On Queueing Models for the Performance Analysis of a Vehicular Ad Hoc Network

Keramidi, Irene; Uzunidis, Dimitris; Moscholios, Ioannis D.; Sarigiannidis, Panagiotis; Logothetis, Michael D.

doi:10.23919/softcom55329.2022.9911228

Cited by 5 publications

(3 citation statements)

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“…The authors in [ 7 ] build a model on a network linking a certain number of queues derived from both the taxi and urban road systems with the consideration of both the passenger and vehicle arrivals. A common multi-server M/M/c queue [ 8 ] that can account for road capacity is proposed for the urban road system, and feedback of network states is sent back to the taxi system. Nevertheless, only the road capacity is considered, not the delay, which actually determines the quality of service of the transportation systemThe above condition similarly exists in the work [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, it studies how to control the vehicle to move or stop from the perspective of a driver rather than from the perspective of the commuting efficiency of traffic flows. Others focus on the resource allocation in information transmission in the Internet of vehicles but do not concentrate on the vehicle planning itself [ 8 , 20 ]. In summary, current works focus more on studying the traffic planning problem via the queuing theory from a non -collaborative mode in some specific scenarios but ignore the performance gain derived from globally collaborative planning.…”

Section: Introductionmentioning

confidence: 99%

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Collaborative Intelligent Traffic Planning in the Internet of Vehicles

Zhu

2024

Sensors

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With the increasing number of urban vehicles, as well as the current situation of non-intelligent traffic control systems, spatiotemporal non-uniform traffic resource occupation, and limited traffic planning and design, existing urban traffic planning methods cannot effectively solve problems such as frequent traffic congestion and uncontrollable commuting time for residents. In order to solve the above problems, this paper first constructs a multi-queue, multi-server queuing model based on the server vacation and a multi-hop cascaded queuing model from the perspective of local intersections and global commuting paths. We analyze the theoretical changes in passage delay costs at local intersections and on global commuting paths as a function of traffic flow and the random duration of traffic signals. On this basis, this article proposes a collaborative intelligent traffic planning algorithm based on artificial intelligence, which utilizes traffic sensors to dynamically perceive traffic congestion status and collaboratively plans the optimal duration of traffic signals and the optimal driving path of vehicles from both local and global perspectives, thereby maximizing the on-time arrival ratio of vehicles while ensuring the required commuting delay. The simulation results show that the proposed method can increase the on-time arrival ratio of vehicles by at least 20% compared to contrast methods while meeting the requirements relating to commuting delays. This verifies that our method can provide support for the improvement in efficiency in future Internet of vehicles.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Collaborative Intelligent Traffic Planning in the Internet of Vehicles

Zhu

2024

Sensors

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“…The authors in [16] formulated a queueing-based model and used it at the network orchestrator to optimally perform a virtual network function (VNF) placement and a resource allocation for the support of the vertical's requirements in 5G networks. The authors in [17] studies how to determine various performance metrics (system's waiting time, the throughput and number of resources required to meet users' needs) of a a vehicular ad hoc network (VANET) with two queueing theory models, namely the M/M/c and the M(N)/M/c models. We can also cite some work on software-defined networking (SDN) modeling.…”

Section: Introductionmentioning

confidence: 99%

Modeling a Linux Packet-Capturing System with a Queueing System with Vacations

2023

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Monitoring the evolution of the state of networks is an important issue to ensure that many applications provide the required quality of service. The first step in network-monitoring systems consists of capturing packets; that is, packets arrive at the system through a network interface card and are placed into system memory. Then, in this first stage, and usually in relation to the operating system, packets are treated and transferred from the capturing buffer to a higher-layer processing, for instance, to be analyzed in the next step of the system. In this work, we focus on the capturing stage. In particular, we focus on a Linux packet-capturing system. We model it as a single server queue. Taking into account that the server can be in charge not only of the capturing process but also of other tasks, we consider that the queue has vacations, i.e., there is some time when the capturing process cannot be carried out. We also assume that the queue has a finite buffer. We consider three different models and present a rigorous analysis of the derived Markov chain of each of the models. We provide standard performance metrics in all cases. We also evaluate the performance of these models in a real packet-capture probe.

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