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A Wi-Fi dynamic routing algorithm based on energy prediction for wildlife monitoring wireless network

FRONTIERS IN PHYSICS 2023年 11卷

作者： Yang, Song Pan, Ziyang Tan, Hui Hu, Shaoxiang Univ Elect Sci & Technol China Sch Automat Engn Chengdu Peoples R China

The routing protocol of wildlife monitoring Wi-Fi (Wireless Fidelity) networks cannot balance node energy consumption, leading to early node death. Therefore, the research on energy balance in wildlife monitoring Wi-Fi networks is a hot topic. In order to balance the energy consumption of Wi-Fi networks and extend the lifespan of wireless networks, we designed the low energy dynamic routing protocol LEACH-EP (Low Energy Adaptive Clustering Hierarchy- Energy Prediction) based on energy prediction by analyzing the long-range dependent characteristics of the remaining energy time series (RETS) of wireless network nodes. This protocol uses the LSTM (Long Short-Term Memory) model to predict the remaining energy of network nodes, and then dynamically plans routes using future remaining energy. We conducted a networking experiment in the Anzihe Nature Reserve in Chengdu, China, and the Energy Balance Factor index of the wireless network significantly improved. The Mean Absolute Error value of network nodes is less than 60 mW, which is less than 10% of the average daily energy consumption of nodes. Half of the surviving network nodes have achieved an increase to 55.2%, and the network death time has been extended by 38.6%. The experimental results show that the energy prediction routing protocol LEACH-EP can significantly extend the node survival life and balance network energy consumption.

关键词： time series long-range dependent dynamic routing algorithm energy prediction Hurst exponent wireless network

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The optimal route planning for inspection task of autonomous underwater vehicle composed of MOPSO-based dynamic routing algorithm in currents

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APPLIED OCEAN RESEARCH 2018年 75卷 178-192页

作者： Lin, Yu-Hsien Huang, Lin-Chin Chen, Shao-Yu Yu, Chao-Ming Natl Cheng Kung Univ Dept Syst & Naval Mechatron Engn Tainan 70101 Taiwan Natl Cheng Kung Univ Res Ctr Energy Technol & Strategy Tainan 70101 Taiwan

For supporting the dynamic routing plan more efficiently, this study has been established by integrating PSO (Particle Swarm Optimization) - based dynamic routing algorithm, self-tuning fuzzy controller, a stereo-vision detection technique and 6-DOF mathematical model into the inspection system of AUV (Autonomous Underwater Vehicle). Specifically, the PSO-based dynamic routing algorithm is modified by adopting the concept of Multi-Objective Particle Swarm Optimization (MOPSO), which is able to handle different weights of objectives in parallel. Therefore, a modular structure is applied to program design of the system by using the graphical language, LabVIEW, which is composed of 6-DOF motion module, a self-tuning fuzzy control module, a stereo-vision detection module, and a dynamic routing module. Performances resulted from the MOPSO-based dynamic routing algorithm would be discussed by conducting a series of inspection tasks in the imitated offshore wind farm. Additionally, selections of fixed weight and dynamic weight of MOPSO-based dynamic routing algorithm would be compared via Pareto frontiers for feasible solutions of both sailing time and energy consumption. Eventually, it is verified that the MOPSO-based dynamic routing algorithm in our system is not only able to estimate the feasible routes intelligently, but also identify features of underwater structures for the purpose of positioning.

