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Deep learning based Enhanced Data Aggregation with Multi-Objective Optimization method in wireless sensor networks

PEER-TO-PEER networkING AND APPLICATIONS 2025年第3期18卷 1-17页

作者： Thiyagarajan, N. Shanmugasundaram, N. KGiSL Inst Technol Dept Elect & Commun Engn Coimbatore Tamil Nadu India Sri Eshwar Coll Engn Dept Elect & Commun Engn Coimbatore Tamil Nadu India

Nowadays, wireless sensor networks (WSNs) play a significant role in data collection and dissemination in various applications. In hierarchically clustered WSN models, the cluster heads (CHs) consume more energy due to the additional workload of receiving, aggregating, and transmitting data from their member nodes to the sink. The CH selection is important in extending the lifetime of WSNs by conserving energy expenditure at sensor nodes. Therefore, this paper proposes a Deep Learning based Enhanced Data Aggregation with Multi-Objective Optimization method in wireless sensor network. The Gazelle Optimization Algorithm (GOA) is employed for the energy-efficient cluster-head selection with the incorporation of a well-defined fitness function constructed with intra-cluster proximity, sink proximity, and the residual energy. A single candidate optimizer (SCO) is introduced to select the most suitable routes from the CH to the sink node, considering factors such as energy and proximity. To enhance the efficiency of data aggregation (DA), a novel approach is introduced using a Self-Attention-Based Provisional Variational-Auto-Encoder Generative-Adversarial-network (SPVAGAN). The proposed framework demonstrates its effectiveness in Energy Consumption (Ec), Packet Delivery Ratio (PDR), End-to-End Delay (E2ED), communication Overhead (CoH), and Data Accuracy over the other models.

关键词： Gazelle Optimization Algorithm Single Candidate Optimizer wireless sensor network Cluster Head

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A blockchain-based approach for secure energy-efficient IoT-based wireless sensor networks for smart cities

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Alexandria Engineering Journal 2025年 126卷 1-7页

作者： Aldawsari, Hamad Department of Computer Science Haql University College University of Tabuk Tabuk Saudi Arabia

As a result of IoT-based wireless sensor networks (IoT-WSNs), resource-constrained environments are becoming more efficient and dynamic. Even though IoT-WSNs have many advantages, they also face significant challenges, including their high energy consumption, limited lifespan, and security vulnerabilities. IoT-WSNs for smart cities could be made more energy-efficient and secure by using a blockchain-based approach. Blockchain technology improves energy efficiency and reduces communication costs while ensuring decentralized, secure spectrum management. A smart contract and distributed ledger mechanism reduce redundant data transmissions and facilitate network trust. A blockchain-enabled clustering mechanism allows energy-aware sensing and resource allocation, as well as cognitive radio technology used for efficient spectrum utilization. Compared to existing techniques, the proposed method is more energy efficient, more accurate in sensing spectrums, and more secure. IoT-WSNs provide a solution to energy and security challenges in smart city infrastructure, contributing to sustainable development. © 2025 The Authors

关键词： Blockchain Secure energy-efficient IoT wireless sensor networks Smart cities

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Collaborative Multi-AUV Optical communication via Deep Reinforcement Learning

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IEEE sensorS JOURNAL 2025年第1期25卷 1627-1640页

作者： Li, Mengzhen Luo, Hanjiang Tao, Hang Li, Xiang Dong, Peijun Wu, Kaishun Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China Hong Kong Univ Sci & Technol Guangzhou Guangzhou Peoples R China

