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检索条件"任意字段=6th IEEE International Conference on Distributed Computing in Sensor Systems"

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SNDU: Sequential Networking for distributed Underwater Acoustic sensor Network 6

SNDU: Sequential Networking for Distributed Underwater Acous...

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6th international conference on Information Communication and Signal Processing, ICICSP 2023

作者： Xi, Bochen Gao, Xiang Southeast University Key Laboratory of Underwater Acoustic Signal Processing Ministry of Education Nanjing China

ISBN: (纸本)9798350339994

It is of great theoretical significance and application value to construct a reliable underwater sensor network (UWSN), and the networking protocol plays a key role in the data transmission of UWSN. the research of traditional underwater networking protocols mostly focuses on the process of topology discovery with low energy consumption and fast convergence without recognizing the problem of route repair in the case of node failure. Aiming at achieving low delay, low collision rate and high robustness, this paper proposes a sequential networking protocol suitable for distributed underwater acoustic sensor networks. the protocol is divided into two stages: on Stage 1, the strategy of laying and networking is adopted to shorten the networking time;on Stage 2, the importance of nodes in the network is assigned to achieve the effect of quickly selecting sub-optimal routes and reducing the delay of fault repair. Simulation results show that this protocol can effectively reduce the networking time and fault repair time in UWSN, and reduce the networking communication and repair communication times, which may well contrapuntally meet the needs of low latency, low energy consumption, high repair rate and other scenarios. © 2023 ieee.

关键词： distributed network networking protocol Sequential networking underwater communication

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Scalable Deep Learning for Industry 4.0: Speedup with distributed Deep Learning and Environmental Sustainability Considerations 6th

Scalable Deep Learning for Industry 4.0: Speedup with Distri...

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6th international conference on Cloud computing and Artificial Intelligence-Technologies and Applications

作者： Lerat, Jean-Sebastien Malimoudi, Sidi Ahmed Haute Ecole Hainaut Comp Sci & Management Dept Mons Belgium Univ Mons Sci & Technol Dept Mons Belgium

ISBN: (纸本)9783031786976;9783031786983

this paper presents a solution for leveraging High-Performance computing (HPC) infrastructures, and investigates the integration of distributed deep learning (DDL) techniques to address Industry 4.0 challenges across three distinct applications: intrusion detection with multi-layer perceptron, defect identification with convolutional neural networks, and predictive maintenance with recurrent neural network. Experimental results, underscore the scalability and efficiency of the proposed DDL approach. Notably, computations are accelerated by up to 46 times. In addition to performance metrics, this research places significant emphasis on environmental sustainability. Detailed examination of energy consumption patterns on the HPC infrastructure aims to minimize the carbon footprint associated with deep learning processes. this dual focus on efficiency and sustainability positions the approach as a holistic and responsible solution for Industry 4.0 applications. the practical insights enhance the efficiency of deploying DDL in HPC infrastructure. Additionally, they highlight the significance of ecofriendly AI practices for ethical and environmentally sustainable technological progress.

关键词： Zero-carbon

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VPFL: A Verifiable Property Federated Learning Framework Against Invisible Attacks in distributed IoT 25

VPFL: A Verifiable Property Federated Learning Framework Aga...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Wu, Yuanxiang Cheng, Hang Guan, Lin Liu, Peihao Chen, Fei Wang, Meiqing College of Computer Science and Big Data Fuzhou University Fuzhou China

ISBN: (纸本)9798350330014

the development of Federated Learning (FL) offers an efficient Machine Learning (ML) approach with privacy protection to solve the data island issue in distributed Internet of things (IoT). However, existing FL frameworks still suffer from invisible attacks in IoT environments, such as free-rider attacks, backdoor attacks, and model theft. In this paper, we propose a Verifiable Property Federated Learning (VPFL) framework to overcome the above invisible attacks. We present a black-box watermarking task distribution mechanism to prevent free-rider attacks by verifying the property of local models. Our adversarial fine-tuning embedding technique can not only eliminate backdoors in global models, but also simultaneously embed white-box watermarks into model parameters to prevent model theft. Comprehensive experimental evaluations demonstrate that our framework outperforms state-of-the-art schemes in terms of security and feasibility against invisible attacks. © 2023 ieee.

关键词： Internet of things

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DEN-Based Converged Architecture for RAN and distributed CN toward 6G 19

DEN-Based Converged Architecture for RAN and Distributed CN ...

