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International conference on network and Service Management

作者： Péter Orosz Tamás Marosits Tamás Skopkó Dept. of Telecommunications and Artificial Intelligence Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9783903176669

ISBN: (纸本)9798331505158

Advancements in internet service provision have enabled subscribers to access multi-gigabit throughput for both wired and mobile connections. Despite underutilization, users demand compliance with subscription parameters, necessitating precise measurement of multi-gigabit connections. This paper investigates the challenges associated with profiling multi-gigabit internet access using web browsers, addressing limitations introduced by browser capabilities, client hardware, and SOHO router performance. We present a novel measurement system designed to accurately evaluate key service quality parameters, including throughput, latency, and packet loss, for multi-gigabit connections. The system architecture comprises user endpoint devices and measurement servers strategically positioned in high-bandwidth, network-neutral locations to ensure accurate and scalable measurements. Empirical results demonstrate the system’s efficacy in measuring multi-gigabit connections, even within the constraints of client and network hardware limitations. This research establishes a robust framework for reliable and comprehensive assessment of high-speed internet access services, contributing to improved service quality and user satisfaction.

关键词： performance evaluation Web and internet services systems architecture Packet loss Position measurement Throughput Hardware Browsers Servers Reliability

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TSIP: A Lightweight SIP-Based Messaging Protocol for Resource-Constrained Embedded Devices 31

TSIP: A Lightweight SIP-Based Messaging Protocol for Resourc...

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31st International conference on Software, Telecommunications and Computer networks, SoftCOM 2023

作者： Khalil, Haytham Elgazzar, Khalid Ontario Tech University IoT Research Lab ECSE Department OshawaON Canada

ISBN: (纸本)9798350301076

Phone of Things (PoT) is a term recently coined in the internet of Things (IoT) field. PoT extends the available connectivity options of IoT systems to include the ubiquitous phone network's assets and infrastructure, leveraging them as a part of the IoT architecture. In this context, this paper proposes a constrained version of the Session Initiation Protocol (SIP), the dominant protocol used in VoIP communications. The proposed protocol, called tSIP, is a small-footprint messaging format that provides decentralized peer-to-peer communication between tSIP-enabled IoT devices. tSIP messages can also be mapped to the original SIP messages with the help of a proxy. tSIP promotes PoT and provides a standardized lightweight communication protocol between low-resource embedded IoT devices and the existing Unified Communications (UC) solution within the premises, allowing IoT devices to function as typical SIP endpoints in the VoIP ecosystem and facilitating their control and monitoring. The paper reviews the proposed tSIP messaging protocol regarding its architecture, encoding, and performance evaluation on embedded devices. The paper also gives use case scenarios for the proposed tSIP and discusses where its development will go in the future. © 2023 University of Split, FESB.

关键词： internet of things

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Research on full-process product defect traceability analysis technology based on workshop big data 2

Research on full-process product defect traceability analysi...

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2nd International conference on Algorithms, High performance Computing and Artificial Intelligence, AHPCAI 2022

作者： Zhang, Jianquan Lan, Shiqing Liu, Lei He, Ru Shenzhen Catic Information Industry Group Co. Ltd. Guangdong Shenzhen518055 China IoT Research Institute Shenzhen Polytechnic Guangdong Shenzhen518055 China

ISBN: (纸本)9798350334784

The internet of Things(IOT) technology collects real-time data from material management, equipment status, production process integration, process parameters and other accurate traceability analysis, obtains the information of the whole production process, optimizes the production plan and workshop scheduling, and promotes the intellectualization of the manufacturing industry in the digitization of the whole production process. In the production process of modern discrete manufacturing industry, various types of data will be continuously generated. Radio Frequency Identification(RFID), industrial wireless sensor network, Ethernet and intelligent gateway equipment will be used to realize interconnection and intercommunication. The product quality data in the production process will be collected automatically and in real time. The data will be returned to the data integration center in the form of sensor network networking and stored in the big data platform system, and the big data analysis will be applied, Mining, forecasting, analyzing and processing the product quality, and combining scientific decision-making methods to optimize the production process and achieve more rapid and accurate control. This paper analyzes the structure of industrial big data platform, gives the process of product quality prediction based on big data, and designs the discrete manufacturing product quality prediction model to realize the regression prediction of product quality based on eXtreme Gradient Boosting(XGBoost). © 2022 IEEE.