关键词： Image detection Underwater inspection dynamic routing algorithm Fuzzy control MOPSO

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Applying the stereo-vision detection technique to the development of underwater inspection task with PSO-based dynamic routing algorithm for autonomous underwater vehicles

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OCEAN ENGINEERING 2017年 139卷 127-139页

作者： Lin, Yu-Hsien Wang, Shun-Ming Huang, Lin-Chin Fang, Ming-Chung Natl Cheng Kung Univ Dept Syst & Naval Mechatron Engn Tainan 70101 Taiwan Natl Cheng Kung Univ Res Ctr Energy Technol & Strategy Tainan 70101 Taiwan

This research is an extension of image detection technique for obstacle-avoidance of autonomous underwater vehicles (AUVs) by applying the BK triangle sub-product of fuzzy relations. According to the concept of stereo vision detection technique, the obstacles as well as offshore structures can be reconstructed by depth images. By obtaining the depth information in the space, the optimal route can be evaluated combining PSO (Particle Swarm Optimization)-based dynamic routing algorithm. In this study, the graphical language, LabVIEW (Laboratory Virtual Instrument Engineering Workbench), is used to simulate the AUV's inspection task in the offshore wind farm. The interface shows the pose, trajectories, perspectives and real-time series of 6-Degrees of Freedom (DOF) motion for the AUV. In the existence of obstacles, the AUV is found to conduct inspection tasks of the offshore wind farm with feasible routes by considering minimum time and energy consumption successfully. In summary, the stereo-vision detection technique with PSO-based dynamic routing algorithm is not only beneficial to optimize feasible routes but also identify features of objects for the purpose tracking and obstacle-avoidance more efficiently.

关键词： Stereo vision Underwater inspection dynamic routing algorithm Fuzzy control PSO AUV

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Research on dynamic routing algorithm of the Combat Collaboration Communication Network 27

Research on Dynamic Routing Algorithm of the Combat Collabor...

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第27届中国控制与决策会议

作者： WU Chenghai ZHANG Jianjun FAN Xiquan QIN Kaiyu LIU Xiangping School of Aeronautics and Astronautics of University of Electronic Science and Technology of China Beijing Special Vehicle Research Institute

ISBN: (纸本)9781479970179

The military communication system is the key element to make a victory m the *** general,the combat collaborative communication network is a multi-hop and autonomous system,which is composed by a group of mobile nodes with wireless communication *** network has some features such as no center,self-organizing,multi-hop routing and dynamic *** of the bandwidth limitation and host energy restriction,this kind of network has some weaknesses during the operation,such as long time to establish routing,overmuch maintenance information,weak anti-damage ability and low transfer *** new dynamic routing algorithm in this paper,which combines the location information with intelligent ant colony algorithm,can quickly update the dynamic routing table and improve the linkage *** paper also verifies the algorithm by the OPNet and compares the algorithm with the traditional routing *** results demonstrate that the new algorithm can effectively reduce routing maintenance information,shorten the route setting-up time,and improve the routing forwarding and anti-jamming ability during information transmission.

关键词： Combat collaboration Communication network AD hoc network Self-organizing network dynamic routing algorithm

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dynamic routing for Integrated Satellite-Terrestrial Networks: A Constrained Multi-Agent Reinforcement Learning Approach

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2024年第5期42卷 1204-1218页

作者： Lyu, Yifeng Hu, Han Fan, Rongfei Liu, Zhi An, Jianping Mao, Shiwen Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Beijing Inst Technol Sch Cyberspace Sci & Technol Beijing 100081 Peoples R China Univ Electrocommun Grad Sch Informat & Engn Tokyo 1828585 Japan Auburn Univ Dept Elect & Comp Engn 5201 USA Auburn AL 36849 USA

The integrated satellite-terrestrial network (ISTN) system has experienced significant growth, offering seamless communication services in remote areas with limited terrestrial infrastructure. However, designing a routing scheme for ISTN is exceedingly difficult, primarily due to the heightened complexity resulting from the inclusion of additional ground stations, along with the requirement to satisfy various constraints related to satellite service quality. To address these challenges, we study packet routing with ground stations and satellites working jointly to transmit packets, while prioritizing fast communication and meeting energy efficiency and packet loss requirements. Specifically, we formulate the problem of packet routing with constraints as a max-min problem using the Lagrange method. Then we propose a novel constrained Multi-Agent reinforcement learning (MARL) dynamic routing algorithm named CMADR, which efficiently balances objective improvement and constraint satisfaction during the updating of policy and Lagrange multipliers. Finally, we conduct extensive experiments and an ablation study using the OneWeb and Telesat mega-constellations. Results demonstrate that CMADR reduces the packet delay by a minimum of 21% and 15%, while meeting stringent energy consumption and packet loss rate constraints, outperforming several baseline algorithms.

