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检索条件"任意字段=Conference on Internet Performance and Control of Network Systems II"

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Early detection of DDoS attack using integrated SDN-Blockchain architecture for IoT

Early detection of DDoS attack using integrated SDN-Blockcha...

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2022 International conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2022

作者： Sumathi, A.C. Ahalawat, Anchal Rameshkumar, Abijoy KPR Institute of Engineering and Technology Computer Science and Engineering Coimbatore India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

The advancement in technology with the internet commences the new era of communication by allowing people to communicate through text, audio and video calling, images and video clips and various other applications. The applications of internet paved the way to a technology called internet of Things (IoT). IoT is interpreted as communication between components, (e.g., sensors and actuators) through the internet designed for application-oriented assistance. IoT is simple and user friendly which attracted the people to adapt the technology. Despite the immense benefits of the IoT device, it is *** results in the devices to undergo various attacks. Distributed Denial-of-Service (DDoS) attack challenges the security in IoT devices. Therefore, this paper proposes the integrated SDN-Blockchain architecture to provide the secure connection for IoT devices. Software Defined networking (SDN) technology is used in optimizing the network management, enabling a dynamic and efficient network configuration programming thereby optimizing the performance and monitoring the network. SDN transforms computer network by segregating control plane and data plane. Blockchain is represented as collection of blocks which are linked together as a back traced *** previous block hash is used to connect the blocks together in the chain. The characteristics of Blockchain include decentralization, peer-to-peer connectivity, and immutable ledgers. © 2022 IEEE.

关键词： internet of things

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Distributed Optimal Data Allocation in Finite Time with Efficient Communication and Transmission Stopping over Dynamic networks 61

Distributed Optimal Data Allocation in Finite Time with Effi...

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IEEE 61st conference on Decision and control (CDC)

作者： Rikos, Apostolos, I Hadjicostis, Christoforos N. Johansson, Karl H. KTH Royal Inst Technol Div Decis & Control Syst SE-10044 Stockholm Sweden Digital Futures SE-10044 Stockholm Sweden Univ Cyprus Dept Elect & Comp Engn CY-1678 Nicosia Cyprus

ISBN: (纸本)9781665467612

In this paper, we focus on the problem of data sharing over a wireless computer network (i.e., a wireless grid). Given a set of available data, we present a distributed algorithm, which operates over a dynamically changing network and allows each node to calculate the optimal allocation of data in a finite number of time steps. We show that our proposed algorithm (i) converges to the optimal solution in finite time with very high probability, and (ii) once the optimal solution is reached, each node is able to cease transmissions without needing knowledge of a global parameter such as the network diameter. Furthermore, our algorithm (i) operates exclusively with quantized values (i.e., each node processes and transmits quantized information), (ii) relies on event-driven updates, and (iii) calculates the optimal solution in the form of a quantized fraction which avoids errors due to quantization. Finally, we demonstrate the operation, performance, and potential advantages of our algorithm over random dynamic networks.

关键词： Optimal systems

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Solar Photovoltaic Forecasting Using ANN network for Central and Southern Regions of Jordan

Solar Photovoltaic Forecasting Using ANN Network for Central...

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2023 IEEE Jordan International Joint conference on Electrical Engineering and Information Technology, JEEIT 2023

作者： Al-Rawashdeh, Rafi Alsarayreh, Mohammad Al-Odienat, Abdallah Mutah University Faculty of Engineering Mutah Jordan King Abdullah Ii School of Engineering Princess Sumaya University for Technology Department of Electrical Engineering Amman11941 Jordan Samra Electric Power Company Amman Jordan Amman Arab University Department of Renewable Energy Engineering Amman11953 Jordan Mutah University Faculty of Engineering Jordan

