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Binary-Encoding-Based Quantized Kalman Filter: An Approximate MMSE Approach

IEEE Transactions on Automatic Control 2025年第5期70卷 3181-3196页

作者： Liu, Qinyuan Nie, Yao Wang, Zidong Dong, Hongli Jiang, Changjun Tongji University School of Computer Science and Technology Shanghai201804 China Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai201804 China Tongji University Shanghai Artificial Intelligence Laboratory Shanghai201804 China Brunel University London Department of Computer Science UxbridgeUB8 3PH United Kingdom Northeast Petroleum University Artificial Intelligence Energy Research Institute Daqing163318 China Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Daqing163318 China

In this article, the Kalman filter design problem is investigated for linear discrete-time systems under binary encoding schemes. Under such a scheme, the local information is quantized into a bit string by the remote sensor based on a probabilistic quantizer, and then the bit string is transmitted via memoryless binary symmetric channels (BSCs). Due to the communication link noises, the bit flipping occurs in a random manner, and thus, the transmission of the bit string would suffer from specific bit-error rates. With the received bits, a recursive binary-encoding-based quantized Kalman filter is established in the approximate minimum mean-square error (MMSE) sense, which relies on the Gaussian approximation of the conditional probability density function at each iteration. Furthermore, the proposed estimator is shown to be of a Kalman-like type through performance analysis, which exhibits computational complexity comparable to the conventional Kalman filter. Subsequently, a posterior Cramér-Rao lower bound is derived for the proposed binary-encoding-based quantized Kalman filter. The effectiveness of the proposed estimator is demonstrated through numerical results. © 1963-2012 IEEE.

关键词： Mean square error

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SatCooper: Enhancing Cooperative Inference Analytics for Satellite Service via Multi-exit DNNs

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IEEE Transactions on Mobile Computing 2025年

作者： Zhang, Qiyang Wang, Shangguang Guan, Jinglong Donta, Praveen Kumar Ma, Xiao Prasad, RangaRao Venkatesha Dustdar, Schahram Liu, Xuanzhe Peking University School of Computer Science Beijing100871 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China Stockholm University Department of Computer and Systems Sciences Kista16455 Sweden Beiyou Shenzhen Institute Shenzhen China Netherlands TU Wien Distributed System Group Wien1040 Austria UPF Barcelona Spain

As a key technology of intelligent satellite-enabled services in B5G or 6G networks, deploying Deep Neural Networks (DNN) models on satellites has been a notable trend, catering to the daily demand for extensive computing-intensive and latency-sensitive tasks. The computing resources are strategically deployed on satellites where sensor data is generated or collected, facilitating the fine-grained computational inference of DNN-based tasks. However, no prior study has comprehensively explored the crucial inference challenges-e.g., the trade-off between the number of tasks completed and accuracy and partitioning models in multi-exit models-in the resource-constrained space environment. Effective scheduling frameworks cater to various streams of inference tasks are scarce because inference performance may deviate from the ideal situation due to changes in task system status, such as task profiles and network state. To this end, we first formulate a gain-aware in-orbit computing inference problem to strike a proper trade-off between inference latency and the number of tasks completed by dynamically selecting optimal early exit points and model partitioning points. We propose an offline dynamic programming-based algorithm that provides an effective solution when comprehensive system details are to be predicted. We have developed an online learning-based method to schedule inference tasks with uncertain and dynamic system statuses in real-world situations. Our evaluation shows that, compared to baseline methods, the online learning-based algorithm can improve task gain by an average of 87.3% across various tasks. © 2002-2012 IEEE.

关键词： Dynamic programming

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IoT-Based Transmission Tower Monitoring Communications and Visualization Platform 6

IoT-Based Transmission Tower Monitoring Communications and V...