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Zong, Jiaying Huang, Xuan Liu, Yang Wang, Qingtian Xing, Yanxia China Telecom Res Inst Res Ctr 6G Beijing Peoples R China

ISBN: (纸本)9798350333398

the diverse performance requirements and distributed deployment needs brought about by new types of services have blurred the boundary between the radio access network (RAN) and core network (CN), necessitating research on 6G network architecture. At the deep edge node (DEN) side, this paper investigates a RAN-CN converged architecture to address the demand for RAN and CN collaboration, as well as the problem of functional redundancy between RAN and sunken CN. Additionally, this paper analyzes and studies the procedures of UE initial access and registration, session management, UE context management, based on the converged architecture. the suggested architecture can eliminate functional redundancy between RAN and CN, simplify the existing signaling and data transmission procedures, and shorten latency and processing complexity.

关键词： radio access network RAN-CN convergence service-based architecture deep edge node

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FLARE: Detection and Mitigation of Concept Drift for Federated Learning based IoT Deployments 19

FLARE: Detection and Mitigation of Concept Drift for Federat...

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Chow, theo Raza, Usman Mavromatis, Ioannis Khan, Aftab Toshiba Europe Ltd Bristol Res & Innovat Lab Bristol Avon England Kings Coll London London England Waymap Ltd London England

ISBN: (纸本)9798350333398

Intelligent, large-scale IoT ecosystems have become possible due to recent advancements in sensing technologies, distributed learning, and low-power inference in embedded devices. In traditional cloud-centric approaches, raw data is transmitted to a central server for training and inference purposes. On the other hand, Federated Learning migrates both tasks closer to the edge nodes and endpoints. this allows for a significant reduction in data exchange while preserving the privacy of users. Trained models, though, may under-perform in dynamic environments due to changes in the data distribution, affecting the model's ability to infer accurately;this is referred to as concept drift. Such drift may also be adversarial in nature. therefore, it is of paramount importance to detect such behaviours promptly. In order to simultaneously reduce communication traffic and maintain the integrity of inference models, we introduce FLARE, a novel lightweight dual-scheduler FL framework that conditionally transfers training data, and deploys models between edge and sensor endpoints based on observing the model's training behaviour and inference statistics, respectively. We show that FLARE can significantly reduce the amount of data exchanged between edge and sensor nodes compared to fixed-interval scheduling methods (over 5x reduction), is easily scalable to larger systems, and can successfully detect concept drift reactively with at least a 16x reduction in latency.

关键词： Federated Learning distributed deployment Concept Drift Model Robustness Scalable IoT Inference

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Adaptive DoS Attack Detection in SDN 6

Adaptive DoS Attack Detection in SDN

引用

6th ieee international conference on Emerging Smart computing and Informatics, ESCI 2024

作者： Mathew, Rejo Rajan Vidhate, Amarsinh Ramrao Adik Institute of Technology Dept of Information Technology Navi Mumbai India Ramrao Adik Institute of Technology Dept of Computer Engineering Navi Mumbai India

ISBN: (纸本)9798350306613

SDN is gaining popularity for a few years now. there has been a massive increase in the adoption of SDN, especially with the rise in demand for IoT, and 5G networks which have led to a lot of research in this area. As adoption increased threats have also risen. Out of all the attacks Denial of Service attacks has been most used against SDN. Most countermeasures that are proposed by researchers are specific to attacks on the individual layer and are short-Term ones. Most DoS attack detection focuses on Fast DoS attack. the paper proposes and implements an adaptive DoS Attack detection method which detects Fast DoS attack and detects Low DoS attack avoiding any confusion with congestion. © 2024 ieee.

关键词： Blockchain distributed Denial of Service OpenFlow SDN Software Defined Network

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A Differential BCG sensor System for Long Term Health Monitoring Experiment on the ISS 18

A Differential BCG Sensor System for Long Term Health Monito...

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18th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Kulau, Ulf Rust, Jochen Szafranski, Daniel Drobczyk, Martin Albrecht, Urs-Vito Hamburg Univ Technol Smart Sensors Hamburg Germany DSI Aerosp Technol GmbH Bremen Germany TU Braunschweig Braunschweig Germany German Aerosp Ctr DLR Inst Space Syst Cologne Germany Bielefeld Univ Med Fac OWL Dept Digital Med Bielefeld Germany

ISBN: (纸本)9781665495127

Comprehensive health monitoring is highly relevant for the safety of manned spaced missions. Ballistocardiography (BCG) is a method for providing information of the heart physiology by measuring accelerations on the body surface that are caused by forwarded heart and blood movements in the vascular system. In order to provide a sensor system with a high signal quality, this paper presents differential BCG sensing at the system level for digital accelerometers and its integration into a sensing system. the system is part of a running experiment of the Cosmic Kiss mission on the international Space Station (ISS). Compared to single sensor solutions, the noise power scales down to about 50%, the Signal to Noise Ratio (SNR) is increased by a factor of 1.87 and the BCG signal variability especially improves for diastole area. Furthermore, by exploiting differential sensing techniques, both high reliability is achieved and common mode interference is mitigated, which is of high importance within the scope of space applications. Beside the presentation of the entire wireless sensor system including differential sensing approach, pre-processing unit and Ultra Wideband (UWB) communication module, results of the pre-flight tests show the performance of the system as well as the suitability for targeted mission.