ISBN: (纸本)9798350324051

The use of renewable energy has increased during the last several decades. The most popular renewable energy source is photovoltaic (PV) technology, which uses solar radiation to create electricity. However, a number of variables, such as position, weather, etc., have an impact on the production of PV electricity. It is crucial to control the inherent changeability of PV plants as they expand and contribute significantly to the production of grid power. Predicting solar PV is therefore essential for ensuring efficient and dependable grid functioning. The forecasting model's inputs were historic PV power output data from two solar power installations in Jordan's central and southern regions. The prediction of PV power production in this research takes into account a stacked long short-term memory network (LSTM), a crucial part of the deep recurrent neural network. This model and Nonlinear Autoregressive NARX have been contrasted (Dynamic Neural network). The outcomes demonstrated equivalent, admirable performance for both the dynamic NARX ANN and the LSTM, with NARX being better. The dynamic ANN can be claimed to be superior to the deep neural network (DNN) for time-based performance modeling of PV systems with varying data. © 2023 IEEE.

关键词： Long short-term memory

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SDNaaS: Software-Defined networking as an IXP Service

SDNaaS: Software-Defined Networking as an IXP Service

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IEEE conference on network Function Virtualization and Software Defined networks (IEEE NFV-SDN)

作者： Mendoza, John Robert Frias, Levin Austria, Isabel Festin, Cedric Ocampo, Roel Univ Philippines Diliman Elect & Elect Engn Inst Quezon City Philippines Univ Philippines Diliman Adv Sci & Technol Inst Dept Sci & Technol Quezon City Philippines Univ Philippines Diliman Dept Comp Sci Quezon City Philippines

ISBN: (数字)9781665473347

ISBN: (纸本)9781665473347

network operators need to manage the full lifecycle of controller instance clusters to ensure a high-performance and reliable distributed control plane service for software-defined networks (SDN). However, setting up and configuring multiple controller instances is a resource-intensive and complex process. Outsourcing to a third-party provider may alleviate the challenges associated with managing and orchestrating hardware and software infrastructure required for operating a distributed SDN control plane. We present SDN-as-a-Service (SDNaaS), an internet exchange point-based SDN control plane service provider. We analyzed public IXP datasets and show that these internet infrastructures possess desirable characteristics for hosting missioncritical network services. By leveraging IXP strengths, and implementing techniques for coordinating disparate resources (aggregating capacity), compartmentalizing controller services (decoupling controller functions into distinct yet composable services), and client-side resource discovery (delegating controller selection to switches), SDNaaS can provide the capability for network operators to scale controller processing capacity by as much as 2.6x as compared to single site while concurrently enhancing system availability.

关键词： Mission critical systems Decentralized control Process control Software Hardware internet Software reliability

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Bayesian network and Semidefinite Programming Based Wireless Power Transfer Manufacturing System State Estimation and Regulation 24

Bayesian Network and Semidefinite Programming Based Wireless...

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24th International conference on Advanced Communication Technology (ICACT) - Artificial Intelligence Technologies toward Cybersecurity

作者： Rana, Md Masud Dahotre, Narendra Univ North Texas Dept Mat Sci & Engn Denton TX 76203 USA Univ North Texas Coliege Informat Sci Denton TX 76203 USA

ISBN: (纸本)9791188428090

In order to supply energy to the smart objects such as electric vehicles and smart phones using wireless power transfer (WPT) framework, the internet of things (IoT) embedded sensors and actuators can play critical roles for sensing, monitoring and regulating the WPT system states. Specifically, the smart sensors are used to transmit sensing state information to the control center, where the state estimation program runs to know the operating and health conditions of WPT system. This study proposes a Bayesian network based WPT system state estimation algorithm. This scheme can estimate the WPT system states in a distributed way using the Bayesian tree structure. Afterwards, the semidefinite programming based optimal feedback control scheme is proposed to regulate the system states. Simulations results show that the proposed approach provides significant performance improvement compared with the existing scheme.

关键词： Bayesian network controller internet of things sensors semidefinite programming system state estimation wireless power transfer systems.

