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

共 30780 条记录，以下是1311-1320 订阅

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Practical Validation of Autonomous Source Localization with Ground Robots 6

Practical Validation of Autonomous Source Localization with ...

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6th ieee international conference on Robotic computing, (IRC)

作者： Dorau, Marcus Alpen, Mirco Horn, Joachim Helmut Schmidt Univ Inst Control Engn Hamburg Germany

ISBN: (纸本)9781665472609

A source localization experiment with a group of ground robots is presented in this paper. The process implemented on the robots is shown together with its building blocks which include methods from robotics and control. The results of the experiments show that the source localization is successful in the presented environment. The workings of the process are explained and an implication about the performance in dependence on the number of robots used is given. A way to use measurements from the mapping phase for source localization is presented which speeds up the localization process and the effect of the tuning parameters is investigated.

关键词： Autonomous navigation distributed Control Mobile Robots Obstacle Avoidance Position Estimation Signal Processing LiDAR sensor Source Localization Unmanned Aerial Vehicles

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Security and Privacy in Wireless sensor Networks Using Intrusion Detection Models to Detect DDOS and Drdos Attacks: A Survey

Security and Privacy in Wireless Sensor Networks Using Intru...

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2023 ieee international Students' conference on Electrical, Electronics and Computer Science, SCEECS 2023

作者： Chaitanya, Kosaraju Narayanan, Sankara Veltech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Avadi Tamilndu Chennai62 India Vignan's Nirula Institute of Technology and Science for Women Guntur India

ISBN: (纸本)9798350398748

Wireless sensor networks (WSN) playa significant role in the collection and transmission of data. The principal data collectors and broadcasters are small wireless sensor nodes. As a result of their disorganized layout, the nodes in this network are vulnerable to intrusion. Every aspect of human life includes some form of technological interaction. While the Covid-19 pandemic has been ongoing, the whole corporate and academic world has gone digital. As a direct result of digitization, there has been a rise in the frequency with which Internet-based systems are attacked and breached. The distributed Denial of Service (DDoS) and distributed Reflective Denial of Service (DRDoS) assaults are new and dangerous type of cyberattacks that can quickly bring down any service or application that relies on the Internet's infrastructure. Cybercriminals are always refining their methods of attack and evading detection by using techniques that are out of date. Traditional detection systems are not suited to identify novel DDoS attacks since the volume of data created and stored has expanded exponentially in recent years. This research provides a comprehensive overview of the relevant literature, focusing on deep learning for DDoS and DRDoS detection. Due to the expanding number of loT gadgets, distributed DDoS and DRDoS attacks are becoming more likely and more damaging. Due to their lack of generalizability, current attack detection methods cannot be used for early detection of DDoS and DRDoS, resulting in significant load or service degradation when implemented at the endpoint. In this research, a brief review is performed on the models that are used for identification of DDoS and DRDoS attacks. The working of the existing models and the limitations of the models are briefly analyzed in this research. © 2023 ieee.

关键词： Denial-of-service attack

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24th international conference on Parallel and distributed computing, Applications and Technologies, PDCAT 2023

24th International Conference on Parallel and Distributed Co...

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24th international conference on Parallel and distributed computing, Applications and Technologies, PDCAT 2023

