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Air-Ground Integrated Mobile Edge Networks: A Survey

Wen Zhang, Longzhuang Li, Ning Zhang, Tao Han, Shangguang Wang
2020 IEEE Access  
Because of easy deployment and high mobility of unmanned aerial vehicles (UAVs), air-ground integrated mobile edge networks (AGMEN) is proposed, where UAVs are employed to assist the MEC network.  ...  Such an AGMEN expects to provide MEC services ubiquitously and reliably. In this article, we first introduce the characteristics and components of UAV.  ...  For this end, resource partitioning and bit allocation strategies are discussed.  ... 
doi:10.1109/access.2020.3008168 fatcat:544d6keravgozkdktd6tfhry7e

Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey [article]

Tianxu Li, Kun Zhu, Nguyen Cong Luong, Dusit Niyato, Qihui Wu, Yang Zhang, Bing Chen
2022 arXiv   pre-print
The issues consist of network access, transmit power control, computation offloading, content caching, packet routing, trajectory design for UAV-aided networks, and network security issues.  ...  Future Internet involves several emerging technologies such as 5G and beyond 5G networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of Things (IoTs).  ...  networks [166] [169] [170] Proposes a joint trajectory design and power allocation policy for each UAV to serve the partitioned mobile users Solves the trajectory design problem for an MEC-enabled network  ... 
arXiv:2110.13484v2 fatcat:u2o5uxms65gmnp3q7xbh35l5oi

Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization

Mushu Li, Nan Cheng, Jie Gao, Yinlu Wang, Lian Zhao, Xuemin Shen
2020 IEEE Transactions on Vehicular Technology  
Given the service requirements of users, we aim to maximize UAV energy efficiency by jointly optimizing the UAV trajectory, the user transmit power, and computation load allocation.  ...  In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption.  ...  CONCLUSIONS In this paper, an optimization approach has been proposed to maximize the energy efficiency of a UAV-assisted MEC system, where the UAV trajectory design and resource allocation have been jointly  ... 
doi:10.1109/tvt.2020.2968343 fatcat:g66xsgzqofdy3azr2jafikfpym

2021 Index IEEE Transactions on Wireless Communications Vol. 20

2021 IEEE Transactions on Wireless Communications  
Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TWC Feb. 2021 1105-1121 Trajectory Optimization and Resource Allocation for OFDMA UAV Relay Networks.  ... 
doi:10.1109/twc.2021.3135649 fatcat:bgd3vzb7pbee7jp75dnbucihmq

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

Quoc-Viet Pham, Fang Fang, Vu Nguyen Ha, Md. Jalil Piran, Mai Le, Long Bao Le, Won-Joo Hwang, Zhiguo Ding
2020 IEEE Access  
Therefore, combining UAV with the MEC system may raise the following challenges: • Mobility control and trajectory optimization: Since UAV has limited flight time, the optimal path planning for UAVs MEC  ...  Hence, jointly optimizing the path planning and resource allocation for MEC-UAV system is an open challenging problem.  ... 
doi:10.1109/access.2020.3001277 fatcat:isme7xwfejf4pfnowosljxnzja

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art [article]

Quoc-Viet Pham, Fang Fang, Vu Nguyen Ha, Md. Jalil Piran, Mai Le, Long Bao Le, Won-Joo Hwang, Zhiguo Ding
2020 arXiv   pre-print
The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities.  ...  We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.  ...  Therefore, combining UAV with MEC system may raise to the following challenges: • Mobility control and trajectory optimization: Since UAV has limited flight time, the optimal path planning for UAVs MEC  ... 
arXiv:1906.08452v2 fatcat:krti5kagxzeqte7osdpxs4lxoe

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.  ...  This paper provides a comprehensive research review on RL-enabled MEC and offers insight for development in this area.  ...  In [97] , a joint optimization problem of trajectory planning, task scheduling, and resource allocation was investigated for system timeliness, i.e., the freshness of data and computational tasks.  ... 
arXiv:2201.11410v4 fatcat:24igkq4kbrb2pjzwf3mf3n7qtq

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.  ...  This paper provides a comprehensive research review on RL-enabled MEC and offers insight for development in this area.  ...  In [100] , a joint optimization problem of trajectory planning, task scheduling, and resource allocation was investigated for system timeliness, i.e., the freshness of data and computational tasks.  ... 
doi:10.1109/access.2022.3183647 fatcat:pd5z6q4innd5jl25g4r7b4nq3i

A Survey on Mobile Edge Computing: The Communication Perspective

Yuyi Mao, Changsheng You, Jun Zhang, Kaibin Huang, Khaled B. Letaief
2017 IEEE Communications Surveys and Tutorials  
We also discusse a set of issues, challenges and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware  ...  MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision.  ...  Therefore, reconfiguring the mobile networks to guarantee the connectivity and low latency between the UAVs and the infrastructure becomes a critical task for designing MEC systems for connected UAVs.  ... 
doi:10.1109/comst.2017.2745201 fatcat:rkgkslqx4bg6vp4ynidiuzqtga