The next generation of wireless network 6G is envisioned to enable seamless global connectivity for the Internet of Everything (IoE) on the Earth. To this end, implementing high-speed wireless communication from the deep ocean to the sea surface leveraging multiple autonomous underwater vehicles (AUVs) with underwater wireless optical communication (UWOC) is an emerging and promising technology that enables real-time data collection for accurate underwater exploration and monitoring, for example, coordinated moving target monitoring. However, multihop UWOC is more susceptible to beam misalignment and positional uncertainty caused by external interference in the harsh environment. To address these challenges, we design a cooperative movement scheme for multiple AUVs based on a deep reinforcement learning (DRL) approach to perform robust optical communication. We first model the optical channel and then analyze the link performance to satisfy the bit error rate (BER) requirements. Afterward, we map the cooperative optical communication problem into a Markov decision process (MDP) and then we propose a deep deterministic policy gradient (DDPG)-based cooperative movement strategy, which is integrated with the extended Kalman filter (EKF) technique. Finally, we design a multi-AUV adaptive adjustment scheme for enhanced optical link adaptation, including an optical link distance adjustment algorithm, and an adaptive transmit power adjustment algorithm based on twin-delayed deep deterministic policy gradient (TD3). Through extensive simulations, it is demonstrated that the proposed algorithms are effective in achieving cooperative and adaptive underwater optical communication via multi-AUV under mobile scenarios.

关键词： Autonomous underwater vehicles (AUVs) deep reinforcement learning (DRL) extended Kalman filter (EKF) underwater optical communication underwater sensor networks Autonomous underwater vehicles (AUVs) deep reinforcement learning (DRL) extended Kalman filter (EKF) underwater optical communication underwater sensor networks

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Multi-AAV-Assisted On-Demand Charging in Dense wireless Rechargeable sensor networks

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IEEE INTERNET OF THINGS JOURNAL 2025年第7期12卷 8821-8834页

作者： Xiong, Runqun Chen, Ciyuan Xu, Jiajun Dong, Xirui Pu, Jiahang Southeast Univ Sch Comp Sci & Engn Nanjing 211189 Peoples R China Huawei Technol Suzhou Co Ltd Suzhou 215000 Peoples R China Southeast Univ Coll Software Engn Nanjing 211189 Peoples R China

wireless rechargeable sensor networks (WRSNs) have emerged as a promising solution to overcome the energy bottleneck in traditional battery-powered sensor networks. However, the uncertain energy demands and dense deployment of sensor nodes pose significant challenges to efficient charging scheduling in WRSNs. To address these challenges, this article proposes a novel multi-AAV assisted on-demand partial charging scheduling (MOPCS) algorithm. MOPCS integrates the advantages of one-to-many charging, partial charging, and dynamic multi-AAV coordination to maximize the network lifetime and energy utilization. The key contributions of this work include a real-time adaptive charging scheduling trigger mechanism, an energy-efficient charging cluster division method, a spatiotemporally balanced task allocation among multiple autonomous aerial vehicles (AAVs), and a hybrid priority-based charging path planning algorithm. Extensive simulations demonstrate that MOPCS significantly outperforms state-of-the-art algorithms in terms of charging request response timeliness, node survival rate, and AAV energy efficiency, especially in dense network deployments. This work provides valuable insights and practical solutions for the design and optimization of AAV-assisted charging scheduling in WRSNs, paving the way for more sustainable and scalable wireless sensor networks in various application scenarios.

关键词： Energy consumption Autonomous aerial vehicles Energy efficiency Dynamic scheduling wireless sensor networks Resource management Optimization Inductive charging Heuristic algorithms wireless communication On-demand schedule autonomous aerial vehicle (AAV)-assisted mobile charging wireless rechargeable sensor networks (WRSNs)

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Intelligent Reflecting Surface-Enabled Anti-Detection for Secure Sensing and communications

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IEEE wireless communicationS 2025年第2期32卷 156-163页

作者： Zheng, Beixiong Xiong, Xue Ma, Tiantian Tang, Jie Ng, Derrick Wing Kwan Swindlehurst, A. Lee Zhang, Rui South China Univ Technol Sch Microelect Guangzhou Peoples R China South China Univ Technol Sch Future Technol Guangzhou Peoples R China South China Univ Technol Sch Elect & Informat Engn Guangzhou Peoples R China Univ New South Wales Sydney Australia Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA USA Chinese Univ Hong Kong Shenzhen Peoples R China Natl Univ Singapore Singapore Singapore

The ever-increasing reliance on wireless communication and sensing has led to growing concerns over the vulnerability of sensitive information to unauthorized detection and interception. Traditional anti-detection methods are often inadequate, struggling with limited adaptability and diminished effectiveness against advanced detection technologies. To overcome these challenges, this article presents intelligent reflecting surface (IRS) technology as a groundbreaking tool for enabling flexible electromagnetic manipulation, which has the potential to revolutionize anti-detection in both electromagnetic stealth/spoofing (evading radar detection) and covert communication (facilitating secure information exchange). We explore the fundamental principles of IRS technology for anti-detection, highlight its advantages over traditional anti-detection techniques, and discuss the main design challenges for implementing IRS-based anti-detection systems. Through the examination of case studies and future research directions, we provide a comprehensive overview of the potential of IRS technology to serve as a formidable shield in the modern wireless landscape.