ISBN: (纸本)9789819982103

The proceedings contain 28 papers. The special focus in this conference is on Parallel and distributed computing, Applications and Technologies. The topics include: Insider Trading Detection Algorithm in Industrial Chain Based on Logistics Time Interval Characteristics;link Attributes Based Multi-service Routing for Software-Defined Satellite Networks;A Fuzzy Logical RAT Selection Scheme in SDN-Enabled 5G HetNets;SSR-MGTI: Self-attention Sequential Recommendation Algorithm Based on Movie Genre Time Interval;fine Time Granularity Allocation Optimization of Multiple Networks Industrial Chains in Task Processing systems;Ε-Maximum Critic Deep Deterministic Policy Gradient for Multi-agent Reinforcement Learning;effective Density-Based Concept Drift Detection for Evolving Data Streams;an End-to-End Multiple Hyper-parameters Prediction Method for distributed Constraint Optimization Problem;Formalization and Verification of the Zab Protocol Using CSP;dynamic Priority Coflow Scheduling in Optical Circuit Switched Networks;Deep Reinforcement Learning Based Multi-WiFi Offloading of UAV Traffic;Triple-Path RNN Network: A Time-and-Frequency Joint Domain Speech Separation Model;design of Query Based Gallery Selector and Mask-Aware Loss for Person Search;a Privacy-Preserving Blockchain Scheme for the Reliable Exchange of IoT Data;R-RPT-A Reliable Routing Protocol for Industrial Wireless sensor Networks;action Segmentation Based on Encoder-Decoder and Global Timing Information;Security Challenges and Lightweight Cryptography in IoT: Comparative Study and Testing Method for PRESENT-32bit Cipher;The Prediction Model of Water Level in Front of the Check Gate of the LSTM Neural Network Based on AIW-CLPSO;Using MPIs Non-Blocking Allreduce for Health Checks in Dynamic Simulations;parallelizable Loop Detection using Pre-trained Transformer Models for Code Understanding;list-Based Workflow Scheduling Utilizing Deep Reinforcement Learning.

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A distributed Cooperative Co-Evolutionary Algorithm Based on Ring Network for distributed Large-Scale Optimization

A Distributed Cooperative Co-Evolutionary Algorithm Based on...

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2022 ieee international conference on systems, Man, and Cybernetics, SMC 2022

作者： Ou, Wen-Jie Shi, Xuan-Li Chen, Wei-Neng South China University of Technology Guangzhou China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

With the rapid development of distributed computing paradigms like edge computing and Internet of Things (IoT), many distributed edge nodes involve in data collection and decision making, resulting in many distributed optimization problems (DOPs). In this paper, we consider the DOPs with the following features. First, decision variables of a problem are naturally distributed in several spatial-distributed edges. Each computing node is responsible for one subproblem, and it can only access its corresponding local data and perform local objective evaluation. Second, some decision variables appear in different groups simultaneously, which are called overlapping variables. Third, the computing nodes can only communicate following a certain network topology. They need to work together to solve the overall problem. Because of its divide-and-conquer nature, cooperative coevolution (CC) has good potential for handling such distributed problems. Therefore, we develop a new distributed CC framework to solve them. First, a new CC architecture based on the ring network without any central node is designed. Second, an asynchronously communication strategy with low communication frequency and volume is proposed. Third, a competitive selection strategy is adopted to achieve consistency in asynchronous evolution. We define a set of distributed benchmark problems and the experimental results validate the effectiveness of the proposed approach. © 2022 ieee.

关键词： Internet of things

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A Hybrid System for Integrating Cross-Correlation, DNNs and LSTMs for Enhanced Intrusion Detection System 5

A Hybrid System for Integrating Cross-Correlation, DNNs and ...

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5th ieee international conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Singh, Niharika Prakash, Jay Mmmut Department of Itca Gorakhpur India

ISBN: (纸本)9798350383522

A WSN is a network of wireless sensors that are becoming increasingly vulnerable to cyberattacks due to their widespread deployment and resource constraints. Traditional intrusion detection systems (IDS) often struggle to keep up with the evolving nature of threats, necessitating the adoption of more sophisticated techniques. We do this by using a combination of three powerful tools: Cross correlation, which can understand words from both directions, and two types of neural networks called DNNs and LSTMs. Basically, Cross-correlation measures the similarity between two time series, which can be used to identify patterns in sensor data that deviate from normal behaviour. It used for a variety of purposes, including feature extraction, recognition, filtering, and synchronization, it can help to protect WSNs from a variety of threats, including Denial-of-Service (DoS) attacks, data manipulation attacks, and malicious control attacks. LSTM-DNN models excel at extracting temporal patterns from sensor data, making them well-suited for intrusion detection tasks. Cross-correlation, a statistical measure of similarity between two time series, can further enhance anomaly detection by identifying deviations from normal behaviour patterns. Our tests on real intrusion detection data show that this hybrid model works well. extract complex patterns, capture temporal dependencies, and identify anomalies makes it well-suited for detecting a wide range of intrusions in real-time. Mixing Cross-correlation language skills with DNN and LSTM's monitoring network traffic and system activities for suspicious behaviour that could indicate an intrusion. © 2024 ieee.

