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Differentiated QoS DDPG-based Slicing and Drone Positioning for next generation networks 20

Differentiated QoS DDPG-based Slicing and Drone Positioning ...

20th Annual International conference on Distributed Computing in Smart sensor Systems and the Internet of Things (DCOSS-IoT)

作者： Bista, Ghoshana Bradai, Abbas Moulay, Emmanuel Univ Poitiers XLIM UMR CNRS 7252 Poitiers France Univ Cote Azur LEAT UMR CNRS 7248 Nice France

ISBN: (纸本)9798350369458;9798350369441

In the imminent era of 6G, Unmanned Aerial Vehicles (UAVs) emerge as indispensable connectors, seamlessly integrating ground and space networks with unparalleled flexibility and dynamic mobility. This article focuses on enhancing Quality of Service (QoS) by categorizing users into Premium, Silver, and Bronze tiers, akin to 5G slicing. Leveraging Deep Deterministic Policy Gradient (DDPG), the study unfolds in two phases. In the first phase, UAVs are strategically deployed using DDPG to optimize network coverage in areas of higher user density. This intelligent deployment adapts to user distribution patterns. In the second phase, dynamic repositioning using DDPG meets QoS requirements by prioritizing users based on categories. This two-phase approach showcases UAV adaptability in optimizing wireless communication systems in the evolving landscape of 6G networks. The proposed solution, driven by DDPG, ensures optimal coverage and responsiveness to diverse user needs.

关键词： Deep reinforcement learning Drone Slicing Quality Of Service

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Twofer: Ambiguous Transmissions for Low-Latency sensor networks Facing Noise, Privacy and Loss 23

Twofer: Ambiguous Transmissions for Low-Latency Sensor Netwo...

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23rd ACM/IEEE International conference on Information Processing in sensor networks, IPSN 2024

作者： Oostvogels, Jonathan Michiels, Sam Hughes, Danny Ku Leuven DistriNet Leuven3001 Belgium

ISBN: (纸本)9798350362015

Today's wireless sensor networks focus on achieving reliable data transfer over a lossy medium at the expense of latency. However, sensor data are often noisy and thus only lossily characterise real-world phenomena, rendering their exact transfer wasteful. Furthermore, many next-generation privacy-sensitive applications, such as smart grid control, real-time distributed object tracking, and inter-vehicle federated learning face latency and traffic bottlenecks due to the sheer amount of data collection required to overcome noise. We tackle this problem by introducing Twofer, a communication approach which reduces latency and traffic in high-noise or high-privacy settings by abandoning the focus on reliable networking. Twofer empowers developers to tune networks for latency-bound rather than reliability-bound performance;the system coordinates ambiguous transmissions, which are used to estimate the network-wide distribution of data, rather than to reliably communicate exact data from individual nodes. Twofer's full-stack design maintains black-box compatibility with existing application code, but advocates for, and shows the value of, uncommon physical-layer features such as symbol-synchronous communication. The system is therefore implemented and evaluated on a prototype low-latency wireless mesh network called Zero-Wire. Experiments using state-of-the-art local differential privacy protocols show 25-75% latency reductions relative to conventional approaches. The results are also future-proof, with performance advantages increasing with the strength of the privacy guarantees that are offered. © 2024 IEEE.

关键词： Semantics

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GCN-Integrated Multi-Agent Reinforcement Learning (MARL) with Modified Firefly Algorithm for Cross-Layer Optimization in Cognitive sensor networks 3

GCN-Integrated Multi-Agent Reinforcement Learning (MARL) wit...

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3rd International conference on Integrated Circuits and communication Systems, ICICACS 2025

作者： Jakranpally, Karthik Babu, Nagabathula Ramesh Babu, Doddavarapu Sreenu Rakesh, K. Barve, Amit Shelke, Atmaram Valiant It Services 4000 Stanwick ave SacramentoCA95835 United States J.B. Institute of Engineering & Technology Department of Electronics and Communication Engineering Hyderabad India Bharatratna Indira Gandhi College of Engineering Department of Electronics and Communication Engineering Solapur India Malla Reddy Engineering College for Women Department of Electronics and Communication Engineering Hyderabad India Parul University Parul Institute of Technology Faculty of Engineering and Technology Department of Computer Science and Engineering P.O.Limda Gujarat India Pune India

