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Constructing a Fine-Grained Mapping Algorithm for Blocks and Rack-Mounted Storage Nodes

Constructing a Fine-Grained Mapping Algorithm for Blocks and...

引用

Frontiers Technology of Information and Computer (ICFTIC), ieee international conference on

作者： Juanjuan Zhang Yuheng Li Bing Wei School of Cyberspace Security (School of Cryptology) Hainan University Haikou China Key Laboratory of Internet Information Retrieval of Hainan Province Haikou China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

In a heterogeneous encoding environment, cloud storage systems face a series of challenges caused by frequent data repairs, including the imbalance of erasure coding data transmission, the uneven read load of data racks and nodes, and the high overhead of data repair that results from these issues. this paper aims to address the key problems in cloud storage systems based on erasure coding technology: how to reduce storage costs while ensuring data reliability, and improve the overall system performance and high fault tolerance of the data. this study first proposes a Fine-Grained Mapping Algorithm (FEM) for blocks and storage nodes on racks, which can achieve precise mapping between blocks and storage nodes. the aim is to balance the load of storage nodes and racks simultaneously, accelerate the data repair process, avoid load imbalance caused by the repair program reading different numbers of blocks from different storage nodes, balance the network resource differences between storage nodes, and to some extent, ensure the security of data storage.

关键词： Fault tolerance Cloud computing Costs System performance Fault tolerant systems distributed databases Maintenance engineering Encoding Finite element analysis Faces

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distributed Photovoltaic Multi-point Access Distribution Network Station Area Capacity Planning

Distributed Photovoltaic Multi-point Access Distribution Net...

引用

Energy, Power and Grid (ICEPG), international conference on

作者： Jiaohui Shang Yongqing Li Yao Duan Hao Liu Mingle Yang Baiyin Power Supply Company State Grid Gansu Electric Power Company Baiyin China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

the massive quantity of distributed photovoltaic connections, will lead to a significant effect on the operation of the distribution station area. this paper presents a photovoltaic access capacity planning model and method for poverty alleviation photovoltaic access distribution network station area. A mathematical model with the goal of maximum photovoltaic access capacity is constructed, and the constraint conditions of node voltage, and line power flow, are optimized in the model by combining with the particle swarm optimization and penalty function. Taking the ieee33-node standard system as an example, the consequences exhibit that the approach can efficaciously calculate the distributed photovoltaic capacity and location that can be accessed by the distribution network, and analyze the impact on the voltage and network loss, which provides a reference for guiding the distributed photovoltaic poverty alleviation security.

关键词： Photovoltaic systems Voltage Distribution networks Mathematical models Security Resource management Particle swarm optimization Standards Capacity planning Load flow

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DPLE: A Privacy-Enhanced and Straggler-Resilient distributed Learning Framework for Smart Cloud

DPLE: A Privacy-Enhanced and Straggler-Resilient Distributed...

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ieee international conference on Smart Cloud (SmartCloud)

作者： Yilei Xue Jianhua Li Jun Wu School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350389500

ISBN: (纸本)9798350389517

distributed machine learning (DML) encounters issues related to privacy and the presence of straggling nodes in smart cloud systems. Lagrange coded computing offers a partial solution to mitigate these concerns. Nonetheless, the privacy of the system becomes vulnerable when the number of semi-trusted nodes surpasses a specific limit, or when external eavesdroppers are present. To confront this hurdle, we introduce a novel framework for distributed learning called DPLE (Differentially Private Lagrange Encoding). this framework employs Lagrange interpolation polynomials to obscure the original data while introducing redundancy, thus improving privacy safeguards and increasing robustness to straggling nodes. It also incorporates artificial noise into local computation outcomes to protect confidential data from potential exposures. Furthermore, we perform theoretical analyses to identify the necessary variance of this noise to maintain desired privacy levels. Experimental validations confirm the efficacy of DPLE and examine how different settings of system parameters impact the accuracies of the results.

关键词： Wireless communication Training Privacy Interpolation Wireless sensor networks Data privacy Distance learning

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Optimal Design of Heliostat Field Using Random Search Algorithm

Optimal Design of Heliostat Field Using Random Search Algori...

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ieee international conference on Power, Intelligent computing and systems (ICPICS)

作者： Chenglin Mou Kaiqi Wu Pengcheng Du Kaibo Yang Department of Engineering Mechanics School of Civil Engineering and Architecture Henan University of Science and Technology Luoyang China Department of Computer Science and Technology School of Information Engineering Henan University of Science and Technology Luoyang China Department of Automation School of Information Engineering Henan University of Science and Technology Luoyang China Department of Civil Engineering School of International Education Henan University of Science and Technology Luoyang China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

Tower solar thermal power generation is a new type of low-carbon and environmentally friendly clean energy technology. In this paper, a single-objective optimization model is established with the maximum annual average thermal output per unit mirror area of the heliostat field as the objective function. By optimizing the heliostat width, heliostat height and heliostat coordinate, the annual average output thermal power can be maximized while meeting the rated power. the heliostat field is distributed in a circular shape. As the seasons change, the light intensity received by the heliostat field is uneven, so the optical efficiency of the heliostats is also different. We simplify the heliostat field into S area (area with higher optical efficiency) and W area (area with lower optical efficiency) based on the optical efficiency distribution of heliostats. At different locations, According to the heliostat width, heliostat height and heliostat coordinate generated by random functions, substituting these parameters into the efficiency model in this paper, and the random search algorithm is used to traverse the maximum annual output thermal power and the corresponding heliostat parameters. In the shadow occlusion loss model, we have grid to set up the heliostat and use the coordinate conversion to solve the shadow occlusion loss efficiency.