关键词： Radar Radar detection Electromagnetics wireless communication sensors wireless sensor networks communication system security Radar scattering Receivers Radar cross-sections

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Gradient-Based Optimization of Coherent Distributed Arrays

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IEEE sensorS JOURNAL 2025年第4期25卷 7417-7430页

作者： Lipski, Michael V. Kompella, Sastry Narayanan, Ram M. US Naval Res Lab Washington DC 20375 USA Nexcepta Inc Gaithersburg MD 20878 USA Penn State Univ Sch Elect Engn & Comp Sci State Coll PA 16802 USA

In a coherent communication system consisting of an open-loop distributed transmit array sending messages to a distributed receive array, the combined transmit-receive gain is characterized by the coherent communication gain (CCG). We consider the problem of optimizing CCG using the positions of the individual transmitter and receiver nodes as well as the beam angle of the transmit array as degrees of freedom. We focus on the use of gradient descent to find locally optimal configurations for node positions, which is motivated by two observations: first, the NP-hardness of the problem precludes an exhaustive search for the globally optimal configuration of node positions;and second, the positions of the network nodes are likely not arbitrary. That is, the initial, nonoptimized node placement is intentional and is determined by higher-layer network objectives. The hypothesis is that the CCG of a communication network can be improved in a deterministic fashion using the steepest descent algorithm to make relatively small adjustments to node positions. We develop the closed-form expressions for the rate of change of CCG with respect to node positions and transmit array beam angle. Next, we use the expressions to implement a spherical quadratic steepest descent (SQSD) algorithm and use simulations to test SQSD alongside pattern search and particle swarm optimization to determine theoretical gain improvements achieved by the algorithms, as well as the expected average node displacement.

关键词： Gain Receivers Array signal processing Transmitters Synchronization wireless sensor networks Optimization sensor arrays sensors Collaboration Coherent arrays collaborative beamforming distributed arrays mobile ad hoc network (MANET) optimization wireless sensor network (WSN)

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Equivalent Bandwidth Concept and Its Usage in the network Selection

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China communications 2025年第2期22卷 213-225页

作者： Ma Anhua Pan Su Zhou Weiwei Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts and TelecommunicationsNanjing 210003China

Maximize the resource utilization efficiency and guarantee the quality of service(QoS)of users by selecting the network are the key issues for heterogeneous network operators,but the resources occupied by users in different networks cannot be compared *** paper proposes a network selection algorithm for heterogeneous ***,the concept of equivalent bandwidth is proposed,through which the actual resources occupied by users with certain QoS requirements in different networks can be compared *** the concept of network applicability is defined to express the abilities of networks to support different *** proposed network selection algorithm first evaluates whether the network has enough equivalent bandwidth required by the user and then prioritizes network with poor applicability to avoid the situation that there are still residual resources in entire network,but advanced services can not be *** simulation results show that the proposed algorithm obtained better performance than the baselines in terms of reducing call blocking probability and improving network resource utilization efficiency.

关键词： call blocking probability equivalent bandwidth heterogeneous network network applicability

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Attention-Guided wireless Channel Modeling and Generating

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APPLIED SCIENCES-BASEL 2025年第6期15卷 3058-3058页

作者： He, Yawen Xu, Nan Cheng, Li Yuan, Haiwen Wuhan Inst Technol Sch Elect & Informat Engn Wuhan 430205 Peoples R China

Due to the fast advancement in wireless communication technology, the demand for the modeling and generating of wireless channels is increasing. Deep learning technology is gradually applied in the wireless communication field, and the Generative Adversarial network (GAN) framework provides a new solution for channel modeling. This paper presents a method based on Wasserstein GAN with gradient penalty (WGAN-GP) guided by an attention mechanism for wireless channel modeling and generating. The feature extraction capability of the model is enhanced by adding a channel attention mechanism in WGAN-GP, and the representation capability of the model is enhanced by adaptively recalibrating the channel feature response. The experimental results demonstrate that the proposed approach accurately models the channel distribution and generates data that closely aligns with the real channel distribution. The proposed method has been shown to achieve superior qualitative and quantitative evaluation compared to the existing method.