ISBN: (纸本)9798331508456

CSN s are integrating cognitive abilities, making it challenging to achieve optimized cross-layer performance with limited resources. Non-coordinated techniques typically demonstrate lower proficiency in dynamic spectrum management and network synchronization. We introduce Graph Convolutional networks (GCN) and Multi-Agent Reinforcement Learning (MARL) in our architectural solution, with the help of the specially designed Firefly Algorithm. The framework implements a distributed learning process, utilizing GCN for local topology perception and MARL for cooperative spectrum and optimal routing decisions. The results of experimental analysis show large gains compared to traditional methods. The proposed model provided a 94.2% recognition rate in spectrum hole identification, an 89.7% enhancement in network throughput, and a 78.5% diminution in end-to-end delay. The energy efficiency surpasses baseline techniques by 67.3%, while the raw packet delivery reliability remains at 92.8%. Integrating GCN with MARL and the improved Firefly Algorithm can significantly improve cross-layer optimization, offering a promising solution for the next generation of sensor networks. © 2025 IEEE.

关键词： Reinforcement learning

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Exploring New Opportunities for Service Delivery within next generation networks 15

Exploring New Opportunities for Service Delivery within Next...

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15th International conference on Computing communication and Networking Technologies, ICCCNT 2024

作者： Manjunath, C. Naval, Preeti Upadhyay, Ramanand School of Engineering and Technology Department of Mechanical Engineering Karnataka Bangalore India Maharishi University of Information Technology Maharishi School of Engineering & Technology Uttar Pradesh India Sanskrit University Department of Computer Science Engineering Uttar Pradesh Mathura India

ISBN: (纸本)9798350370249

These days, generation is advancing in the contemporary international at an unheard-of fee with ever-increasing bandwidth usage on contemporary networks, which might be fragile and not able to cope with related increases. This ends in demanding situations in sustaining the potential for assembly of subsequent-era desires. Therefore, research and development for the net of factors (IoT), the Semantic internet, wi-fi sensor networks (WSNs), and side Computing, amongst other emerging fields, are especially relevant today. To address those concerns, studies on revolutionary solutions to improve provider shipping for the subsequent technology of networks are being explored. One viable answer is the adoption of software-defined networking (SDN) and virtualized community technologies and offerings for Time-touchy Networking (TSN). TSN integrates numerous IT and IoT devices and services in addition to the deployment of specialized network technology, which includes 5G cell networks. This lets in for the switch of facts without compromising the overall performance and reliability of services, which includes actual-Time Networking (RTN). Furthermore, quantum technologies for IoT, consisting of Quantum Computing (qc) and Quantum networks (QN), may be explored to enhance the scalability and reliability of provider shipping networks. © 2024 IEEE.

关键词： Quantum computers

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A Three-Factor-Based Authentication Scheme of 5G Wireless sensor networks for IoT System

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IEEE INTERNET OF THINGS JOURNAL 2023年第17期10卷 15087-15099页

作者： Sahoo, Shreeya Swagatika Mohanty, Sujata Sahoo, Kshira Sagar Daneshmand, Mahmoud Gandomi, Amir H. Siksha O Anusandhan Univ Dept CSE Bhubaneswar 751019 India Natl Inst Technol Rourkela Dept Comp Sci & Engn Rourkela 769008 India Umea Univ Dept Comp Sci S-90187 Umea Sweden Stevens Inst Technol Sch Sci & Engn Hoboken NJ 07030 USA Univ Technol Sydney Fac Engn & Informat Technol Sydney NSW 2007 Australia Obuda Univ Univ Res & Innovat Ctr H-1034 Budapest Hungary

Internet of Things (IoT) is an expanding technology that facilitate physical devices to interconnect each other over a public channel. Moreover, the security of the next-generation wireless mobile communication technology, namely, 5G with IoT, has been a field of much interest among researchers in the last several years. Previously, Sharif et al. have suggested an IoT-based lightweight three-party authentication scheme proclaiming a secured scheme against different threats. However, it was found that the scheme could not achieve user anonymity and guarantee session key security. Additionally, the scheme fails to provide proper authentication in the login phase, and it s unable to update a new password in the password change phase. Thus, we propose an improved three-factor-based data transmission authentication scheme (TDTAS) to address the weaknesses. The formal security analysis has been proved using the Real-or-Random (RoR) model. The informal security analysis demonstrates that the scheme is secure against several known attacks and achieves more security features. In addition, the comparison of the work with other related schemes demonstrates the proposed scheme has less communicational and storage costs.

