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检索条件"任意字段=3rd IEEE International Conference on Distributed Computing in Sensor Systems"

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Survey on deadlocks in distributed database systems 3

Survey on deadlocks in distributed database systems

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3rd international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

作者： Bhavani, Y. Kumar, K. Praveen Dharmateja, K. Pranathi, P. Sowmya, R. Kakatiya Institute of Technology Science Dept. of IT Warangal India

ISBN: (纸本)9780738111834

In distributed Database System (DBS) and multitasking system, the occurrence of deadlocks is one of the most serious problems. If a site request for a resource that is already in the another site which is waiting for another resource then the scenario is called as distributed deadlock. Different distributed environments require a suitable deadlock detection algorithm to detect deadlocks. Different distributed environments needs to maintain their platforms by avoiding deadlocks. To achieve this environment, it is required to fed with optimized deadlock detection and avoidance algorithms. In this article, different deadlock detection algorithms that uses Wait For Graph and resolution algorithms to trace out deadlocks were discussed. An optimization technique is used for resolving deadlock in an efficient manner. A comparison between different deadlock detection algorithms based on different parameters like, delay time, message size, number of messages and whether the algorithm detects false deadlocks or not were performed. Based on the comparisons, a few deadlock detection algorithms were suggested for the distributed environment. © 2021 ieee.

关键词： distributed database systems

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BeeMind AI: Development of an Artificial Intelligence-Based System to Assess Honeybee Health, Behavior, and Nutrient Effects

BeeMind AI: Development of an Artificial Intelligence-Based ...

引用

computing and Machine Intelligence (ICMI), international conference on

作者： Matthew Lo The Haverford School

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

This research proposed and built the first integrated AI-based honeybee health assessment system called BeeMind AI. The BeeMind AI system had eight sensors including a microphone, temperature and humidity, carbon dioxide, atmospheric pressure, and camera, which enabled BeeMind AI to monitor both in-hive and external conditions. BeeMind AI has several diverse applications due to its ability to analyze honeybee movement and behavioral patterns to determine honeybee health, and it was used to evaluate the effects of four nutrients on honeybee health through video analysis in two experimental settings, one in a newly designed tri-chambered maze based on a Delayed Matching-to-Sample procedure, and another in a free-flying homing paradigm. The free-flying experiment was conducted to study the effect of nutrients on return rates of honeybees at distances of 300 m, 500 m, and 800 m, and it was found that the base return rates of the control group even at 800 m was close to 75%. It was observed for the first time that C60 nanoparticles had significant positive effects on learning, memory, and flying capabilities, improving return rates by around 9% at 300 m, 16% at 500 m, and 20% at 800 m, while neonicotinoid pesticides had negative effects on return rates, reducing them significantly by up to 30%. The developed BeeMind AI system has a significant impact on honeybee-related research, especially in the evaluation of honeybee learning and memory.

关键词： Temperature sensors Nanoparticles Temperature measurement Symbols Pesticides Nutrients sensor systems

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Development and Implementation of an Adaptive Overcurrent Protection Algorithm for a Modern Power Distribution Network 3

Development and Implementation of an Adaptive Overcurrent Pr...

引用

3rd ieee international conference on Energy, Power and Environment - Towards Clean Energy Technologies (ICEPE)

作者： Chandraratne, C. Naayagi, R. T. Panda, Gayadhar Newcastle Univ Sch EEE Singapore Singapore Natl Inst Technol Dept Elect Engn Shillong Meghalaya India

ISBN: (纸本)9781665425360

There has been a prediction for the future power system that penetration of distributed generators (DG) to be high. One of the challenges for the modern power system is a protection issue when DGs are connected. The level of fault current is dependent on the sources of the main power grid. However, when the DGs are connected to the distribution system, there is a change in the fault current. Therefore, the setting of protection coordination varies which leads to maloperation of the distribution network. It is not effective to use the traditional overcurrent protection as it is fixed to one value. Therefore, the proposed solution for this problem is to employ adaptive overcurrent protection. The advantage of this protection is that it adapts to real-time changes automatically and isolation of the fault is faster. In this paper, an algorithm is proposed based on which adaptive overcurrent protection relay works. This algorithm is verified by using a circuit system with three different types of test systems. All the simulation studies are carried out via Electrical Transient and Analysis Program (ETAP) software environment.

