H
Hongju Cheng
Researcher at Fuzhou University
Publications - 42
Citations - 844
Hongju Cheng is an academic researcher from Fuzhou University. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 14, co-authored 38 publications receiving 657 citations. Previous affiliations of Hongju Cheng include Chinese Ministry of Education & Wuhan University.
Papers
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Journal ArticleDOI
Nodes organization for channel assignment with topology preservation in multi-radio wireless mesh networks
Hongju Cheng,Naixue Xiong,Athanasios V. Vasilakos,Laurence T. Yang,Guolong Chen,Xiaofang Zhuang +5 more
TL;DR: A channel assignment algorithm named as DPSO-CA which is based on the discrete particle swarm optimization and can be used to find the approximate optimized solution is formulated and it is shown that the algorithm can be easily extended to the case with uneven traffic load in the network.
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Energy-efficient node scheduling algorithms for wireless sensor networks using Markov Random Field model
TL;DR: This paper introduces how to model the spatial correlation among sensed data by Markov Random Field model and proposes a novel Data Amendment Procedure (DAP), Representative node Selection Procedure (RSP) and energy-efficient Node Scheduling Algorithm (NSA) respectively for these above problems.
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Multi-Step Data Prediction in Wireless Sensor Networks Based on One-Dimensional CNN and Bidirectional LSTM
TL;DR: A novel model for multi-step sensory data prediction in wireless sensor network based on 1-D CNN (One-Dimensional Convolutional Neural Network) and Bi-LSTM (Bidirectional Long and Short-Term Memory) is proposed and its performance is better compared with other related methods.
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Multi-Source Temporal Data Aggregation in Wireless Sensor Networks
TL;DR: An energy-efficient multi-source temporal data aggregation model called MSTDA in WSNs is proposed, a feature selection algorithm using particle swarm optimization (PSO) is presented to simplify the historical data source firstly, and a data prediction algorithm based on improved BP neural network with PSO is proposed.
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Data prediction model in wireless sensor networks based on bidirectional LSTM
TL;DR: This paper has proposed a new data prediction method multi-node multi-feature (MNMF) based on bidirectional long short-term memory (LSTM) network that has better performance compared with the other methods in many evaluation indicators.