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6th IEEE Symposium on Future Telecommunication Technologies, SOFTT 2022

作者： Mohd Alias, Mohamad Razin Naim Mohd Dzaki, Dzahir Rashidi Din, Norashidah Md Deros, Siti Noratiqah Mohd Passarella, Rossi Amier Chaai, Azzam Eusuf Chaai Malaysia Universitas Sriwijaya Computer Networking and Information System Faculty of Computer Science Department Palembang Indonesia Malaysia

ISBN: (纸本)9781665455978

Transmission tower fault monitoring has always been a challenge for power system engineers. Vertical and horizontal displacement monitoring is important for evaluating health status of transmission tower's infrastructures. Quick fault detection can help protect the equipment by allowing the disconnection of transmission tower before any significant damage of the equipment. The purpose of this study is to propose an IoT monitoring system for transmission towers. The monitoring system adheres to Three-Layer IoT architecture. In the perception layer, sensors MPU6050 and Anemometer are used to measure a specific parameter. The data, which includes the Roll, Pitch, Yaw, and wind velocity, is gathered and delivered to the ESP32 through network layer using WiFi, which then stored the information in the cloud using InfluxDB. For visualization purposes in the application layer, Grafana is utilized which is hosted in the web dashboard and the mobile application. Flutter framework is used to develop the mobile application. An alert will be displayed in the mobile application when the threshold of the wind speed exceeds 10m/s. © 2022 IEEE.

关键词： Wind

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An Optimal Distribution of RSU for Improving Self-Driving Vehicle Connectivity

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computers, Materials & Continua 2022年第2期70卷 3311-3319页

作者： Khattab Alheeti Abdulkareem Alaloosy Haitham Khalaf Abdulkareem Alzahrani Duaa Al_Dosary Department of Computer Networking System College of Computer Sciences and Information TechnologyUniversity of AnbarRamadiIraq College of Medicine University of AnbarRamadiIraq Department of Computer Science Faculty of Computer Science and Information TechnologyAlbaha UniversityAlbahaSaudi Arabia College of Computer Sciences and Information Technology University of AnbarRamadiIraq

Self-driving and semi-self-driving cars play an important role in our daily *** effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital ***,external infrastructures also play significant roles in the transmission and reception of control data,cooperative awareness messages,and caution *** this case,roadside units are considered one of themost important communication *** distribution of these infrastructures will overburden the spread of self-driving vehicles in terms of cost,bandwidth,connectivity,and radio coverage *** this paper,a new distributed roadside unit is proposed to enhance the performance and connectivity of these ***,this approach is based primarily on k-means to find the optimal location of each roadside *** addition,this approach supports dynamicmobility with a long period of connectivity for each ***,this system can adapt to various locations(e.g.,highways,rural areas,urban environments).The simulation results of the proposed system are reflected in its efficiency and ***,the system can achieve a high connectivity rate with a low error rate while reducing costs.

关键词： Self-driving cars roadside unit autonomous vehicles distributed systems connectivity

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Effects of Impulse Noise on Massive MIMO

Effects of Impulse Noise on Massive MIMO

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2019 Imam Al-Kadhum International Conference for Modern Applications of Information and Communication Technology, MAICT 2019

作者： Dawod, Adnan Yousif Abdulqader, Mohammed Fakhrulddin Hameed, Saif Saad University of Kirkuk Iraq Department of Computer Networking System Faculty of Computer Science and Information Technology University of Anbar Iraq

The usage range of nowadays wireless communications become wide, all of the develop applications uses wireless communication which improve the mobility and improve the mobility of the network subscribers. As known that the antenna diversity scheme developed from "SISO" to "MIMO" that has a maximum capacity and ability to improve the communication quality with a good shields among the fading effects and other impairments. In this research work study and analysis to the antenna systems and antenna schemes was done taking into consideration the central antenna system and the distributed antenna system "CAS" and "DAS". A Matlab simulation was developed to test antenna configuration system in term of effeteness of fading channel while using different modulation order. © Published under licence by IOP Publishing Ltd.

