination [6,13,25]. In this section, we develop a noncooperative game model (G VRS ) for vehicular routing services.…”

Section: E Vrs Algorithm Based On a Non-cooperative Gamementioning

confidence: 99%

“…Step 8. At every time step (H), the RSU adjusts the learning values (Z(•)) and the probability distribution (P R ) according to equations (12) and (13).…”

Section: Main Steps Of Proposed Triple-plane Bargainingmentioning

confidence: 99%

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New Bargaining Game Model for Collaborative Vehicular Network Services

Kim

2019

Mobile Information Systems

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The wireless industry’s evolution from fourth generation (4G) to fifth generation (5G) will lead to extensive progress in new vehicular network environments, such as crowdsensing, cloud computing, and routing. Vehicular crowdsensing exploits the mobility of vehicles to provide location-based services, whereas vehicular cloud computing is a new hybrid technology that instantly uses vehicular network resources, such as computing, storage, and Internet for decision-making. In this study, novel crowdsensing, cloud computing, and routing algorithms are developed for a next-generation vehicular network, and they are combined into a hybrid scheme. To provide an effective solution toward an appropriate interactive vehicular network process, we focus on the paradigm of learning algorithms and game theory. Based on individual cooperation, our proposed scheme is designed as a triple-plane game model to adapt to the dynamics of a vehicular network system. The primary advantage of our game-based approach is to provide self-adaptability and responsiveness to current network environments. The performance of our hybrid scheme is evaluated and analyzed using simulation experiments in terms of the cloud service success ratio, normalized dissemination throughput, and crowdsensing success probability.

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Priority-based capacity and power allocation in co-located WBANs using Stackelberg and bargaining games

Wang

Sun

2018

J Supercomput

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Timed bargaining-based opportunistic routing model for dynamic vehicular ad hoc network

Cited by 11 publications

References 14 publications

Cooperative Bargain for the Autonomous Separation of Traffic Flows in Smart Reversible Lanes

Cooperative Bargain for the Autonomous Separation of Traffic Flows in Smart Reversible Lanes

New Bargaining Game Model for Collaborative Vehicular Network Services

Priority-based capacity and power allocation in co-located WBANs using Stackelberg and bargaining games

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