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Exploiting Moving Intelligence: Delay-Optimized Computation Offloading in Vehicular Fog Networks [article]

Sheng Zhou, Yuxuan Sun, Zhiyuan Jiang, Zhisheng Niu
2019 arXiv   pre-print
Vehicular fog networks (VeFN) have thus emerged to enable computing resource sharing via computation task offloading, providing wide range of fog applications.  ...  In this article, we first review the state-of-the-art of task offloading in VeFN, and argue that mobility is not only an obstacle for timely computing in VeFN, but can also benefit the delay performance  ...  Vehicles can contribute their computing resources, acting like fog nodes in the context of fog computing [1] , and thus the whole network can be regarded as vehicular fog network (VeFN).  ... 
arXiv:1902.09401v1 fatcat:uuauri2rujgcvjrb3rn6ht4kwq

Resource allocation optimization using artificial intelligence methods in various computing paradigms: A Review [article]

Javad Hassannataj Joloudari, Roohallah Alizadehsani, Issa Nodehi, Sanaz Mojrian, Fatemeh Fazl, Sahar Khanjani Shirkharkolaie, H M Dipu Kabir, Ru-San Tan, U Rajendra Acharya
2022 arXiv   pre-print
in computational paradigms.  ...  With the advent of smart devices, the demand for various computational paradigms such as the Internet of Things, fog, and cloud computing has increased.  ...  Due to the intractability of the formulated optimization problem, DQN was used in [81] to reduce overall delay in the fog computing environment for vehicular applications in the information-centric network  ... 
arXiv:2203.12315v1 fatcat:43mouwxwene6xllnw3gsmdh6hy

An infrastructure-assisted job scheduling and task coordination in volunteer computing-based VANET

Abdul Waheed, Munam Ali Shah, Abid Khan, Gwanggil Jeon
2021 Complex & Intelligent Systems  
AbstractVehicular networks as the key enablers in Intelligent Transportation Systems (ITS) and the Internet of Things (IoT) are key components of smart sustainable cities.  ...  Most of these applications are delay sensitive and demand high computational capabilities that are provided by emerging technologies.  ...  Fog computing and vehicular network combinedly can use the surplus resources of vehicles in the form of vehicular fog nodes.  ... 
doi:10.1007/s40747-021-00437-3 fatcat:a4wynzgsgngthlia3govbkcsw4

Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence

Peng Wei, Kun Guo, Ye Li, Jue Wang, Wei Feng, Shi Jin, Ning Ge, Ying-Chang Liang
2022 IEEE Access  
Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive and delay-sensitive tasks in fifth generation (5G) networks and beyond.  ...  Thanks to the evolved reinforcement learning (RL), upon iteratively interacting with the dynamic and random environment, its trained agent can intelligently obtain the optimal policy in MEC.  ...  To reduce the task delay, a multiplatform intelligent algorithm of offloading and resource allocation is proposed in dynamic vehicular networks.  ... 
doi:10.1109/access.2022.3183647 fatcat:pd5z6q4innd5jl25g4r7b4nq3i

Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence [article]

Peng Wei, Kun Guo, Ye Li, Jue Wang, Wei Feng, Shi Jin, Ning Ge, Ying-Chang Liang
2022 arXiv   pre-print
Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive and delay-sensitive tasks in fifth generation (5G) networks and beyond.  ...  Thanks to the evolved reinforcement learning (RL), upon iteratively interacting with the dynamic and random environment, its trained agent can intelligently obtain the optimal policy in MEC.  ...  To reduce the task delay, a multiplatform intelligent algorithm of offloading and resource allocation is proposed in dynamic vehicular networks.  ... 
arXiv:2201.11410v4 fatcat:24igkq4kbrb2pjzwf3mf3n7qtq

Twin-Timescale Artificial Intelligence Aided Mobility-Aware Edge Caching and Computing in Vehicular Networks

Le Thanh Tan, Rose Qingyang Hu, Lajos Hanzo
2019 IEEE Transactions on Vehicular Technology  
In this paper, we propose a joint communication, caching and computing strategy for achieving cost efficiency in vehicular networks.  ...  function using the classic particle swarm optimization scheme at the associated large timescale level, while we employ deep reinforcement learning at the small timescale level of our sophisticated twin-timescale  ...  Index Terms-Vehicular networks; vehicular mobility; edge caching and computing; artificial intelligence; deep reinforcement learning; particle swarm optimization I.  ... 
doi:10.1109/tvt.2019.2893898 fatcat:e4mq2iw6fjcfncxhyv5ip6j6pi

Survey on cooperatively V2X downloading for intelligent transport systems

Tong Wang, Xiaodan Wang, Ziping Cui, Yue Cao, Chakkaphong Suthaputchakun
2019 IET Intelligent Transport Systems  
One of the key challenges in building cooperative downloading today is the provisioning of multimedia services requiring actuator algorithm, intermittent connectivity and real-time computation.  ...  Traditional cellular networks cannot meet people's needs for video, large files and entertainment.  ...  In [35] , Zheng proposed a hierarchical cloud-based vehicular edge computing offloading framework, where a backup computing server in the neighbourhood is introduced to make up for the deficit computing  ... 
doi:10.1049/iet-its.2018.5104 fatcat:ice4gxbckrb6rkcgplc6i5xtb4