关键词： Integrated optics Green energy Shape Optimization models Computational modeling Poles and towers Linear programming Mirrors Power generation

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A New Model of Automatic Repowering Management Based on distributed Architecture

A New Model of Automatic Repowering Management Based on Dist...

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ieee international conference on Power and Energy Applications (ICPEA)

作者： Jiayi Li Guanheng Zhou Bo Xu Wenjun Qi Zhiying Zhong Xiaohui Fu Smart Grid Service Center Jiangsu Frontier Electric Power Technology Co. Ltd. Nanjing China

In order to closely implement the headquarters strategy of constructing excellent service engineering and continuously improving service efficiency proposed by State Grid, and comprehensively improve the time efficiency of users’ electricity consumption after payment of bills, based on intelligent electricity meters, and based on the active power restoration (automatic restoration after tripping) function of remote fee-control electricity meters, and through the optimization and upgrading of the digitized business processes of the two sets of systems of electric power marketing and power consumption collection, the Company explored and constructed a new mode of power restoration management based on the distributed architecture and carried out a pilot application. By optimizing and upgrading the digital business processes of the two systems of power marketing and power consumption collection, we explore the construction of a new model of power restoration management based on distributed architecture and carry out pilot applications to realize the restoration of power delivery within 2 hours after the user pays the fee. this paper firstly analyzes the working principle of traditional power outage and restoration, and then introduces the new mode of management based on distributed architecture and the realization of business process transformation in the two systems. Finally, the application effectiveness potential of the new model is described and further research directions are proposed.

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An Intelli BEF: An Intelligent Bio-Inspired Energy-Efficient and Fault-Tolerant Routing for IoT-Enabled WSNs

An Intelli BEF: An Intelligent Bio-Inspired Energy-Efficient...

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： Satyanarayana Nimmala Maragoni Mahendar Pinnapureddy Manasa K Raghavendar Bandi Rambabu Dokku Durga Bhavani Department of CSE (Data Science) CVR College of Engineering Hyderabad India Department of CSE Neil Gogte Institute of Technology Hyderabad India Department of CSE Teegala Krishna ReddyEngineering College Hyderabad India Department of CSE CVR College of Engineering Hyderabad India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

In IoT-enabled Wireless sensor Networks (WSNs), effective energy utilization and fault tolerance are essential for extended network functionality and dependable data delivery. these networks, prevalent in applications ranging from environmental monitoring to smart cities, have difficulties stemming from sensor node failures caused by energy depletion or environmental interference. this study presents Intelli BEF, a bio-inspired, energy-efficient, and fault-tolerant routing protocol that improves WSN performance by intelligent optimization and fault detection. Intelli BEF utilizes Particle Swarm Optimization (PSO) to identify energy-efficient cluster heads (CHs), thereby optimizing energy consumption across nodes and extending the network's operating duration. A Convolutional Neural Network (CNN) classifier is utilized to identify defective nodes in real-time, facilitating efficient rerouting and minimizing data loss. Intelli BEF has shown substantial advancements compared to conventional protocols through comprehensive simulations, resulting in improved fault tolerance, heightened energy efficiency, and prolonged network longevity. this study emphasizes the promise of Intelli BEF for dependable and scalable applications in IoT-enabled wireless sensor networks (WSNs).

关键词： Wireless sensor networks Fault tolerance Smart cities Fault tolerant systems Routing Energy efficiency Routing protocols Real-time systems Convolutional neural networks Particle swarm optimization

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Reliability Measurement Of Vehicle sensor Data Based On Historical Perception

Reliability Measurement Of Vehicle Sensor Data Based On Hist...

引用

ieee international conference on Data Science in Cyberspace (DSC)

作者： Chenqing Guo Jinxin Zuo Yueming Lu Weixuan Xie School of Cyberspace Security Key Lab of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

On-board sensors are utilized for monitoring and collecting a diverse range of data pertaining to the vehicle and its surroundings. However, in the field of Internet of Vehicles, security threats encountered by vehicle sensors often result in compromised accuracy of collected data. therefore, it is crucial to investigate trusted measurement methods for vehicle sensor data. this paper proposes a reliable measurement approach for vehicle sensor data based on historical perception. the method initially achieves historical feature extraction through time correlation of single sensor sequence data and spatial correlation of multisensor data. Subsequently, a reliability measurement method is devised to quantify real-time data reliability by assessing the deviation from the theoretical expected value. Finally, historical data reliability is integrated with real-time data reliability to enhance accuracy of the overall reliability measurement process. this approach takes into consideration spatio-temporal correlation of vehicle sensor data and resolves issues stemming from unbalanced datasets that lead to inaccurate evaluation results. Experimental findings demonstrate an accuracy rate of 98.91% for the proposed method.

