Xi Hu

Dr. Xi Hu

orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2022 in Applied Energy
Verified
Journal Article
Closed access
XXXin Xiong
Xin Xiong
XHXi Hu
Xi Hu
TTTian Tian
Tian Tian
HGHuan Guo
Huan Guo
HLHan Liao
Han Liao

24 August 2022 in Expert Systems with Applications
Verified
Journal Article
Closed access
XHXi Hu
Xi Hu
XXXin Xiong
Xin Xiong
YWYou Wu
You Wu
MSMengji Shi
Mengji Shi
PWPeng Wei
Peng Wei
CMChunmei Ma
Chunmei Ma

6 January 2024 in Energy
Verified
Journal Article
Closed access
XXXin Xiong
Xin Xiong
ZZZhenghao Zhu
Zhenghao Zhu
JTJunhao Tian
Junhao Tian
HGHuan Guo
Huan Guo
XHXi Hu
Xi Hu

24 June 2023 in Multimedia Tools and Applications
Verified
Journal Article
Closed access
PDF file
WGWang Gao
Wang Gao
BYBaoping Yang
Baoping Yang
YXYue Xiao
Yue Xiao
PZPeng Zeng
Peng Zeng
XHXi Hu
Xi Hu
XZXun Zhu
Xun Zhu

10 June 2023 in Biomimetics
Verified
Journal Article
Open access
PDF file
XHXi Hu
Xi Hu
ZSZhiwei Shen
Zhiwei Shen
XXXin Xiong
Xin Xiong
SZSiqi Zhang
Siqi Zhang
JCJunming Chang
Junming Chang
WGWang Gao
Wang Gao
This paper proposes a novel WOA-based robust control scheme with two kinds of propagation latencies and external disturbance implemented in Software-Defined Wireless Networks (SDWNs) to maximize overall throughput and enhance the stability of the global network. Firstly, an adjustment model developed using the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme with propagation latency in device-to-device paths and a closed-loop congestion control model with propagation latency in device–controller pairs are proposed, and the effect of channel competition from neighboring forwarding devices is analyzed. Subsequently, a robust congestion control model with two kinds of propagation latencies and external disturbance is established. Then, a new WOA-based scheduling strategy that considers each individual whale as a specific scheduling plan to allocate appropriate sending rates at the source side is presented to maximize the global network throughput. Afterward, the sufficient conditions are derived using Lyapunov–Krasovskii functionals and formulated using Linear Matrix Inequalities (LMIs). Finally, a numerical simulation is conducted to verify the effectiveness of this proposed scheme.