Maoli Wang
Qufu Normal University
10 Papers
Maoli Wang is an academic researcher from Qufu Normal University. The author has contributed to research in topics: Computer science & Edge computing. The author has an hindex of 2, co-authored 2 publications.
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Papers
Service Offloading With Deep Q-Network for Digital Twinning-Empowered Internet of Vehicles in Edge Computing
Xiaolong Xu,Bowen Shen,Sheng Ding,Gautam Srivastava,Muhammad Bilal,Mohammad Reza Khosravi,Varun G. Menon,Mian Ahmad Jan,Maoli Wang +8 more
TL;DR: A service offloading (SOL) method with deep reinforcement learning, is proposed for DT-empowered IoV in edge computing, which leverages deep Q-network (DQN), which combines the value function approximation of deep learning and reinforcement learning.
212
6G-Enabled Short-Term Forecasting for Large-Scale Traffic Flow in Massive IoT Based on Time-Aware Locality-Sensitive Hashing
TL;DR: A big data-driven and nonparametric model aided by 6G is proposed in this article to extract similar traffic patterns over time for accurate and efficient short-term traffic flow prediction in massive IoT, which is mainly based on time-aware locality-sensitive hashing (LSH).
Stackelberg Game-Based Intelligent Offloading Incentive Mechanism for a Multi-UAV-Assisted Mobile Edge Computing System
TL;DR: In this paper , the authors studied the intelligent offloading problem for a multiple UAV-assisted mobile edge computing (MEC) system in a MEC scenario where a natural disaster has damaged the edge server.
21
Path Optimization of Agricultural Robot Based on Immune Ant Colony: B-Spline Interpolation Algorithm
TL;DR: A path planning algorithm based on immune ant colony B spline interpolation is presented to eliminate path duplication and corner inflection points, increase the smoothness of the agricultural robot’s path trajectory, and enhance the path planning performance.
8
The Current Research Status of AI-Based Network Security Situational Awareness
Maoli Wang,Yang Yu +1 more
TL;DR: In this article , the authors focus on artificial intelligence, summarizes the related definitions and classic models of network security situational awareness, and provides an overview of artificial intelligence using machine learning techniques.