关键词： Authentication Wireless sensor networks Security Internet of Things Passwords Elliptic curve cryptography Cryptography 5G authentication biometric elliptic curve cryptography (ECC) Internet of Things (IoT) Real-or-Random (RoR)

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SemFusion: Multi-Source Semantic Information Fusion and communication 20

SemFusion: Multi-Source Semantic Information Fusion and Comm...

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20th IEEE International Wireless communications and Mobile Computing (IEEE IWCMC) - Green and Intelligent communications

作者： Chen, Jie Yang, Shuai Chan, Tse-Tin Pan, Haoyuan Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China Educ Univ Hong Kong Dept Math & Informat Technol Hong Kong Peoples R China

ISBN: (纸本)9798350361261;9798350361278

This paper puts forth SemFusion, a semantic information fusion and communication framework for two-hop multi-source relay networks. Although deep learning-based semantic communication is considered a new paradigm for next-generation communication networks, most prior works have focused on single-source scenarios, especially in relay networks. In contrast, we investigate a multi-source scenario where multiple sensors monitor the same scene from different angles and send partial images to the destination via a relay. The destination receives partial images of the monitored scene to reconstruct the complete image. Empowered by semantic communication, in the first hop, SemFusion allows only a subset of sensors to send their semantic information of the partial images to the relay. In the second hop, instead of forwarding the semantic information of each sensor separately, the relay further performs semantic information fusion so that only the most valuable semantic information is sent to the destination. Moreover, in contrast to the conventional end-to-end training method used in semantic communication, we propose a two-stage training strategy, where each stage corresponds to one hop, to improve the training efficiency of SemFusion. Experiments indicate that SemFusion significantly saves communication resources and provides better image reconstruction quality than state-of-the-art semantic forwarding strategies.

关键词： Deep learning information fusion relay semantic communication

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Adaptive Energy Routing Protocol using Spider Optimization in Wireless sensor networks

Adaptive Energy Routing Protocol using Spider Optimization i...

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2023 International conference on Computer communication and Informatics, ICCCI 2023

作者： Srinivasa Reddy, A. Malleswari, G. CVR College of Engineering Department of CSIT Hyderabad India CVR College of Engineering Department of CSE Hyderabad India

ISBN: (纸本)9798350348217

A WSN is a collection of sensor nodes that monitor and record the condition of the physical atmosphere and compile the obtained information in one place. The next generation networks, which include the Internet of Things, sensor Control networks, Ubiquitous sensor networks, and Machine-Oriented communications, use WSN technology as their fundamental foundation. To complete the sensing, communication, and processing functions of WSN, an energy-efficient routing protocol is required to manage the network energy dissipated and to reduce traffic and overhead during data transmission phases. To balance the energy consumption of each sensor Node in the network, clustering is utilised as a method. The Firefly and Spider Optimization algorithms serve as the foundation for the ensemble bio-inspired technique we offer here. The suggested protocol prevents unnecessary routing messages, which could lead to significant energy waste, by frequently recycling information from the source node into the sink. The ideal route path can be chosen by this routing protocol. The suggested algorithm made use of several characteristics, including node residual energy, inter-cluster distances to the sink, and cluster overlaps, to choose the optimal cluster heads at each round. To achieve the best performance for the network requirements, the parameters of the projected solution can be adaptively modified during the clustering process. © 2023 IEEE.

关键词： sensor nodes

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An Energy-Efficient communication Protocol for Power-Constrained IoT networks: A Deep Reinforcement Learning Approach 6

An Energy-Efficient Communication Protocol for Power-Constra...

