Intelligent Digital Twin-Based Software-Defined Vehicular Networks

Zhao, Liang; Han, Guangjie; Li, Zhuhui; Shu, Lei

doi:10.1109/mnet.011.1900587

Cited by 144 publications

(45 citation statements)

References 12 publications

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“…In this section, we present details of the simulation, including parameters and evaluations. To evaluate our routing algorithm, we develop an open-source simulator in Python to meet the experimental demand of SD-VNs (https://github.com/a824899245/SDVN-platform) [34]. Our simulation is based on a real map of Tiexi District, Shenyang City, China.…”

Section: Simulationmentioning

confidence: 99%

A Novel Prediction-Based Temporal Graph Routing Algorithm for Software-Defined Vehicular Networks

Zhao

Al‐Dubai

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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Temporal information is critical for routing computation in the vehicular network. It plays a vital role in the vehicular network. Till now, most existing routing schemes in vehicular networks consider the networks as a sequence of static graphs. We need to find an appropriate method to process temporal information into routing computation. Thus, in this paper, we propose a routing algorithm based on the Hidden Markov Model (HMM) and temporal graph, namely, Prediction-Based Temporal Graph Routing Algorithm (PT-GROUT). This new algorithm considers the vehicular network as a temporal graph, in which each data transmission as an edge has its specific temporal information. To better capture the temporal information, we select Software-Defined Vehicular Network (SDVN) as our network architecture, which is a preferred architecture for processing the temporal graph regarding the vehicular network since all vehicle statuses can be easily managed. To compute the future routing path accurately and efficiently, the future temporal graph is predicted by applying HMM, in which we model the current vehicular network with dynamic programming and greedy strategies. With the temporal information and reasonable setting of HMM, PT-GROUT can better evaluate the vehicular network and discover the evolution of the internal structure of the network. The optimal routing path can be achieved more efficiently. The simulation results demonstrate that PT-GROUT can substantially improve the computation efficiency and reduce packet loss and delivery delay compared with its counterparts.

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Section: Simulationmentioning

confidence: 99%

A Novel Prediction-Based Temporal Graph Routing Algorithm for Software-Defined Vehicular Networks

Zhao

Al‐Dubai

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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“…5GB networks provide unprecedented capacity of wireless communication service to serve GUE [3][4] [5], e.g., smart sensors, autonomous cars, smart traffic lights and so on, including ultra-reliable low latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machinetype communications (mMTC). The key technologies in 5GB include massive Multiple-Input-Multiple-Output (mMIMO) [6], small cell, beamforming [7], millimetre-wave communication [8], software defined networking [9] [10], and network function virtualisation [11]. Combining the capacity of UAV systems, 5GB-enabled UAV research has attracted significant efforts with fruitful research outcomes.…”

Section: A Motivationmentioning

confidence: 99%

Unlocking the Potential of 5G and Beyond Networks to Support Massive Access of Ground and Air Devices

Miao

Luo

Min

et al. 2021

IEEE Trans. Netw. Sci. Eng.

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Flying devices, e.g., Unmanned Aerial Vehicles (UAV) and High Altitude Platforms (HAP) are showing great potentials to revolutionise human society with unprecedented efficiency and convenience. 5G and beyond (5GB) networks have been considered as an important infrastructure for supporting flying devices to accomplish mission-critical applications. However, most of the existing research on 5GB networks mainly focuses on technology evolution to support ground devices, paying insufficient attention to the emerging large-scale deployment of flying devices. To fill the gap, this study aims to identify the differences when 5GB networks are used to provide massive access services for the ground devices and their counterpart flying in the air and analyse in which aspects that 5GB should be enhanced to serve flying devices. In detail, a holistic 5GB architecture is presented to support both ground and flying devices. Then, the unique features of flying devices are analysed with a focus on the challenges they bring to 5GB systems. Facing these challenges, we thoroughly investigate the advantages and disadvantages of 5GB key technologies. Furthermore, a case study is presented to demonstrate that flying devices not only create new issues for 5GB design, but also bring new opportunities for 5GB to enhance their service capabilities.

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“…For example, VNs are susceptible to the dynamic road conditions including highly-mobile vehicles and changing of vehicle density, in which both may result in high packet loss and latency. Consequently, as an emerging network paradigm, Software-Defined Vehicular Network (SDVN) has been starting to attract research attention [4], [5], [6], [7], [8], [9] as one of the most important technologies to manage VNs. Similar to the general softwarized network, SDVN separates the data plane and control plane in which the data plane is mainly composed of vehicles, infrastructure; the control plane is a logic controller that provides services for the unit of the data plane with its global view of the network.…”

Section: Introductionmentioning

confidence: 99%

A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading

Zhao

Yang

Tan

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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154

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Vehicular computation offloading is a well-received strategy to execute delay-sensitive and/or compute-intensive tasks of legacy vehicles. The response time of vehicular computation offloading can be shortened by using mobile edge computing that offers strong computing power, driving these computation tasks closer to end users. However, the quality of communication is hard to guarantee due to the obstruction of dense buildings or lack of infrastructure in some zones. Unmanned Aerial Vehicles (UAVs), therefore, have become one of the means to establish communication links for the two ends owing to its characteristics of ignoring terrain and flexible deployment. To make a sensible decision of computation offloading, nevertheless vehicles need to gather offloading-related global information, in which Software-Defined Networking (SDN) has shown its advances in data collection and centralized management. In this paper, thus, we propose an SDN-enabled UAV-assisted vehicular computation offloading optimization framework to minimize the system cost of vehicle computing tasks. In our framework, the UAV and the Mobile Edge Computing (MEC) server can work on behalf of the vehicle users to execute the delay-sensitive and compute-intensive tasks. The UAV, in a meanwhile, can also be deployed as a relay node to assist in forwarding computation tasks to the MEC server. We formulate the offloading decision-making problem as a multiplayers computation offloading sequential game, and design the UAV-assisted Vehicular Computation Cost Optimization (UVCO) algorithm to solve this problem. Simulation results demonstrate that our proposed algorithm can make the offloading decision to minimize the Average System Cost (ASC).

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Intelligent Digital Twin-Based Software-Defined Vehicular Networks

Cited by 144 publications

References 12 publications

A Novel Prediction-Based Temporal Graph Routing Algorithm for Software-Defined Vehicular Networks

A Novel Prediction-Based Temporal Graph Routing Algorithm for Software-Defined Vehicular Networks

Unlocking the Potential of 5G and Beyond Networks to Support Massive Access of Ground and Air Devices

A Novel Cost Optimization Strategy for SDN-Enabled UAV-Assisted Vehicular Computation Offloading

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