关键词： internet of things

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A Study on the performance of Distributed Storage systems in Edge Computing Environments

A Study on the Performance of Distributed Storage Systems in...

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IEEE International conference on Joint Cloud Computing (JCC)

作者： Antonios Makris Ioannis Kontopoulos Stylianos Nektarios Xyalis Evangelos Psomakelis Theodoros Theodoropoulos Andreas Varvarigos Konstantinos Tserpes Department of Informatics and Telematics Harokopio University of Athens Greece School of Electrical and Computer Engineering National Technical University of Athens Greece

ISBN: (数字)9798350387339

ISBN: (纸本)9798350387346

Edge computing presents a promising paradigm for the management and processing of the vast volumes of data generated by internet of Things (IoT) devices. By merging cloud services with decentralized processing at the edge of the network, edge computing optimizes resource utilization while mitigating communication overhead and data transfer delays. Despite advancements, there are issues regarding cloud/edge-based application requirements. A distributed edge storage solution is crucial, ensuring data proximity, minimizing network congestion, and adapting to changing demands. Nevertheless, implementing or selecting an efficient edge-enabled storage system presents numerous challenges due to the distributed and heterogeneous nature of the edge, as well as its limited resource capabilities. Hence, it is essential for the research community to actively contribute towards clarifying the objectives and delineating the strengths and weaknesses of different storage solutions. This work presents an overview and performance analysis of three storage solutions in the edge computing context, namely MinIO, IPFS, and BigchainDB. The evaluation considers a set of quality of Service (QoS) and resource utilization metrics. The systems are deployed on a cluster of four Raspberry Pis, which function as a network of edge devices. The results demonstrate the superiority of IPFS and provide insights into the performance of the evaluated storage systems for edge deployments.

关键词： performance evaluation Cloud computing quality of service performance analysis internet of Things Resource management Time factors

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Design of Minority Student Management System in Higher Vocational Colleges Under Private network Environment: Based on Identification and Retrieval Algorithm 6

Design of Minority Student Management System in Higher Vocat...

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6th International conference on Intelligent Computing and control systems, ICICCS 2022

作者： Zhao, Dan Jia, Yangbing Sichuan Vocational and Technical College Suining629000 China

ISBN: (纸本)9781665410359

This paper is based on the random level removal algorithm and the continuous level removal algorithm, and the identification algorithm of the random level removal algorithm respectively, the system uses Java language, the database uses MySQL relational database system to manage related data, the server uses Windows11 ServerSP1 operating system, and the container uses Tomcat6.0, the client uses IE6.0 or later browsers, the technical architecture adopts MVC three-tier structure, and a B/S mode student information management system is designed to establish basic data maintenance, student attendance, student awards, and academic performance. Management, conduct quality assessment, comprehensive quality assessment, performance clustering, psychological testing, recruitment and employment and other nine modules. © 2022 IEEE.

关键词： Students

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Identifying the Prospects of the RedBoard Arduino in LTE Wireless Landscapes

Identifying the Prospects of the RedBoard Arduino in LTE Wir...