关键词： Integrated satellite-terrestrial networks dynamic routing algorithm end-to-end delay constrained multi-agent reinforcement learning

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An EEG-Based Seizure Recognition Method Using dynamic routing

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IEEE ACCESS 2024年 12卷 74054-74068页

作者： Xiong, Zhiwen Liu, Yang Jiang, Peng Yiwu Ind & Commercial Coll Jinhua 322000 Peoples R China Chongqing Coll Sci & Creat Chongqing 402160 Peoples R China

The diagnosis and treatment of brain diseases represent the forefront of brain science research, with EEG-related research occupying a uniquely significant position. In recent years, deep learning technology has been widely applied to the study of EEG signals, yet the integration of information from multiple EEG channels remains a challenging task. Based on the dynamic routing algorithm, this study established a deep neural network. Subsequently, leveraging this network, an epileptic seizure recognition method, VarChanNet, was proposed. Seizure recognition experiments were conducted using the Bonn and CHB-MIT databases. The experimental results demonstrate that the proposed VarChanNet method maintains high recognition accuracy even when the number of channels involved in the recognition process changes. It reliably functions on both the Bonn and CHB-MIT databases, indicating its potential for generalization. Furthermore, the method provides recommendations for channel selection during the recognition process. For instance, in the case of CHB-MIT, Channel 21 can be selected for single-channel recognition, Channels 2 and 3 for dual-channel, and Channels 1, 2, and 3 for triple-channel epileptic seizure recognition. In a word, the proposed VarChanNet method enables the fusion of information from different EEG channels, supporting recognition tasks even when the number of channels varies. It offers a new perspective for EEG analysis and holds the potential for generalization.

关键词： Electroencephalography Heuristic algorithms Databases routing Feature extraction Artificial neural networks Vectors Brain modeling capsule neural network dynamic routing algorithm brain connectivity seizure detection

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A routing Layer Number Generation and dynamic routing algorithm on Random Wireless Sensor Network

A Routing Layer Number Generation and Dynamic Routing Algori...

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5th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Tan Guolin Qiu Kaijin Yu Qunchao Southwest Univ Coll Comp & Informat Sci Chongqing Peoples R China

ISBN: (纸本)9781479932795

in real life, random wireless sensor network is very common, such as network of monitoring nodes in rural anti-theft system and as well as in agriculture-forestry environmental monitoring, and so on. Large-scale network, intensive nodes and disorganized distribution are the features of this network. If we transmit data by point-to-point method on such a network, then there exist disadvantages of large transmitting power at the monitoring nodes and high energy consumption of the nodes, so networking between nodes is inevitable development. Based on the characteristics of random wireless sensor network proposed routing layer number generation algorithm and dynamic routing algorithm for random wireless sensor network, to achieve transmit reliable data stably between routing nodes.

关键词： random wireless sensor network dynamic routing algorithm routing layer number generation algorithm

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Adaptive selection: External knowledge and internal context representation for few-shot intention recognition

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ALEXANDRIA ENGINEERING JOURNAL 2025年 117卷 301-310页

作者： Tang, Jingfan Li, Pengfei Zhang, Xuefeng Xia, Jianmei Hangzhou Dianzi Univ Coll Comp Sci & Technol Hangzhou 310018 Peoples R China Zhoukou Normal Univ Sch Network Engn Zhoukou 466000 Peoples R China Ningbo Univ Coll Sci & Technol Sch Informat Engn Ningbo 315300 Peoples R China Westlake Univ Affiliated Hangzhou Peoples Hosp 1 Sch Med Dept Gynecol & Obstet Hangzhou 310006 Peoples R China

