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Mobile Edge Computing

Mobile Edge Computing

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Background of MEC:

Owing to a large amount of data and tremendous devices, mobile-edge computing (MEC) has been proposed to improve the Quality of Service (QoS) of users at the edge, e.g., the macro base station (MBS) is equipped with computing resources to provide services to UEs or wireless devices

Presentation PPT Download:
  1. 2022-05-18 Machine Learning Driven Latency Optimization for Application-aware Edge Computing-based IoTs ― IEEE ICC 2022
  2. 2022-04-13 Machine Learning Driven UAV-assisted Edge Computing ― IEEE WCNC 2022
  3. 2020-10 Latency-aware Service Provisioning in UAV Mobile Edge Computing ― IEEE IoT 2020

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Mobile Edge Computing Publications:

Journals Articles:
  1. L. Zhang, B. Jabbari and N. Ansari, “Deep Reinforcement Learning Driven UAV-assisted Edge Computing,” IEEE Internet of Things Journal, vol. 9, no. 24, pp. 25449-25459, Dec. 2022.
  2. L. Zhang and J. Chakareski, “UAV-Assisted Edge Computing and Streaming for Wireless Virtual Reality,” IEEE Transactions on Vehicular Technology, vol. 71, no. 3, pp. 3267-3275, Mar. 2022.
  3. L. Zhang and N. Ansari, “Optimizing the Operation Cost for UAV-aided Mobile Edge Computing,” IEEE Transactions on Vehicular Technology, vol. 70, no. 6, pp. 6085-6093, Jun. 2021.
  4. L. Zhang and N. Ansari, “Latency-Aware IoT Service Provisioning in UAV-Aided Mobile-Edge Computing Networks,” IEEE Internet of Things Journal, vol. 7, no. 10, pp. 10573-10580, Oct. 2020.
Conference Papers:
  1. L. Zhang and B. Jabbari, “Machine Learning Driven Latency Optimization for Application-aware Edge Computing-based IoTs,” Proc. IEEE International Conference on Communications (ICC), pp. 183-188, May 2022.
  2. L. Zhang, B. Jabbari and N. Ansari, “Machine Learning Driven UAV-assisted Edge Computing,” Proc. IEEE Wireless Communications and Networking Conference (WCNC), pp. 2220-2225, Apr. 2022.