关键词： Correlation Accuracy Reliability theory Feature extraction Real-time systems Spatial databases sensors Security Monitoring Internet of Vehicles

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Evaluation of distributed Photovoltaic Admission Capacity in Distribution Grid Considering Uncertainty

Evaluation of Distributed Photovoltaic Admission Capacity in...

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Electrical Engineering and Control Technologies (CEECT), conference on

作者： Dian Shao Junqiu Fan College of Electrical Engineering Zhejiang University Hangzhou China State Grid Corporation of Guizhou Province Guiyang China

ISBN: (数字)9798331528096

ISBN: (纸本)9798331528102

Under the background of “Carbon peaking and carbon neutrality” goals, new energy is widely utilized, especially distributed photovoltaic. the large-scale integration of distributed PV into the distribution grid is a trend for the future distribution grid. therefore, the calculation of distributed PV admission capacity in the distribution grid is an important issue in distribution grid planning. this paper first establishes an output probability model based on the randomness and uncertainty of distributed PV and load output power. then handle the correlation between distributed PV and load. the constraints are constructed and added to the PV admission capacity calculation model, and the stochastic weighted particle swarm optimization algorithm is used for solving the model. Finally, the factors influencing the distributed PV admission capacity in an ieee 33-bus distribution grid are analyzed.

关键词： Photovoltaic systems Uncertainty Correlation Stochastic processes Market research Linear programming Large scale integration Planning Particle swarm optimization Load modeling

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Analysis of a 8-Year Field-Tested PV Module Deployed in a Subtropical Environment

Analysis of a 8-Year Field-Tested PV Module Deployed in a Su...

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Smart Power & Internet Energy systems (SPIES), international conference on

作者： Sukanta Roy Alexander Stevenson Milad Behnamfar Shanzeh Batool Arif Sarwat Department of Electrical and Computer Engineering Florida International University Miami FL USA School of Computing Science Vellore Institute of Technology Bhopal India

ISBN: (数字)9798350368864

ISBN: (纸本)9798350368871

distributed Energy Resource (DER) deployments continue to accelerate as the electric grid experiences the transformative shift to a decentralized renewable generation and distribution-based network. Photovoltaics (PV) systems in particular are an extremely attractive option for many residential and commercial owners towards electricity generation in densely populated urban areas. However, harsh environmental conditions can often accelerate the degradation of PV components which may lead to electrical issues, hazardous conditions for people and equipment, and decreases in their economic effectiveness. In this work, the failure modes and effects of PV modules are discussed as well as the inference of their effects on system reliability. Furthermore, a visual inspection and temperature analysis of a 315W solar PV module from a 8-year PV system deployed in the harsh subtropical environment of Miami, FL are performed. From these analyses, several insights on PV design are drawn at both the module and system level, and recommendations for future PV installations are provided.

关键词： Photovoltaic systems Visualization Renewable energy sources Energy Electricity Urban areas Inspection distributed power generation Internet Reliability

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Prediction of Fruits and Vegetable Diseases Using Machine Learning and IoT

Prediction of Fruits and Vegetable Diseases Using Machine Le...

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international conference on Information systems and Computer Networks (ISCON)

作者： Dharmendra Kumar Kamal Narayan Kamlesh Amresh Kumar Shilpi Banerjee Dr. Kumar Vishal Department of Computer Science & IT Magadh University Bodh Gaya Bihar India G.B.M College Gaya Bihar India

sensors and the Internet of things (IoT) will be integral to making agriculture more sustainable and productive in the future. Most of the pressing environmental, economic, and technological problems can be solved by taking advantage of IoT, WSNs, and ICT (Information and Communications Technology). Adding more and more connected devices generates a large volume of data with various modalities. Additionally, the increase in the number of interconnected devices occurs due to geographical and temporal factors. this vast amount of data, once intelligently processed and analyzed, will provide a higher level of insights that will improve forecasting, decision making, and sensor dependency management in the future. In this article, we will cover a comprehensive overview of how machine learning algorithms can assist in the analysis of agricultural sensor data. We also discuss a prototype for an integrated food, energy, and water (FEW) system utilizing IoT data. the majority of previous papers in the literature on fruits and vegetables disease detection focused on just one type of disease. Nevertheless, this paper reviews several types of fruits and vegetables diseases.

关键词： Smart agriculture Cloud computing Wireless sensor networks Machine learning algorithms Image recognition Prediction algorithms Classification algorithms

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