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network Traffic Prediction and Congestion control Using a Feed Forward Neural network

Network Traffic Prediction and Congestion Control Using a Fe...

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International IEEE conference on Intelligent systems, IS

作者： JohnPaul Nwigwe Iain Martin Craig Ramsay School of Science and Engineering (Computing) University of Dundee United Kingdom

ISBN: (数字)9798350350982

ISBN: (纸本)9798350350999

The surge in internet of Things (IoT) usage has precipitated the need to replace classical internet network prediction and congestion control methods with a more efficient and reliable learning-based approach. Many machine-learning based approaches have been offered by different studies to solve this problem but not without limitations. In this study, we propose a new feed forward neural network with a multi-channel routing congestion control system (FFNN-MCRCCS) to optimize network prediction and congestion control problem. The nodes in the proposed network are mutually connected to enable the firing of neurons in a more decentralized manner to update their weights in order to call the recursive square function to predict the traffic. The exponent value of the recursive function serves as a parameter to determine the channel with the minimum congestion threshold for packet transmission. The results of the experiment show that the proposed model has the capability to optimize network traffic for effective utilization of network resources more than the baseline and the counterpart methods. The performance evaluation metrics used for the experiment include mean square error throughput, link utilization, average jitter, settling time, queue length and network and network convergence.

关键词： performance evaluation Neurons Telecommunication traffic Throughput Routing internet of Things Feeds Reliability Surges Biological neural networks

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An access control and authentication scheme for secure data sharing in the decentralized cloud storage system 5

An access control and authentication scheme for secure data ...

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5th conference on Cloud and internet of Things (CIoT)

作者： Khatiwada, Pankaj Yang, Bian Norwegian Univ Sci & Technol Dept Informat Secur & Commun Technol Gjovik Norway

ISBN: (纸本)9781665479646

Data privacy and data availability remain the major concern in centralized cloud storage, which could be handled effectively through the concept of decentralized data storage. However, the secrecy of data sharing is a rising concern in the decentralized data storage for which the effective access control and data sharing scheme, hash and session key-dependent attribute-based encryption (HS-ABE) is proposed in this research. Accordingly, the multi-level access control and sharing strategy authenticates the genuine requestors and assures access to the requestors upon the authentication of their attribute sets. In this perspective of access control and secure data sharing, Ethereum blockchain, decentralized Interplanetary File System (IPFS), HS-ABE are organized. The data owners (DOs) provide the secret attribute set for the requestors ensuring fine-grained access over the data. The performance of the developed HS-ABE scheme is investigated and compared with the conventional strategies, where the memory usage of the proposed scheme is 5812 Kbps, which proclaims a well-defined secure access control and authentication in the Blockchain-based cloud storage.

关键词： Secure data transfer Decentralized storage systems Blockchain Security

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Traffic control Analysis in High Altitude Platforms using a Semi-Markov Process Approach 18

Traffic Control Analysis in High Altitude Platforms using a ...

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18th IEEE International conference on Advanced networks and Telecommunications systems, ANTS 2024

作者： Raj, Raina Selvamuthu, Dharmaraja Mishra, Deepak IIT Delhi Bharti School of Telecommunication Technology and Management New Delhi110016 India University of New South Wales School of Electrical Engineering and Telecommunications SydneyNSW2052 Australia

ISBN: (纸本)9798350391725

This study uses a cooperative communication approach to propose a traffic model for relay nodes in space-airground networks. The proposed model is employed in threelayer networks: low earth satellite (LEO), high altitude platform (HAP), and user devices on the ground. This type of aerial communication network is adopted in most internet of Things (IoT) networks. The analysis has been carried out by constructing traffic models. The traffic model has been analyzed by applying the semi-Markov process due to the non-exponential behaviour of some of the transitions of states. The network's practical lifetime, the average delay of source/relay packets, and throughput are investigated through the novel traffic model. Finally, through numerical illustrations, the impact of the performance measures is shown by conducting a sensitivity analysis. © 2024 IEEE.