关键词： sensor System Ballistocardiography Deifferential Sensing Accelerometers Health Monitoring Human Spaceflight

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distributed Twins in Edge computing: Blockchain and IOTA 19

Distributed Twins in Edge Computing: Blockchain and IOTA

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Sadad, Anwar Khan, Muazzam A. Ghaleb, Baraq Khan, Fadia Ali Driss, Maha Boulila, Wadii Ahmad, Jawad Quaid i Azam Univ Dept Comp Sci Islamabad Pakistan Edinburgh Napier Univ Sch Comp Engn & Built Environm Edinburgh Midlothian Scotland Univ Wah Dept Mech Engn Wah Engn Coll Wah Pakistan Prince Sultan Univ Secur Engn Lab CCIS Riyadh Saudi Arabia Prince Sultan Univ Robot & Internet Things Lab Riyadh Saudi Arabia

ISBN: (纸本)9798350333398

Blockchain (BC) and Information for Operational and Tactical Analysis (IOTA) are distributed ledgers that record a huge number of transactions in multiple places at the same time using decentralized databases. Both BC and IOTA facilitate Internet-of-things (IoT) by overcoming the issues related to traditional centralized systems, such as privacy, security, resources cost, performance, and transparency. Still, IoT faces the potential challenges of real-time processing, resource management, and storage services. Edge computing (EC) has been introduced to tackle the underlying challenges of IoT by providing real-time processing, resource management, and storage services nearer to IoT devices on the network's edge. To make EC more efficient and effective, solutions using BC and IOTA have been devoted to this area. However, BC and IOTA came with their pitfalls. this survey outlines the pitfalls of BC and IOTA in EC and provides research directions to be investigated further.

关键词： Blockchain IOTA distributed Ledger Edge computing IoT Bitcoin

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A Float-Point Arithmetic Logic Unit for High Performance RISC-V Processor 6

A Float-Point Arithmetic Logic Unit for High Performance RIS...

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6th international conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Wei, Chunyuan Yuan, Chuan Qi, Yu Xu, Bangjian Niu, Xin College of Computer Science and Electronic Engineering Hunan University Changsha China College of Electrical and Information Engineering Hunan University Changsha China College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Laboratory Changsha China

ISBN: (纸本)9798331541750

With the rapid advancement of artificial intelligence, chips have become increasingly important. the emerging RISC-V instruction set gradually provides powerful computing support for this field. In this context, along with the computing requirements of deep learning, this paper presents the design of a high-performance floating-point arithmetic logic unit (FALU) that facilitates calculations with double-precision, single-precision, half-precision, and Bfloat16 precision data. this design is based on a single-channel algorithm with merged rounding. It improves and implements a composite adder that combines high and low bits. It also proposes a tree-like floating-point comparator based on the Kogge-Stone parallel prefix network. To ensure that the FALU components meet performance requirements, we undergo functional verification in the Vivado simulation environment. Operating at 1.47GHz under the 28nm CMOS process, the components achieve the predetermined performance indicators. © 2024 ieee.

关键词： Computer circuits

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Optimal Dispatch of distributed Generators in Multiple Microgrids Using Hybrid PSO-GWO 6

Optimal Dispatch of Distributed Generators in Multiple Micro...

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6th international conference on Energy Conservation and Efficiency, ICECE 2023

作者： Hassan, Usman Ahmad, Aftab University of Engineering and Technology Taxila Department of Electrical Engineering Taxila Pakistan

ISBN: (纸本)9798350332193

In modern energy systems, policies are evolving the grid structures speedily to enhance the penetration of more distributed generation (DGs). Among DGs, renewable energy sources (RES) are a better choice to reduce the cost of main grid. this paper proposed a hybrid approach based on particle swarm optimization and grey wolf optimization (PSO-GWO) to solve the optimal dispatch problem of distributed microgrids (MGs). Both dispatchable and non-dispatchable DGs were considered in the case study comprising three MGs. the proposed dispatch strategy to dispatchable DGs like microturbines, fuel cells, and energy storage systems along with non-dispatchable DGs such as solar photovoltaic and wind turbines reduced the energy cost of the MGs. the results of this study make MGs less dependable on the main grid and enhance their reliability. the proposed technique was implemented in MATLAB R2021a and the cost was improved by $217.55 for main grid. © 2023 ieee.

关键词： distributed power generation

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