Intention recognition models usually need to be trained on a large number of data, and when new intentions appear in the discriminant field, only a small amount of data is available. The method based on few-shot learning can well deal with this problem. In existing methods, the intent representation is often obtained by summing or averaging the sample representations. This will make the distance between the intents too close and cause the classification to fail. In this paper, we propose a few-shot intent recognition method based on adaptive selection of external knowledge and internal context representation. This method combines external knowledge representation extracted from a knowledge graph with internal context representation within sentences. It achieves hierarchical modeling of sentences through a dynamic routing algorithm and adaptively selects entity semantic representation information to enhance the semantic representation of entities in sentences. Experiments conducted on the Banking 77 dataset demonstrate that this method outperforms existing methods in both crossdomain and same-domain scenarios, particularly achieving an accuracy rate of 80.73 % under the 3-way 30shot setting.

关键词： Few-shot intention recognition Adaptive selection Knowledge graph Capsule network dynamic routing algorithm

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A routing Layer Number Generation and dynamic routing algorithm on Random Wireless Sensor Network

A Routing Layer Number Generation and Dynamic Routing Algori...

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2014 IEEE 5th International Conference on Software Engineering and Service Science

作者： Tan Guolin Qiu Kaijin Yu Qunchao College of Computer & Information Science Southwest University

in real life,random wireless sensor network is very common,such as network of monitoring nodes in rural anti-theft system and as well as in agriculture-forestry environmental monitoring,and so ***-scale network,intensive nodes and disorganized distribution are the features of this *** we transmit data by point-to-point method on such a network,then there exist disadvantages of large transmitting power at the monitoring nodes and high energy consumption of the nodes,so networking between nodes is inevitable *** on the characteristics of random wireless sensor network proposed routing layer number generation algorithm and dynamic routing algorithm for random wireless sensor network,to achieve transmit reliable data stably between routing nodes.

关键词： random wireless sensor network dynamic routing algorithm routing layer number generation algorithm

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A DGA Domain Name Detection Method Based on Two-Stage Feature Reinforcement 22

A DGA Domain Name Detection Method Based on Two-Stage Featur...

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IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) / BigDataSE Conference / CSE Conference / EUC Conference / ISCI Conference

作者： Yang, Hongyu Zhang, Tao Hu, Ze Zhang, Liang Cheng, Xiang Civil Aviat Univ China Sch Safety Sci & Engn Tianjin Peoples R China Civil Aviat Univ China Sch Comp Sci & Technol Tianjin Peoples R China Univ Arizona Sch Informat Tucson AZ USA Yangzhou Univ Sch Informat Engn Yangzhou Jiangsu Peoples R China

ISBN: (纸本)9798350381993;9798350382006

The domain name features used in the existing domain name detection methods about domain generation algorithm (DGA) are generally easy to evade, which results in some common DGA domain name detection methods failing to effectively detect the DGA domain name. To solve the issues, we propose a DGA domain name detection method based on two-stage feature reinforcement. Firstly, we encode the domain name to obtain the domain name word vector. Secondly, the slice pyramid network (SPN) is used to process the word vector to extract the domain name feature. Thirdly, we reinforce the domain name feature by using the two-stage reinforcement method we proposed. The two-stage reinforcement method reinforces the domain name feature by adding domain name semantic information to the extracted features and reducing feature information redundancy to improve the stability of the domain name feature, meanwhile, we convert the reinforced domain name feature to the primary capsules to reduce feature loss. Finally, we use the dynamic routing algorithm to process the primary capsules to generate digital capsules, and then the digital capsules are used to detect domain names. Experimental results on domain name detection and domain name family classification both show that compared with the state-of-the-art methods, our method has better detection performances.

关键词： DGA domain name detection slice pyramid network two-stage feature reinforcement dynamic routing algorithm

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