关键词： Markov processes

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International conference on VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded systems, VSPICE-2022

International Conference on VLSI, Signal Processing, Power E...

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International conference on VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded systems, VSPICE-2022

ISBN: (纸本)9789819944439

The proceedings contain 25 papers. The special focus in this conference is on . The topics include: Denoising of ECG Signal Using Optimized iiR Filter Architecture—A CSD-Based Design;deep Learning Analysis for Skin Cancer Detection;Design and Development of a BCI Framework to control a UTM Using EEG Headset;approximate Compressors-Based Multiplier for Image Processing and Neuromorphic Modeling;integration of Particle Swarm Optimization and Sliding Mode control: A Comprehensive Review;design and Testing of a Solar Powered Automated Fruit and Vegetable Sorter;characterization of Dust Particles and Their Impact on the performance of Photovoltaic Panels: A Laboratory Investigation;Design and Analysis of DC-DC Boost Converter;energy Management Analysis on Smart Street Lighting for Smart Cities;design and Implementation of Smart Waste Management System;Design and Development of Efficient Feeding network Structure for Patch Antenna Array Modules in UAV Communication Applications;E—RiCoBiT—ii: A High Performing RiCoBiT (Ring Connected Binary Tree) Topology with Fully Adaptive Routing Algorithm;Design and Development of Autonomous VTOL for Medicine Deliveries in Hilly Areas;Implementation and Design of Agile and Multipurpose Autonomous Robot Using ROS;prediction of Chronic Pain Onset in Patients Experiencing Tonic Pain: A Survey;design and Analysis of Miniaturized Broadband Microstrip Patch Antenna for Aircraft Surveillance Applications;Multiplier Design for the Modulo Set {2n- 1, 2n, 2n+1- 1 } and Its Application in DCT for HEVC;Modelling performance Analysis in VLSI Testing Methodologies;Verification of AHB2APB Bridge Protocol Using UVM;Design and Verification of AMBA AHB Protocol Using UVM.

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Wearable Physiological IoT System with Neural network to Detect an Individual IT Professional's Stress / Emotion in Working Environments 7

Wearable Physiological IoT System with Neural Network to Det...

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7th International conference on Intelligent Computing and control systems, ICICCS 2023

作者： Devi, V.Anusuya Pradeepaj, T.Sam Achyuth, N.Sai Nagarajan, R. Raj, R.Rahul Krishna, B.Navneetha School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankovil India

ISBN: (纸本)9798350397253

Stress in the workplace has a major impact on people's lives. IT industries are pushing the boundaries by introducing cutting-edge technologies and products but the high levels of stress among IT professionals remains as a concerning issue. Research has shown that stress can have an adverse effect on cognitive performance and physical health. This research study presents a novel neural network based wearable physiological IoT system to detect the stress and emotion levels of individual IT professionals in working environments. The proposed system is composed of a wearable device, mobile application, and neural network. The wearable device is equipped with three physiological sensors, namely heart rate, skin temperature, and electromyography (EMG) sensor. The mobile application collects the sensed data from the wearable device and then sends it to the neural network for analysis. The neural network is designed to detect the individual's stress and emotion levels based on the sensed physiological data. In addition, the mobile application provides the user with visual feedback and can be used to set goals and track progress. The proposed system is evaluated through a user study in an IT professional work environment. The results show that the system has the capability to detect the individual's stress and emotion levels with an accuracy rate of 91.6%. In order to minimize the potential risks of stress and its related effects, it is important to recognize these emotions and take appropriate steps to alleviate them. This work presents a system that can detect stress using facial analysis, a pulse oximeter, and temperature sensors. A camera is used to capture the person's front view. The proposed system utilizes a Convolutional Neural network (CNN) Algorithm to analyze an individual's facial expression in an image frame and determine their stress level. A prototype was developed to detect if someone is under stress based on their heart rate and blood pressure variations.

关键词： internet of things

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