关键词： Impulse noise

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Investigate SPRON Convergence Time Using Aggressive Chord and Aggressive AP-Chord 12

Investigate SPRON Convergence Time Using Aggressive Chord an...

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12th International Conference on Information Technology: New Generations, ITNG 2015

作者： Min, Chin Teck Ming, Lim Tong Department of Computer Science and Networking Sunway University Selangor Malaysia Department of Information System Sunway University Selangor Malaysia

ISBN: (纸本)9781479988273

Private overlay network is a network that consists of groups of known peers that have been accepted as members. SPRON is the proposed private reappearing overlay network that will be used by schools in Malaysia to solve the distribution and sharing issues of teaching material among them. There are about nine thousand schools in Malaysia and these schools are grouped into morning only, evening only, and morning evening sessions. Peers bootstrap and reappear in a reappearing overlay network could cause maintenance overhead. One of the challenges of this research is that the P2P must be bootstrapped within a short period of time before school session starts. The convergence time for SPRON P2P must be able to converge within the time constraint to be usable and implementable in schools. The study of the network convergence time in aggressive Chord and aggressive Chord with Anchor Peers (AP-Chord) were carried out to ensure bootstrapping time for all the peers can converge into a fully connected overlay network within specific amount of time. Our study shows that the performance of aggressive Chord and aggressive AP-Chord are able to bootstrap 3000 peers that take about 1090s and 1050s seconds respectively using random join rate which clearly shown AP-Chord performs with lot of improvement. If peer joining rate is fixed at 1000 peers per second or higher, both Chords did not guarantee that all the peers are able to join the network entirely in the bootstrapping phase. The outcomes of this study are AP-Chord have the capability to bootstrap 3000 or possibly more with aggressive join in considerably shorter period of time fulfilling the time constraint. © 2015 IEEE.

关键词： Overlay networks

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Automatic Features Extraction Using Autoencoder in Intrusion Detection system

Automatic Features Extraction Using Autoencoder in Intrusion...

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2018 International Conference on Electrical Engineering and computer Science, ICECOS 2018

作者： Kunang, Yesi Novaria Nurmaini, Siti Stiawan, Deris Zarkasi, Ahmad Jasmir, Firdaus Intelligent System Research Group Faculty of Computer Science Department Universitas Sriwijaya Palembang Indonesia Computer Networking Information System Faculty of Computer Science Departement Universitas Sriwijaya Palembang Indonesia

ISBN: (纸本)9781538657201

Intrusion Detection system (IDS) can detect attacks by analysing the patterns of data traffic in the network. With a large amount of data that is processed in the IDS, then need to do a feature extraction to reduce the computational cost of processing raw data in IDS. Feature extraction will transform features to the lower dimension to accelerate the learning process and improve the accuracy. This research on automatic feature extraction using simple autoencoder and SVM to classify attacks on IDS. We use various functions activation and loss to see how far this feature extraction feature can improve accuracy. We use Datasets KDD Cup' 99 NSL-KDD and to evaluate the effectiveness of the mechanisms of detection after extraction features process. In the proposed model, the activation functions autoencoder hyperparameter ReLU activation and loss function cross-entropy gives best accuracy value than other functions. © 2018 IEEE.

关键词： Feature extraction

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The impact of Routing Protocols and topologies on IOT Based systems 2

The impact of Routing Protocols and topologies on IOT Based ...