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Open Innovations Association (FRUCT), conference of

作者： Khalida Walid Nathim Nabaa Ahmed Noori Manar Adnan Nassrat Al-Ubaidi Ibraheem Mohammed Khalil Ibraheem Nadher Olha Myronenko Wafaa Mustafa Hameed Alnoor University Nineveh Iraq Al Mansour University College Baghdad Iraq Al Hikma University College Baghdad Iraq Al-Rafidain University College Baghdad Iraq Al-Turath University Baghdad Iraq Kruty Heroes Military Institute of Telecommunications and Information Technology Kyiv Ukraine Cihan University Sulaimaniya Sulaymaniyah City Iraq

ISBN: (数字)9789526524627

ISBN: (纸本)9798331507411

In the backdrop of an enormous increase in internet of Things (IoT) devices and advanced wireless networks like Long-Term Evolution (LTE), it is essential, from various perspectives, to understand the performance behavior. The RedBoard Arduino is a microcontroller that enables real-time insights and performance for your remote monitoring, data gathering, and control *** study aims to evaluate the latency and throughput performance of Redboard Arduino in LTE cellular wireless networks. Success of IoT applications in real-time environments is anchored by these performance *** environment set up was created to analyze the RedBoard Arduino in diverse network scenarios. We studied how data packet sizes, network congestion, signal strength and uplink transmissions affect the performance of devices. Trials were conducted under a range of circumstances to mimic real-world *** RedBoard Arduino was good under perfect network conditions. Latency on the other hand saw a much larger range due to fluctuating network load, signal quality, and packet size. These difference can be very critical to systems which depend on real time data exchange and *** characteristics dictate the successful coexistence of RedBoard Arduino with LTE networks for evolving IoT applications. The research contributes to the ongoing debate on performance management of IoT devices over next generation wireless networks, highlighting that adaptive mechanisms are required for communicating with specific network conditions.

关键词： performance evaluation Protocols Microcontrollers Wireless networks Throughput Real-time systems Safety internet of Things Uplink Long Term Evolution

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The Smart Factory of Tomorrow: Artificial Intelligence and Machine Learning Reshaping Manufacturing Processes 2

The Smart Factory of Tomorrow: Artificial Intelligence and M...

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2nd International conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Priyanga, P. Ashwini, K. Deepa, S.R. Sridevi, S. Department of Artificial Intelligence and Machine Learning RNS Institute of Technology Karnataka Bangalore India Department of Computer Science and Design K.S. Institute of Technology Karnataka Bangalore India Tamil Nadu Chennai India

ISBN: (纸本)9798350305418

The smart factory of the future would not be possible without the development of AI and ML technologies, which have ushered in a new era of production. Traditional industrial processes are being revolutionized by AI and ML due to their capacity to evaluate large quantities of data and make autonomous choices, which is leading to greater efficiency, productivity, and profitability. Predictive maintenance is one area where AI and ML are making important contributions. These systems may prevent unexpected and expensive failures by constantly monitoring equipment performance and analyzing real-time data. Taking preventative measures like these results in less downtime, lower maintenance expenses, and more efficient machinery. Synergies between AI and ML are improving factory quality assurance. These technologies can identify even the smallest flaws or deviations from product standards using sophisticated vision systems and pattern recognition algorithms. Manufacturing companies may reduce waste and customer complaints by maintaining a constant quality standard via the use of automated inspection methods. Optimization of production planning and scheduling is another important use of AI and ML in manufacturing. © 2023 IEEE.

关键词： Artificial Intelligence Collaborative Robots (Cobots) Industrial internet of Things (IIoT) Lean Manufacturing Machine Learning Manufacturing Processes Predictive Maintenance Production Planning quality control Smart Factory

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Automatic Water Distribution System Using Wireless Sensor network 27

Automatic Water Distribution System Using Wireless Sensor Ne...

