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Wen-Tao Li
Researcher at Yunnan University
Publications - 7
Citations - 153
Wen-Tao Li is an academic researcher from Yunnan University. The author has contributed to research in topics: Mobile edge computing & Resource allocation. The author has an hindex of 2, co-authored 7 publications receiving 25 citations.
Papers
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Journal ArticleDOI
Collaborative offloading for UAV-enabled time-sensitive MEC networks
TL;DR: In this paper, the authors investigated a UAV-enabled MEC network with the consideration of multiple tasks either for computing or caching, and aimed to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices.
Journal ArticleDOI
Energy-Aware Task Offloading and Resource Allocation for Time-Sensitive Services in Mobile Edge Computing Systems
Mingxiong Zhao,Jun-Jie Yu,Wen-Tao Li,Di Liu,Shaowen Yao,Wei Feng,Changyang She,Tony Q. S. Quek +7 more
TL;DR: In this article, the authors jointly optimize task offloading and resource allocation to minimize the energy consumption subject to the latency requirement, and propose an iterative algorithm to deal with them in a sequence.
Journal ArticleDOI
Fairness-Aware Task Scheduling and Resource Allocation in UAV-Enabled Mobile Edge Computing Networks
TL;DR: This work proposes an iterative algorithm to deal with the UAV’s trajectory and resource allocation problems in a sequence, and designs a penalty method-based algorithm to reduce computation complexity when the branch-and-bound (B&B) algorithm incurs a high complexity.
Proceedings ArticleDOI
Joint Offloading and Resource Allocation for Time-Sensitive Multi-Access Edge Computing Network
TL;DR: This paper proposes an iterative algorithm to decide the proportion of data to offload and design the resource allocation strategy in a sequence and results show that the proposed algorithm achieves better performance than the reference schemes.
Posted Content
Energy Minimization for Mobile Edge Computing Networks with Time-Sensitive Constraints
TL;DR: This paper jointly optimize task offloading and resource allocation to minimize the energy consumption in an orthogonal frequency division multiple access (OFDMA)-based MEC networks, where the time-sensitive tasks can be processed at both local users and MEC server via partial offloading.