关键词： Cross-correction Deep learning DNN Intrusion detection LSTM Wireless sensor Network

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BGP Blockchain for Metaverse - A distributed Consensus System for BGP

BGP Blockchain for Metaverse - A Distributed Consensus Syste...

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2023 ieee international conference on Metaverse computing, Networking and Applications, MetaCom 2023

作者： McBride, Mike Fan, Xinxin Guzman, David Futurewei Technologies Santa ClaraCA95050 United States IoTeX Menlo ParkCA94025 United States Technical University of Munich Munich Germany

ISBN: (纸本)9798350333336

A Metaverse provides an immersive and linked experience for individuals similar to what is depicted in the book "Ready Player One". Experiences will be enabled by VR headsets, gaming systems, desktop computers, smartphones, etc., while there will likely emerge several metaverses which in turn will need interconnection. Thus, the Metaverse may be portrayed as a platform that utilizes networking to build an open ecosystem in which different platforms co-exist to serve all users. One key technology for the Metaverse is a distributed consensus system (DCS), underpinning a set of distributed applications, most notably for cryptocurrency and asset management in general, often characterized as blockchain-based trading platforms. But the use of DCSs is not limited to applications. We assert that for a true Metaverse experience, and to prevent metaverse silos, there will need to be DCS-based security between the various metaverse platforms interconnected by the Border Gateway Protocol (BGP). Key for such security is the permissionless notion in its participation to enable a truly open ecosystem, while also addressing key performance aspects such as low latency across the various interconnections. This position paper highlights various opportunities for integrating DCSs with BGP in order to provide a secure and interoperable Metaverse architecture, and we propose a BGP Blockchain system as one area for additional BGP route security. We further propose the necessary elements needed in order to address key performance aspects in such a BGP Blockchain environment. © 2023 ieee.

关键词： Interoperability

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Dynamic Energy-Efficient Clustering Algorithms Using Advanced Metaheuristics for Prolonged Network Lifetime in Wireless sensor Networks 4

Dynamic Energy-Efficient Clustering Algorithms Using Advance...

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4th international conference on Ubiquitous computing and Intelligent Information systems, ICUIS 2024

作者： Sivakumar, T. Sathiya, A. Saravanan, M. Uma, G. Samson, S. Arivumani Elangovan, A. Dept. of Electronics & Communication Engg Karur639113 India Dept. of Electronics & Communication Engg Karur639113 India Annamalai University Faculty of Engineering & Technology Dept. of Electronics & Communication Engg Chidambaram608002 India Sathyabama Institute of Science and Technology Dept. of Mathematics Chennai600119 India Arunai Engineering College Dept. of Electronics & Communication Engg Tiruvannamalai606603 India

ISBN: (纸本)9798331529635

Wireless sensor Networks (WSNs) are pivotal in modern applications, yet challenges such as energy efficiency and network lifetime remain critical. This paper proposes a Dynamic Energy-Efficient Clustering Algorithm (DEECA) utilizing hybrid metaheuristics combining Egret Swarm Optimization and Genetic Algorithms. The proposed method dynamically selects cluster heads and optimizes clustering based on node energy, distance, and traffic conditions. Simulations were conducted on diverse WSN scenarios to evaluate energy consumption, network lifetime, packet delivery ratio, and throughput. Results demonstrate that DEECA outperforms traditional algorithms such as LEACH, HEED, and PSO by achieving a 20% increase in network lifetime and a 15% improvement in packet delivery ratio. Visual analyses include energy consumption trends, coverage heatmaps, and multi-metric radar plots. The findings validate DEECA's capability to enhance energy efficiency and scalability in WSNs, offering a robust framework for real-world deployments in resource-constrained environments. © 2024 ieee.