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27th International conference on Information Technology, IT 2023

作者： Ndagi, Abubakar Kertesz, Csaba Zoltan Transilvania University Department of Electronics and Computers Brasov Romania

ISBN: (纸本)9798350397512

Water distribution sector is currently facing operation challenges, especially in urban areas, as a result of climate change and high rate of urbanization experienced in these areas. These two aforementioned factors pose a threat of water shortage in these cities and consequently affects the water distribution sector as there will be interruption in water supply. To mitigate this, efficient management of the entire distribution process and automated monitoring and control systems are needed. This paper showcases such an automated water distribution system that is responsible for providing clean water to urban residents. The system uses an IoT (internet of Things) approach for constant and real-time monitoring of water supply from the Base Station down to the water tanks of each block of house. Water levels and water quality are continuously monitored in the end-user's water tanks, and the tanks are automatically refilled based on user requirements and Base Station planning. Both end users and water board managers can follow the water flow information in a user-friendly web application. © 2023 IEEE.

关键词： Water tanks

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A Smart Energy Optimization and Collision Avoidance Routing Strategy for IoT systems in the WSN Domain 7th

A Smart Energy Optimization and Collision Avoidance Routing ...

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7th International conference on Computing in Engineering and Technology, ICCET 2022

作者： Swaminathan, K. Ravindran, Vijay Ponraj, Ramprakash Satheesh, R. Department of ECE University College of Engineering Pattukkottai Thanjavur India Departement of EEE Saranathan College of Engineering Trichy India

ISBN: (纸本)9789811927188

Wireless Sensor networks (WSNs) offer a wide range of applications, including next-generation intelligent internet of Things (IoT) applications. network nodes in WSNs do not admit their battery replacement since the phenomenon being researched is rarely accessible or inaccessible. WSN nodes with limited resources utilize batteries with limited capacity. For IoT applications, power utilization of each node and the longevity of the overall network is a difficulty for long-running WSNs. Energy-efficient technologies must be employed to extend the lifetime of WSNs, which is a significant problem. Most on-demand routing systems choose a link between sources to the destination nodes depending on characteristics such as the number of hops. Count-based data result in frequently broken links, higher energy usage, and shorter IoT application lives. The approach provided in this work is a cross-layer form of Ad-hoc based vector, with quality of link and collision occurrence data’s substituting the hopping occurrence in the system with link establish. To aid the network layer in making intelligent routing decisions, the proposed technique gathers quality of link diagnostic values (LDV) information from the superior Physical layer and collides information from the Media control layer. The proposed routing measure uses algorithms presented for route establishment, updating collision count for a stable and long-term routing plan. The proposed approach of incorporating essential changes into existing code, this study will be carried out using the NS-2 network simulator. Physical and MAC layers and an Adhoc protocol comparison of existing techniques show that performance has improved in terms of the energy economy, system durability, path consistency, and latency. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： internet of things

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Distributed energy storage planning considering reactive power output of energy storage and photovoltaic

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ENERGY REPORTS 2022年 8卷 562-569页

作者： Wang, Chunyi Zhang, Lei Zhang, Kai Song, Sijin Liu, Yutian Shandong Elect Power Co State Grid Jinan Shandong Peoples R China Heze Power Supply Co State Grid Heze Shandong Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Shandong Peoples R China

With distributed photovoltaic (DPV) rapidly developing in recent years, the mismatch between residential load and DPV output leads to serious voltage quality problems. A double layer nested model of distributed energy storage (DES) planning is proposed in this paper to solve this problem. The inner optimization model is established for optimizing DES and DPV operation strategy considering the optimization of voltage quality evaluation results. The voltage quality evaluation indicators include three-phase voltage unbalance, voltage deviation and voltage fluctuation. The outer optimization model is established for DES siting and sizing considering the cost performance ratio of voltage quality improvement. The reactive power output of DPV and DES are the main factors to be considered. The modified particle swarm optimization algorithm is adopted to solve this model. Simulation results of the modified IEEE 33-bus distribution network demonstrate that the voltage safety margin is enhanced and the subsequent voltage management cost is reduced. (C) 2022 The Author(s). Published by Elsevier Ltd.

关键词： Distributed energy storage Distributed photovoltaic Reactive power Smart grid Voltage quality

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