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2nd International Conference of Modern Applications on Information and Communication Technology, ICMAICT 2020

作者： Hameed, Saif Saad Saleh, Hadeel Mohammed University of Anbar College of Computer Science and Information Technology Department of Computer Networking System Iraq University of Anbar College of Pharmacy Iraq

Routing protocols is a mechanism of detecting best route path from single node to multiple nodes or signal node in order to transfer data between network and it specify how routing techniques in routers communicate between routers to accomplish communication tasks. A simulation was done to compare some protocols such as ""RIP"", ""OSPF""and "EIGRB' to determine the best routing protocol at a specific given network topology for IoT applications. The main problem there is a different routing protocols was developed each has its performance among different IoT applications. As well a simulation was required to detect the perfect routing protocol required for IoT applications. In this project a simulation of "IoT"network that serve the "IoT"applications using different routing protocols such as ""RIP"", ""OSPF"' and "EIGRB"and an evaluation to the performance of each routing technique was to decide which is the best routing for "IoT"applications. Opnet modular was used to implement the simulation and it is found that the ""IGRP""has the fastest router convergence among the three protocols we are testing. © Published under licence by IOP Publishing Ltd.

关键词： Routing protocols

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Deep Learning Model for IDS in the Internet of Things 7

Deep Learning Model for IDS in the Internet of Things

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7th International Conference on Contemporary Information Technology and Mathematics, ICCITM 2021

作者： Mohammed, Maha Majed Alheeti, Khattab M. Ali College of Computer and Information Technology University of Anbar Computer Sciences Department Anbar Iraq University of Anbar College of Computer and Information Technology Computer Networking System Department Anbar Iraq

ISBN: (纸本)9781665420327

Emerging technology makes one's life more comfortable;however, in the Internet of Things, there are a lot of weaknesses like infrastructure, connectivity, network, etc, due to the presence of millions of networked devices that make it difficult to implement safety on each device. Security threats are one of the most important issues recently gaining popularity in IoT, attacks that can cause major disruptions and loss of information within the IoT network. Intrusion Detection system (IDS) has a substantial role in protecting and securing an IoT network through detecting and preventing malicious activities. To develop IDS for timely detection and categorization of cyber threats at the network level, classical machine learning techniques are commonly utilized. However, because malicious attacks are continuously evolving and occurring at extremely large sizes, various problems arise, necessitating a scalable solution. In this paper, a convolutional neural network (CNN) approach, which is a kind of deep learning model for IDS discovery, is developed that is flexible and efficient for detecting and classifying cyber-Attacks in IoT networks. The well-Applied CNN model on the UNSW-NB15 dataset obtained 100% precision results. © 2021 IEEE.

关键词： Internet of things

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A Real-Time Acceleration-Based Frailty Detection system for Elderly Care 17

A Real-Time Acceleration-Based Frailty Detection System for ...

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17th International Convention on Rehabilitation Engineering and Assistive Technology, i-CREATe 2024

作者： Sansrimahachai, Watsawee Toachoodee, Manachai Khemapech, Ittipong School of Science and Technology University of the Thai Chamber of Commerce System and Networking Group Computer Science Department Bangkok Thailand University of the Thai Chamber of Commerce System and Networking Group School of Science and Technology Bangkok Thailand

ISBN: (纸本)9798350355154

Over the past decade, almost all countries in the world have experiencing growth in both the size and the proportion of elderly people in the population. The number of world's aging population is expected to reach about 2.1 billion by 2050, which is more than double figure from 1 billion in 2020. This statistic indicates the fact that we are entering the era of 'super-aged society'. One of the major problems in the elderly comes in the form of a decline in health and physical function, generally called Frailty. The elderly with frailty typically suffer several health issues including loss of muscle mass, poor gait and balance and cognitive impairment. They are higher risk of falls and quick progression to dependency. Early identification of frailty is required to effectively reduce and prevent frailty outcomes. To address the problem, we propose a frailty detection system that can remotely analyze gait characteristics and detect frailty among elderly individuals in real-time. Our system utilizes an Ultra-wideband tag attached to the body of the elderly as a data collection device. It applies data stream mining techniques that perform machine learning-based gait analysis and detect frailty based on the patterns of acceleration data. The experimental result indicates that our proposed frailty detection system is practical to be used in real-world settings with relatively high accuracy rate, about 81.8% for overall accuracy. © 2024 IEEE.

关键词： Frailty Detection Gait Analysis Stream Mining

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