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6th Global conference on Wireless and Optical Technologies, GCWOT 2023

作者： Ullah, Syed Asad Muhammad Khalid, Syed Korai, Umair Ahmed Ullah, Anayat Department of Electronic Engineering Quetta Pakistan Control Automotive and Robotics Lab Quetta Pakistan Mehran University of Engineering and Technology Department of Telecommunication Engineering Jamshoro Pakistan

ISBN: (纸本)9798350333718

Power-limited devices (or sensors) constrain the deployment of modern IoT networks, such as next-generation Industrial IoT (NG-IIoT). These networks are envisioned as the key enablers to facilitate connectivity to billions of devices for applications like smart industries, smart healthcare, etc. This paper presents an optimal up-link communication protocol for a power-limited unlicensed sensor operating among numerous licensed sensors communicating in a time division multiple access (TDMA)-based scheme. The transmission of the power-limited sensor is ensured by employing the non-orthogonal multiple access (NOMA) technique during the time slot of a licensed sensor. To ensure energy-efficient communication, we maximize the throughput of the power-limited sensor using a deep reinforcement learning (DRL) framework recognized as a combined experience replay deep deterministic policy gradient (CER-DDPG) algorithm. Our simulation results demonstrated that the CER-DDPG-based communication protocol outperforms the benchmark schemes, such as DDPG and stochastic algorithms, in terms of throughput. © 2023 IEEE.

关键词： Internet of things

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Integrated Human Activity Sensing and communications

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IEEE communicationS MAGAZINE 2023年第5期61卷 90-97页

作者： Li, Xinyu Cui, Yuanhao Zhang, J. Andrew Liu, Fan Zhang, Daqing Hanzo, Lajos Univ Technol Sydney Fac Engn & Informat Technol Ultimo NSW 2007 Australia Beijing Univ Posts & Commun BUPT Sch Informat & Commun Engn Beijing 100876 Peoples R China Southern Univ Sci & Technol Dept Elect & Elect Engn Shenzhen 518055 Peoples R China Telecom SudParis Paris France Peking Univ Beijing Peoples R China Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ England

Advances in wireless communication and signal processing facilitate integrated sensing and communication (ISAC) - a compelling technology that intrinsically combines sensing and communication functionalities for the dual-purpose exploitation of wireless/hardware resources and pursues mutual benefits. Consequently, the next-generation communications network will be perceptive. In this article, we provide a review of human-related sensing in the context of ISAC. We first present a general ISAC receiver signal processing framework, with a focus on human activity recognition (HAR). Based on its specific spatial deployments, we then categorize ISAC HAR into monostatic, bi-static, and distributed deployments, and discuss their properties, critical research problems and solutions. To facilitate the system's realization and improve its recognition performance, we then explore the inherent connections between the physical-layer system parameters and HAR performance metrics. Experimental results are presented for characterizing the sensing potentials of different ISAC systems. Finally, we review the technical challenges and identify the open research problems.

关键词： sensors Feature extraction OFDM Signal processing Wireless sensor networks Receivers Interference

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Coverage guaranteed cooperative MIMO formation for underwater MI-assisted acoustic WSNs

Coverage guaranteed cooperative MIMO formation for underwate...

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IEEE International conference on communications (IEEE ICC)

作者： Ren, Qingyan Sun, Yanjing Magno, Michele China Univ Min & Technol Sch Informat & Control Engn Xuzho Peoples R China ETH Ctr Project Based Learning Zurich Switzerland

ISBN: (纸本)9781538674628

Underwater magnetic induction (MI)-assisted acoustic cooperative multiple-input-multiple-output (MIMO) technology enables reliable communication with high throughput over long transmission distances. The combination of such as technology and underwater wireless sensor networks (UWSNs) is initiating a novel underwater Internet of Things (IoT paradigm): underwater MI-assisted acoustic cooperative MIMO WSNs. The MIMO UWSNs meets the requirements of reliable communication networks connecting underwater sensor nodes and remote surface base station (BS) for the next generation of smart ocean applications. The objective of the paper is to obtain the cooperative MIMO formation scheme in these networks for minimizing the nodes' energy consumption, simultaneously ensuring the connectivity of nodes and surface BS, and improving the coverage of networks. This paper proposes a scaly cooperative MIMO formation (SCMF) scheme based on the greedy algorithm to solve the constrained optimization problem, which is a two-phase method. In the first phase, the members of the cooperative MIMO are preliminarily determined while ensuring that there is only a single coverage hole in each iteration. In the second phase, a new master node (MN) is selected and the transmission power is determined to reduce energy consumption. Simulation results show that our proposed scheme not only fills the gap that the existing algorithm does not consider the network coverage, but also confirms that it can achieve significant energy saving and prolongs the network lifetime considerably.

关键词： Underwater Wireless sensor networks (UWSNs) Magnetic Induction (MI) Cooperative Multiple-input-multiple-output (MIMO) Energy Efficiency Coverage

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