A Survey of Rate-optimal Power Domain NOMA with Enabling Technologies of Future Wireless Networks [article]

Omar Maraqa, Aditya S. Rajasekaran
2020 arXiv   pre-print
The considered system models, the optimization methods utilized to maximize the achievable rates, and the main lessons learnt on the optimization and the performance of these NOMA-enabled schemes and technologies  ...  including MISO, MIMO, mMIMO, advanced antenna architectures, mmWave and THz, CoMP, cooperative communications, cognitive radio, VLC, UAV and others.  ...  Also, the authors would like to thank Ericsson Canada Inc. and the Discovery Grant of the Natural Sciences and Engineering Research Council of Canada for support.  ... 
arXiv:1909.08011v4 fatcat:xlt7aul75zhozkb2stpbs4q2fm

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
, Toward Swarm Coordination: Topol-ogy-Aware Inter-UAV Routing Optimization; TVT Sept. 2020 10177-10187 Hong, P., see Li, R., TVT April 2020 4006-4018 Hong, P., see Xu, J., TVT June 2020 6688-6698 Hong  ...  + Check author entry for coauthors ami-mFading Channels With Integer and Non-Integerm; TVT March 2020 2785-2801 Hoang, T.M., Tran, X.N., Nguyen, B.C., and Dung, L.T., On the Performance of MIMO Full-Duplex  ...  ., +, TVT Feb. 2020 1741-1750 Energy-Efficient UAV-Assisted Mobile Edge Computing: Resource Allocation and Trajectory Optimization.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

A Survey on Cache-Aided NOMA for 6G Networks [article]

Dipen Bepari, Soumen Mondal, Aniruddha Chandra, Rajeev Shukla, Yuanwei Liu, Mohsen Guizani, Arumugam Nallanathan
2022 arXiv   pre-print
Beginning with fundamentals of cache-aided NOMA technology, we summarize the performance goals of cache-aided NOMA systems, present the associated design challenges, and categorize related recent literature  ...  to content servers in parallel and improve the cache hit probability.  ...  Authors are aiming to reduce the total consumption of energy by the UAV-assisted NOMA-based MEC networks taking into account the task computation allocation, computation capacity, and UAV trajectory in  ... 
arXiv:2205.05321v1 fatcat:zdsvoxspdfgzvpbxelbuqp2cnq

Mobility- and Energy-Aware Cooperative Edge Offloading for Dependent Computation Tasks

Mahshid Mehrabi, Shiwei Shen, Yilun Hai, Vincent Latzko, George P. Koudouridis, Xavier Gelabert, Martin Reisslein, Frank H. P. Fitzek
2021 Network  
We formulate the minimization problem for the consumed battery energy for task execution, task data transmission, and waiting for offloaded task results on end devices.  ...  (or follow predetermined mobility paths) and for independent computation tasks.  ...  The flight path of the UAVs is optimized to effectively support the offloading of independent tasks that can be partitioned.  ... 
doi:10.3390/network1020012 fatcat:a4zr7umze5db5annz5oq3yfpmi

Deep Reinforcement Learning Based Dynamic Trajectory Control for UAV-assisted Mobile Edge Computing [article]

Liang Wang, Kezhi Wang, Cunhua Pan, Wei Xu, Nauman Aslam, Arumugam Nallanathan
2021 arXiv   pre-print
We aim to minimize energy consumption of all the UEs via optimizing the user association, resource allocation and the trajectory of UAVs.  ...  In this paper, we consider a platform of flying mobile edge computing (F-MEC), where unmanned aerial vehicles (UAVs) serve as equipment providing computation resource, and they enable task offloading from  ...  to optimize the UAV trajectory and resource allocation.  ... 
arXiv:1911.03887v2 fatcat:ni56ykwxlfgxjf66cdsvskxlkm

2020 Index IEEE Transactions on Wireless Communications Vol. 19

2020 IEEE Transactions on Wireless Communications  
Identification for MIMO Systems in Dynamic Environments; TWC June 2020 3643-3657 Huang, C., see Yang, M., TWC Sept. 2020 5860-5874 Huang, D., Tao, X., Jiang, C., Cui, S., and Lu, J  ...  ., and Saad, W., Joint Access and Backhaul Resource Management in Satellite-Drone Networks: A Competitive Market Approach; TWC June 2020 3908-3923 Hu, Y.H., see Xia, M., TWC June 2020 3769-3781 Hua,  ...  ., +, TWC Sept. 2020 6116-6129 Joint Cache Placement, Flight Trajectory, and Transmission Power Optimization for Multi-UAV Assisted Wireless Networks.  ... 
doi:10.1109/twc.2020.3044507 fatcat:ie4rwz4dgvaqbaxf3idysubc54
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