关键词： Adaptive Overcurrent Protection distributed Generators (DG) Digital Relay Distribution Network

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Research on Reactive Power Impact and Optimization of Photovoltaic Power Distribution Network Based on the Concept of Power Flow Direction Change

Research on Reactive Power Impact and Optimization of Photov...

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Power Electronics, Computer Applications (ICPECA), ieee international conference on

作者： Lintao Yuan Zhen Liu Daoyu Li School of Electrical Engineering Shandong University Jinan China

With the development of the national economy, the distribution network equipment has been continuously upgraded and the operation level has been continuously improved, and the distribution network has gradually developed in the direction of automation, forming an active distribution network with high penetration, high reliability and self-healing rate of distributed power sources. However, the large-scale access of distributed photovoltaics in the active distribution network often leads to problems such as voltage fluctuation, harmonic over-limit and power factor reduction in the distribution network, which has a great impact on the power supply quality of the distribution network. Among them, the reduction of the power factor of the distribution network will lead to an increase in line loss, a decrease in voltage, and a decrease in equipment utilization, which is extremely detrimental to the power quality of the public grid. Based on the actual situation and operation data of distributed photovoltaic in distribution network of XC District, a city in Shandong Province, this paper conducts a practical study on the impact, causes and improvement measures of low-voltage distributed photovoltaic reactive power in active distribution network. Firstly, according to the actual operation of distribution network, the concept of transformer power flow direction change point (stage) is proposed. Then, based on the concept of transformer power flow direction change point (stage), this paper studied the impact of public transformer distributed photovoltaic access on power factor using a large number of operating data, and deeply analyzed the reasons for the reduction of power factor of public transformer connected to distributed photovoltaic through vector method, and then proposed a transformer refined reactive power compensation scheme based on intelligent fusion terminal of distribution transformer. Finally, this paper proved the correctness and scientificity of the research

关键词： Photovoltaic systems Reactive power Voltage fluctuations Power quality Urban areas distributed databases Distribution networks

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Remaining useful life prediction of multi-sensor monitored degradation systems with health indicator 3

Remaining useful life prediction of multi-sensor monitored d...

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3rd international conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Huang, Xucong Peng, Zhaoqin Tang, Diyin Zheng, Zaiping Chen, Juan School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Insititue of Precise Mechatronics and Controls Laboratory of Aerospace Servo Actuation and Transmission Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China

ISBN: (纸本)9781665492812

Rolling bearings are kernel components of machinery devices. To evaluate degradation processes of rolling bears in real-time devices, health indicators (HIs) are required to be built. Due to the constraints of sensors, the degradation pattern cannot be denoted by commonly used signals such as vibration data. Moreover, the practical requirements of HI for prognostics are always ignored, such as monotonicity and trendability. Therefore, a novel HI construction method based on reinforcement learning (RL) is proposed. Firstly, the HI construction process is regarded a data fusion process. Observed multi-sensor data is used to abstract degradation information. In this way, the determination of HI is changed into the optimization of fusion coefficient vector. Secondly, a RL agent is established to automatically learn the strategy though the intergradation with environment. Then the trained strategy is directly used for real-time HI construction. The effectiveness of proposed approach is verified though a real bearing dataset. © 2022 ieee.

关键词： data fusion HI construction reinforcement learning RUL

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distributed Network Carbon Emission Forecasting Based on Adaptive Graph Convolutional Recurrent Neural Networks

Distributed Network Carbon Emission Forecasting Based on Ada...

