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Your search keyword '"Huang, Hualong"' showing total 26 results
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26 results on '"Huang, Hualong"'

1. Battery-Care Resource Allocation and Task Offloading in Multi-Agent Post-Disaster MEC Environment

Author

Tang, Yiwei, Huang, Hualong, Zhan, Wenhan, Min, Geyong, Duan, Zhekai, and Lei, Yuchuan

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

Being an up-and-coming application scenario of mobile edge computing (MEC), the post-disaster rescue suffers multitudinous computing-intensive tasks but unstably guaranteed network connectivity. In rescue environments, quality of service (QoS), such as task execution delay, energy consumption and battery state of health (SoH), is of significant meaning. This paper studies a multi-user post-disaster MEC environment with unstable 5G communication, where device-to-device (D2D) link communication and dynamic voltage and frequency scaling (DVFS) are adopted to balance each user's requirement for task delay and energy consumption. A battery degradation evaluation approach to prolong battery lifetime is also presented. The distributed optimization problem is formulated into a mixed cooperative-competitive (MCC) multi-agent Markov decision process (MAMDP) and is tackled with recurrent multi-agent Proximal Policy Optimization (rMAPPO). Extensive simulations and comprehensive comparisons with other representative algorithms clearly demonstrate the effectiveness of the proposed rMAPPO-based offloading scheme., Comment: accepted by wcnc2024

Published
2023

5. Nanomaterials for Modified Asphalt and Their Effects on Viscosity Characteristics: A Comprehensive Review.

Author

Huang, Hualong, Wang, Yongqiang, Wu, Xuan, Zhang, Jiandong, and Huang, Xiaohan

Abstract

The application of nanomaterials as modifiers in the field of asphalt is increasingly widespread, and this paper aims to systematically review research on the impact of nanomaterials on asphalt viscosity. The results find that nanomaterials tend to increase asphalt's viscosity, enhancing its resistance to high-temperature rutting and low-temperature cracking. Zero-dimension nanomaterials firmly adhere to the asphalt surface, augmenting non-bonding interactions through van der Waals forces and engaging in chemical reactions to form a spatial network structure. One-dimensional nanomaterials interact with non-polar asphalt molecules, forming bonds between tube walls, thereby enhancing adhesion, stability, and resistance to cyclic loading. Meanwhile, these bundled materials act as reinforcement to transmit stress, preventing or delaying crack propagation. Two-dimensional nanomaterials, such as graphene and graphene oxide, participate in chemical interactions, forming hydrogen bonds and aromatic deposits with asphalt molecules, affecting asphalt's surface roughness and aggregate movement, which exhibit strong adsorption capacity and increase the viscosity of asphalt. Polymers reduce thermal movement and compact asphalt structures, absorbing light components and promoting the formation of a cross-linked network, thus enhancing high-temperature deformation resistance. However, challenges such as poor compatibility and dispersion, high production costs, and environmental and health concerns currently hinder the widespread application of nanomaterial-modified asphalt. Consequently, addressing these issues through comprehensive economic and ecological evaluations is crucial before large-scale practical implementation. [ABSTRACT FROM AUTHOR]

Published
2024
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6. A Cloudlet Placement Method Based on Birch in Wireless Metropolitan Area Network

Author

Peng, Kai, Liang, Haodong, Zhang, Yiwen, Qian, Xingda, Huang, Hualong, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Chen, Phoebe, Editorial Board Member, Cuzzocrea, Alfredo, Editorial Board Member, Du, Xiaoyong, Editorial Board Member, Kara, Orhun, Editorial Board Member, Liu, Ting, Editorial Board Member, Sivalingam, Krishna M., Editorial Board Member, Slezak, Dominik, Editorial Board Member, Washio, Takashi, Editorial Board Member, Yang, Xiaokang, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zheng, Zibin, editor, Dai, Hong-Ning, editor, Tang, Mingdong, editor, and Chen, Xiangping, editor

Published
2020
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12. Stereo Matching Using Conditional Adversarial Networks

Author

Huang, Hualong, Huang, Bo, Lu, Hongtao, Weng, Huiyu, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Xie, Shengli, editor, Li, Yuanqing, editor, Zhao, Dongbin, editor, and El-Alfy, El-Sayed M., editor

Published
2017
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13. Convolutional Gated Recurrent Units Fusion for Video Action Recognition

Author

Huang, Bo, Huang, Hualong, Lu, Hongtao, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Xie, Shengli, editor, Li, Yuanqing, editor, Zhao, Dongbin, editor, and El-Alfy, El-Sayed M., editor

Published
2017
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15. Intelligent Computation Offloading and Resource Allocation in IIoT with End-Edge-Cloud Computing Using NSGA-III

Author

Peng, Kai, Huang, Hualong, Zhao, Bohai, Jolfaei, Alireza, Xu, Xiaolong, Bilal, Muhammad, Peng, Kai, Huang, Hualong, Zhao, Bohai, Jolfaei, Alireza, Xu, Xiaolong, and Bilal, Muhammad

Abstract

The Industrial Internet of things (IIoT), which consists of massive IoT devices and wireless access points in industrial infrastructures to acquire intelligent services, has been considered as a vital physical information platform for implementing Industry 4.0. Further, mobile edge computing (MEC) has brought an opportunity to accelerate the development of IIoT. However, the existing MEC methods may not be directly used for IIoT scenarios due to the large size of IIoT devices and the characteristics of the applications, as well as the limited and heterogeneous resources of edge servers. In view of this, the computation offloading and resource allocation are formulated as a multi-objective optimization problem, and an end-edge-cloud collaborative intelligent optimization method is devised in this paper. Comprehensive experiments and evaluations are carried out to prove the effectiveness and efficiency of our proposed method with regard to the energy consumption and time consumption of IIoT devices, as well as resource utilization and load balancing of edge servers.

Published
2023

16. Distributed Incentives for Intelligent Offloading and Resource Allocation in Digital Twin Driven Smart Industry

Author

Peng, Kai, Huang, Hualong, Bilal, Muhammad, Xu, Xiaolong, Peng, Kai, Huang, Hualong, Bilal, Muhammad, and Xu, Xiaolong

Abstract

Mobile edge computing is one of the key enabling technologies of smart industry solutions, providing agile and ubiquitous services for mobile devices (MDs) through offloading latency-critical tasks to edge service providers. However, it is challenging to make optimal decisions of computation offloading and resource allocation while ensuring the privacy and information security of MDs. Consequently, we consider a new vision of digital twin (DT) empowered edge networks, where the optimization problem is formulated as a two-stage incentive mechanism. First, the resource allocation strategy is determined by the interaction among DTs according to the credit-based incentives. Afterward, a distributed incentive mechanism based on the Stackelberg-based alternating direction method of multipliers is opted to obtain the optimal offloading and privacy investment strategies in parallel. Numerical results show that the proposed two-stage incentive mechanism achieves effective resource allocation and computation offloading while simultaneously improving the privacy and information security of MDs.

Published
2023

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