关键词： Genetic algorithms

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sensor Data Transforming into Real-Time Healthcare Evaluation: A Review of Internet of Things Healthcare Monitoring Applications

Sensor Data Transforming into Real-Time Healthcare Evaluatio...

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2023 ieee international conference on Intelligent and Innovative Technologies in computing, Electrical and Electronics, ICIITCEE 2023

作者： Sundas, Amit Badotra, Sumit Singh, Gurpreet Lovely Professional University Department of Computer Science and Engineering Punjab Phagwara India

ISBN: (纸本)9781665462631

As the world population ages and the frequency of chronic diseases grows, it will become more crucial to discover effective healthcare solutions to guarantee that people may live healthy, productive lives. The possibility of deploying Internet of Things (IoT)-based remote health surveillance devices has gained considerable attention. This concept has the potential to improve homecare for those with chronic diseases and the elderly, while cutting healthcare costs and lessening the pressure on hospital systems. This study analyses the potential of Internet of Things (IoT) applications in healthcare settings and provides an IoT Tiered Architecture (IoTTA) for transforming sensor output data into direct clinical input. This strategy takes into consideration several activities, including sensing, transmitting, processing, storing, mining, and learning. In IoT healthcare application development, this strategy may be used to give efficient and useful solutions. Data mining, self-care, and machine learning are the fastest-growing subfields of IoT applications in healthcare, according to the report. © 2023 ieee.

关键词： Internet of things

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Mathematical Model for Determining the Geometric Location of the Environmental Pollutant Based on sensor Data 12

Mathematical Model for Determining the Geometric Location of...

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12th ieee international conference on Intelligent Data Acquisition and Advanced computing systems: Technology and Applications, IDAACS 2023

作者： Khaidurov, Vladyslav Yailymov, Bohdan Shelestov, Andrii National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Kyiv03056 Ukraine Space Research Institute NASU-SSAU Kyiv03187 Ukraine

ISBN: (纸本)9798350358056

The practical result of this work is the development of a generalized mathematical model for determining the position of an environmental pollutant. Computer simulation was carried out in order to verify the developed mathematical model. A number of computational experiments were conducted to verify the mathematical model. In the future, the developed algorithm is proposed to be used for real ground air quality measurement stations with additional use of air quality information from satellite data and specify the location of the pollution source using the Urban Atlas. © 2023 ieee.

关键词： environmental pollutant genetic algorithm inverse problem mathematical modeling PM2.5 smart city Urban Atlas

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Digital Twin Based distributed Cooperative Frequency Control of Islanded Microgrids 11

Digital Twin Based Distributed Cooperative Frequency Control...

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11th China international conference on Electricity Distribution, CICED 2024

作者： Su, Chang Liu, Wei Li, Yajie School of Automation Nanjing University of Science and Technology Nanjing China Nanjing China

ISBN: (纸本)9798350368345

Due to the intricate operational mechanisms of various renewable energy sources within existing microgrid systems, fluctuations in output or load power and frequency instability are prone to occur, this study proposes a collaborative frequency control strategy based on digital twin strategy with depth deterministic strategy gradient (DDPG). Firstly, the utilization of the DDPG algorithm in microgrid systems is analyzed, and the network parameters of the strategy are planned accordingly. Secondly, real-time data from the AC microgrid is collected through a sensor network. Finally, the DDPG algorithm model is trained to create a new intelligent algorithm engine for microgrid frequency control. Compared to simulations driven by the digital twin, the DDPG-based control strategy presented in this study enhances the control accuracy of the digital twin system for AC microgrids and accelerates convergence speed. © 2024 ieee.

关键词： deep deterministic policy gradient digital twin microgrid

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