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Power systems and Electrical Technology (PSET), ieee international conference on

作者： Binxie Ren Pengfei Zhao Shi Jing Zhenyuan Zhang Ying Liu Zheng Wang School of Mechanical and Electrical Engineering the University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350353204

ISBN: (纸本)9798350353211

Achieving carbon peak and carbon neutrality is a critical goal for sustainable development worldwide. Accurate carbon emission forecasting plays an important role in carbon trading and low-carbon management in distributed systems. This paper proposes a carbon emission forecasting method based on an Adaptive Graph Convolutional Recurrent Network (AGCRN), it features two distinct modules designed for adaptive graph learning: one module adjusts node parameters adaptively, while the other module creates data-specific graphs. The node adaptive parameter learning module captures node-specific patterns in the carbon emission sequences of each power grid node, while the data-adaptive graph generation module infers the spatial correlations between the carbon emission flows of different nodes in the power grid. To evaluate the accuracy and performance of the proposed model, we compared it with two popular forecasting methods. The results demonstrate that the proposed method can achieve more accurate carbon emission predictions than other baselines.

关键词： Adaptation models Adaptive systems Correlation Accuracy Carbon dioxide Predictive models Power grids Data models Topology Forecasting

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What We Know About HTTP/3 and Its Implementation: A Literature Review

What We Know About HTTP/3 and Its Implementation: A Literatu...

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computing and Machine Intelligence (ICMI), international conference on

作者： Jacob Koch Olufunsho Falowo Nathan Elrod School of Information Technology University of Cincinnati Cincinnati United States

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

HTTP is the backbone of modern web communication. With the rapid growth of web architecture and web communication, it has led to the need for a development of new versions of the HTTP protocol to address performance, security, and communication issues that currently exist. HTTP/3 is a new protocol proposed in 2022 and recently accepted. This paper aims to examine its integration with the QUIC protocol, a UDP-based alternative to traditional TCP-based HTTP versions. HTTP/3 addresses several limitations of previous versions, such as head-of-line blocking, by using QUIC and UDP for traffic communication. This helps HTTP/3 to provide a more responsive and fault-tolerant connection. Despite its benefits, HTTP/3 faces several challenges, including application support for UDP traffic and a potential susceptibility to distributed Denial of Service (DDoS) attacks. Often in literature however, HTTP/3 and QUIC are conflated as the same thing due to their novel nature. Through a systematic literature review, this study seeks to answer three key research questions. First, how does HTTP/3 integrate the QUIC protocol, and what are the key differences between HTTP/3 and traditional TCP-based HTTP versions? Second, which specific features and enhancements in HTTP/3 address the performance and security issues found in previous HTTP versions? The final question is, “How has HTTP/3 been deployed to solve challenges in cloud, IoT, and web environments and what opportunities does it afford? By addressing these questions, this paper will provide a clearer understanding of HTTP/3's architecture, its relationship with QUIC, and its implications for web, IoT, and cloud system architecture.

关键词： Transport protocols Protocols Bibliographies Focusing systems architecture Telecommunication traffic HTTP

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A TDMA Algorithm for Dual-Hop Energy Harvesting Wireless sensor Networks

A TDMA Algorithm for Dual-Hop Energy Harvesting Wireless Sen...

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computing and Machine Intelligence (ICMI), international conference on

作者： Tanner D. Patterson Robert J. Hayek Ahmed Ammar ECCS Dept. Ohio Northern University Ada Ohio USA ECE Dept. Northwestern University Evanston Illinois USA

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

In this paper, we propose a time division multiple access (TDMA) algorithm and system for a dual-hop energy harvesting wireless sensor network. We assume that the network is divided into clusters, where each cluster has a cluster head and cluster members. A cluster head collects data from its respective cluster members and then transmits the data in one packet to the base station. The proposed algorithm first synchronizes the network and then enables each node to transmit over its designated time slot. The proposed algorithm allows each node to synchronize not only based on a synchronization packet from the base station, but also based on a data packet from another node that is within its communication range. Moreover, the proposed algorithm synchronizes clusters individually, i.e., if a cluster becomes out-of-sync, the algorithm only synchronizes that cluster while allowing the remaining clusters to continue normal operation. The proposed algorithm works also for single-hop networks, and achieves network synchronization without the need for acknowledgment packets, which reduces the average energy consumption and average delay by approximately 1.36 and 1.46 times, respectively, compared to the most recent single-hop algorithm.