Guest Editorial Software Defined Internet of Vehicles

Zhihan Lv, Jaime Lloret, Houbing Song
2021 IEEE transactions on intelligent transportation systems (Print)  
These large amounts of vehicle information can be analyzed and processed through computer technology to calculate the optimal route for different vehicles, and report road conditions in time and schedule  ...  The system realizes the integrated network of intelligent traffic management, intelligent dynamic information service, and intelligent vehicle control by "filtering and cleaning" massive data and processing  ...  In "A Novel Cost Optimization Strategy for SDN-enabled UAV-assisted Vehicular Computation Offloading".  ... 
doi:10.1109/tits.2021.3080875 fatcat:tvd6ubmtmfe73mta3iorxzncju

Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions

Salahadin Seid Musa, Marco Zennaro, Mulugeta Libsie, Ermanno Pietrosemoli
2022 Future Internet  
In particular, we focus on intelligent edge computing and networking, offloading, intelligent mobility-aware caching and forwarding and overall network performance.  ...  Advances in information-centric networks (ICN), edge computing (EC), and artificial intelligence (AI) will transform and help to realize the Intelligent Internet of Vehicles (IIoV).  ...  In [83] , joint task caching and computational offloading for vehicular edge computing are proposed.  ... 
doi:10.3390/fi14070192 fatcat:knlyn5uaurarlhq7a5p66rwrgi

Towards a Novel Air–Ground Intelligent Platform for Vehicular Networks: Technologies, Scenarios, and Challenges

Swapnil Sadashiv Shinde, Daniele Tarchi
2021 Smart Cities  
In order to satisfy the stringent requirements of new vehicular applications and services, Edge Computing (EC) is one of the most promising technologies when integrated into the Vehicular Networks (VNs  ...  By exploiting most modern technologies, with particular attention towards network softwarization, vehicular edge computing, and machine learning, we propose here three possible layered air-ground EC-enabled  ...  In particular, we have considered three main aspects able to enhance actual vehicular scenarios, i.e., the use of efficient ML platform, the exploitation of computation offloading approaches, and the optimal  ... 
doi:10.3390/smartcities4040078 fatcat:yzavo6rmlrfjzaz4364oxmwvzi

Dense Moving Fog for Intelligent IoT: Key Challenges and Opportunities [article]

Sergey Andreev, Vitaly Petrov, Kaibin Huang, Maria A. Lema, Mischa Dohler
2018 arXiv   pre-print
Conventional cloud and edge computing paradigms may thus become insufficient in supporting the increasingly stringent operating requirements of intelligent Internet-of-Things (IoT) devices that can move  ...  Envisioning gradual evolution of these infrastructures toward the increasingly denser geographical distribution of fog functionality, we in this work put forward the vision of dense moving fog for intelligent  ...  Support of Fog Enhancements in Moving IoT 1) Flexible Softwarized 5G Networking: In our scenario, the utilization of softwarized 5G networking allows for constructing flexible temporarily-optimal network  ... 
arXiv:1812.08387v1 fatcat:2ldqwzmbhreixbkqgq2jgnd52q

2021 Index IEEE Transactions on Intelligent Transportation Systems Vol. 22

2021 IEEE transactions on intelligent transportation systems (Print)  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Note that the item title is found only under the primary entry in the Author Index.  ...  ., +, TITS Aug. 2021 5293-5309 Optimal Distribution of Workloads in Cloud-Fog Architecture in Intelligent Vehicular Networks.  ... 
doi:10.1109/tits.2021.3139738 fatcat:p2mkawtrsbaepj4zk24xhyl2oa

A Hierarchical Vehicular-based Architecture for Vehicular Networks: A Case Study on Computation Offloading

Tingting Liu, Junhua Wang, BaekGyu Kim, Jiang Xie, Zhu Han
2020 IEEE Access  
In [35] , the authors propose to use fog computing technology in vehicular networks to support delay-sensitive vehicular applications.  ...  Vehicular data in the network layer are offloaded to the fog layer through BSs.  ...  Her research interests include game theory, blockchain, caching-enabled systems, edge computing, network quality of service, device-to-device networks and cognitive radio networks.  ... 
doi:10.1109/access.2020.3029169 fatcat:4k3j5mpnajgzlbdu6gxbbum6me

Artificial Intelligence for Vehicle-to-Everything: A Survey

Wang Tong, Azhar Hussain, Wang Xi Bo, Sabita Maharjan
2019 IEEE Access  
Artificial intelligence (AI) has been widely used to optimize traditional data-driven approaches in different areas of the scientific research.  ...  Recently, the advancement in communications, intelligent transportation systems, and computational systems has opened up new opportunities for intelligent traffic safety, comfort, and efficiency solutions  ...  • Security in VANETs • Vehicular edge computing • Content delivery and offloading • Vehicle platoons A.  ... 
doi:10.1109/access.2019.2891073 fatcat:kpojxobitvd7fdinkvqnchvtdm

Distributed Intelligence in Wireless Networks [article]

Xiaolan Liu and Jiadong Yu and Yuanwei Liu and Yue Gao and Toktam Mahmoodi and Sangarapillai Lambotharan and Danny H. K. Tsang
2022 arXiv   pre-print
A blend of edge computing and Artificial Intelligence (AI) techniques could optimally shift the resourceful computation servers closer to the network edge, which provides the support for advanced AI applications  ...  In this paper, we conduct a comprehensive overview of recent advances in distributed intelligence in wireless networks under the umbrella of native-AI wireless networks, with a focus on the basic concepts  ...  and resource management in vehicular networks [122] .  ... 
arXiv:2208.00545v1 fatcat:znfxcsceifevvbccog4yz5mkji
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