A vehicle's weight‐based prioritized reciprocity MAC

Abstract

In vehicular ad hoc networks, vehicles compete for channel access through the medium access control protocol to transmit messages. Most traditional medium access methods assign the same probability to all vehicles accessing the channel and ignore the intrinsic attributes of different vehicles. Attributes regarding the position and role of a vehicle are important factors to be considered when a vehicle is competing for the channel. In this paper, we introduce a new notion of a weight factor in a fair medium access game and propose a game model to adjust each node's channel access probability with complete information in the vehicular environment based on the weight factors of vehicles. The weight of a vehicle represents a specific property, such as the distance between vehicles, the vehicle's role, and so on, which can be used to distinguish priorities of different vehicles during channel competition. We also provide instances of relevant applications by using the distance between vehicles and a vehicle's role. Then, we analyze the incomplete information game in which each node cannot acquire the previous channel access probabilities of other nodes. Moreover, we construct a distributed best-response learning algorithm based on the medium access game model and demonstrate that the game can converge to a unique and stable equilibrium under certain conditions. Furthermore, we investigate some performance indicators such as channel access delay and normalized throughput and perform extensive numerical analyses compared with the IEEE 802.11p protocol and an existing game-based medium access control algorithm without consideration of weights. The performance comparison of high-priority nodes and all nodes in a network is also studied. Finally, we analyze the effects of the proportion of high-priority nodes on the performance of the channel. The performance improvement after introducing the weight factor is verified by these numerical results.Trans Emerging Tel Tech. 2019;30:e3654.wileyonlinelibrary.com/journal/ett

Dynamic Task Offloading for Cloud-Assisted Vehicular Edge Computing Networks: A Non-Cooperative Game Theoretic Approach

“…Therefore, in our proposed system, we used a dynamic-pricing strategy to control the task-offloading behavior of the vehicle. Based on the strategy of the dynamic-pricing mechanism used in [ 30 ], the price function can be derived as follows: where represents the pricing factor that determine where the task will be offloaded, and depicts the task arrival rate. If the MEC server has sufficient storage and computing resources, then we use a low pricing factor to ensure efficient use of the MEC resources.…”

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“…Furthermore, some vehicle nodes may deviate from the MAC protocol to obtain an unfair bandwidth share. To solve these problems, GT has been applied by several studies for collision alleviation [75], [96], competition resolution [76], [77], and greedy behavior prevention [78]. It should be noted that they are theoretical models based on the standard MAC protocol of CSMA/CA released by IEEE 802.11p [163] and the radio resource control (RRC) released by 3GPP LTE [164].…”

“…An equilibrium enables the successful transmission of message within a latency limit when the channel is nearly saturated. The inter-distance between vehicles and their roles are further considered in a medium access game in [77] to determine a player's priority to access the channel.…”

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“…Furthermore, some vehicle nodes may deviate from the MAC protocol to obtain an unfair bandwidth share. To solve these problems, GT has been applied by several studies with the purpose of collision alleviation [47], [78], competition solution [48], [49], and greedy behaviors prevention [50].…”

“…The equilibrium enables the successful transmission of the message within the latency limit when the channel is nearly saturated. The inter-distance between vehicles and the roles of vehicles are further considered in the medium access game in [49] to determine a player's priority to access the channel.…”