关键词： channel modeling data generating deep learning WGAN-GP

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SORT-secured optimal routing technique for smart cities using IoTenabled wireless sensor networks

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Multimedia Tools and Applications 2025年 1-32页

作者： Gandhi, Charu Mohindra, Anubhuti Department of Engineering and Technology Gurugram University Gurugram India Department of CSE & IT Jaypee Institute of Information Technology Noida India

The advancement of smart cities and IoT technologies poses challenges such as the need for eco-friendly solutions and efficient data collection and communication in these environments. The objective is to propose a new architecture for data collection and communication in IoT smart applications, focusing on green IoT solutions and addressing the challenges of quality definition in smart cities. The proposed methods include the Secured Optimal Routing Technique (SORT) using wireless sensor networks (WSN) with IoT, the CMBS algorithm for IoT sensor cluster formation, the Enhanced Differentiation Search (EDS) algorithm to estimate sensor node trust, and a lightweight signcrypt approach for data encryption. Additionally, the Optimum Decisive Former (ODF) method is used to compute the best route in the IoT platform. The SORT technique is implemented and evaluated using the NS2 tool for network simulation. The performance of the SORT technique is compared with existing techniques, demonstrating its effectiveness in addressing the challenges of data collection, communication, and eco-friendly IoT solutions in smart cities. The study concludes that the proposed SORT technique, along with the CMBS algorithm, EDS algorithm, and lightweight signcrypt approach, contributes to the advancement of intelligent and sustainable smart cities by improving data collection, communication efficiency, and eco-friendliness in IoT applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： sensor nodes

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Ultralow Ohmic Contact in Recess-Free Ultrathin Barrier AlGaN/GaN Heterostructures Across a Wide Temperature Range

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Chinese Journal of Electronics 2025年第1期26卷 137-145页

作者： Yuhao Wang Sen Huang Qimeng Jiang Xinhua Wang Jie Fan Haibo Yin Ke Wei Yingkui Zheng Xinyu Liu Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics of the Chinese Academy of Sciences Institute of Microelectronics University of Chinese Academy of Sciences

“Ohmic-before-passivation” process was implemented on ultrathin-barrier AlGaN（<6 nm）/GaN heterostructure to further reduce the ohmic contact resistance（Rc）. In this process, alloyed Ti/Al/Ni/Au ohmic metal was formed first, followed by AlN/SiNxpassivation contributed to restore two-dimensional electron gas（2DEG） in the access region. Due to the sharp change in the concentration of 2DEG at the metal edge, a reduced transfer length consisted with lower Rcare achieved compared to that of ohmic contact on AlGaN（～20 nm）/GaN heterostructure with pre-ohmic recess process. Temperature-dependent current voltage measurements demonstrate that the carrier transport mechanism is dominated by thermionic field emission above 200 K and by field emission below 200 K. The “ohmic-before-passivation” process enables the relative stability of ohmic contacts between 50 K and 475 K and significantly improves the direct current characteristics of GaN-metal-insulator-semiconductor-high electron mobility transistor, offering a promising means for scaling down and enabling the utilization of low-voltage GaN-based power devices in extreme environmental conditions.

关键词： optimal CDG framework telecommunication network routing energy efficient WSN CS compressed sensing diffusion wavelet transform matrix optimal compressed data gathering framework wireless sensor network Measurement matrix telecommunication power management measurement matrix optimization algorithm compressed data measurement sparse representation optimal data aggregation tree algorithm energy consumption trees (mathematics) Compressed sensing (CS) signal representation wireless sensor networks (WSNs) ODAT algorithm data transmission reduction wavelet transforms wireless sensor networks Optimal data aggregation tree (ODAT) MMOA energy consumption minimization routing technology energy conservation DWTM

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