关键词： Time division multiple access Wireless sensor networks Base stations Energy consumption Clustering algorithms Approximation algorithms Partitioning algorithms

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LSTM based Soft-sensor for Estimating Nitrate Concentration in Aquaponics pond

LSTM based Soft-Sensor for Estimating Nitrate Concentration ...

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Innovation in Technology (INOCON), ieee international conference for

作者： A. Dharshan Purushottam Kumar S. Ravimaran U Srinivasulu Reddy Department of Artificial Intelligence and Data Science Saranathan College of Engineering Trichy India CoE in Artificial Intelligence Machine Learning & Data Analytics Lab National Institute of Technology Trichy India Department of Computer Applications Machine Learning & Data Analytics Lab National Institute of Technology Trichy India

In the field of aquaponics, where fish and plants coexist in a symbiotic environment, closely monitoring nitrate levels in the water is crucial due to their profound impact on aquatic and plant well-being. Traditional nitrate measurement methods are often time-consuming and costly. Various approaches, including first principles, IoT-based sensors, and machine learning-based soft sensors, have been attempted to address this challenge. However, these efforts face challenges such as expensive sensors, infrequent data collection, multistage data processing using limited sensor types, and the need for regular maintenance like cleaning and calibration. Additionally, varied environmental conditions affect sensor suitability for different water environments, and even some machine learning-based soft sensors have proven inaccurate. In response, soft sensors, especially deep learning-based ones, have gained prominence in industrial applications for their adaptability and accuracy. These sensors provide real-time insights into complex processes without requiring expensive hardware. In this study, an innovative solution was introduced using Long Short-Term Memory (LSTM) technology, a neural network architecture in deep learning known for capturing complex temporal patterns. LSTM is well-suited for modeling and predicting nitrate concentration changes in aquaponics, trained with extensive data collected from various aquaponic ponds. Through rigorous evaluation, a remarkable MSE value of 0.00074 and an impressive R-squared score of 0.98 were achieved, holding potential for scaling up to commercial applications, benefiting aquaponics operations, supporting researchers, and enhancing sustainability and productivity in aquaponic systems.

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Automatic Finite Deterministic Algorithm and PSO Based Secured Energy Efficient Routing in Wireless sensor Network 3

Automatic Finite Deterministic Algorithm and PSO Based Secur...

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3rd international conference on Advances in computing, Communication Control and Networking, ICAC3N 2021

作者： Shah, Priyanka Kasbe, Tanmay Oriental University Department of Computer Science Madhya Pradesh Indore India

ISBN: (纸本)9781665438117

Economic sensor networks have always been a boon to disaster management applications due to their ease of setup. Communication is difficult for them due of their vulnerability to a variety of security dangers. This study presents a new routing strategy those guards against both external and internal threats such as hello flooding, eavesdropping, and wormhole attacks. To limit energy dissipation, this method employs a one-way hash chain. Event-driven clustering at the level also saves energy. The suggested technique extends network longevity even when the cluster-based wireless sensor network is under attack, according to simulated results. A 5G wireless sensor network (WSN) is a collection of self-contained nodes that monitor the environment. WSN design goals like as energy efficiency or secure data transmission are primarily measured. With the increasing difficulties of workstation networks, network-based attacks have drawn the attention of various academics from various domains. As a result, multiple intrusion detection systems (IDS) have been built to address various areas of complicated security, such as denial-of-service attacks, worms, viruses, malware, and so on. IDS automation has been designed to safely restore the realization of energy-efficient routing in wireless sensor networks. Intrusion detection and data transmission performed in a secure manner using automatic finite deterministic and particle swarm optimization (PSO) algorithms that determine and follow an optimum path. Routing along the optimal path can restore the overall appearance of a sensor network in wireless technology, and it can be managed using a variety of indicators (such as power expenditure, capacity, network life, active nodes and dead nodes). The threat model and safety objectives for secure routing in wireless networks are discussed in this paper. The simulation was carried out using the MATLAB simulation software. © 2021 ieee.

关键词： Intrusion detection

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