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Performance evaluation of cluster-based routing protocol used in wireless internet-of-things sensor networks 1

Performance evaluation of cluster-based routing protocol use...

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1st ieee international conference on Advances in Electrical, computing, Communications and Sustainable Technologies, ICAECT 2021

作者： Mishra, Jaya Bagga, Jaspal Choubey, Siddhartha Choubey, Abha Gupta, Khushi Shri Shankaracharya Technical Campus C.S.V.T. University Bhilai Chhattisgarh India

ISBN: (纸本)9781728157900

The Internet of Things (IoT) is the most popular technology exist due to its huge number of application. One of the components of IoT is wireless sensor network (WSN). The WSN is the combination of huge amount of sensor nodes, which are responsible to generate the data for the IoT network. These sensor notes are very low power computing devices, due to that they also have low range of communication. The wireless sensor network generates the data and sends the data through the intermediate sensor node to the sink node. The sink node sometime also called gateway node or Base station (BS), which collects and aggregates the data and transmit it to the cloud for further storage and processing, which is again a component of IoT. The data reaches the gateway node using different routing protocol with the aim of less energy cost. As we are talking about low power sensor nodes the power efficiency is the most importance performance metrics while developing the routing protocol. In this paper, a cluster-based routing protocol for IoT enabled WSN network has been proposed. The cluster-based routing protocol known as the energy efficient protocol due to its lower Energy consumption for cluster by aggregating the data within the cluster head and reducing the number of data transmission to the gateway node. In this paper, the cluster-head selection and cluster formation are defined, and simulation has been conducted. Further, the proposed algorithm compared with the existing research on cluster-based routing protocol in the basis of different metrics such as energy consumption, throughput and the lifetime of the network. © 2021 ieee

关键词： Energy efficiency

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Management of load demand considering a DG working on islanded mode 1

Management of load demand considering a DG working on island...

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1st Odisha international conference on Electrical Power Engineering, Communication and computing Technology, ODICON 2021

作者： Tungadio, Diambomba Hyacinthe Sun, Yanxia Electrical and Electronic Engineering Science University of Johannesburg Johannesburg South Africa

ISBN: (纸本)9781728176635

This paper presents a load demand management of interconnected distributed generation (DG) working on islanded mode. The development of technology related to network integration and the use of energy renewable source continues to attract researches, today these sources can generate over a thousand kilowatts, that why it important to look after the management of load supplied by the DG specially when working in islanded mode. The proposed load management model took into account the energy from the storage system and the tie-lines power flow transfer constraints applying the optimal control theory. The proposed methodology considers two loads types: critical and non0critical and proposes a load management of DG interconnected system. All optimization problems were solved using Matlab environment. © 2021 ieee.

关键词： distributed power generation

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distributed manufacturing in knitting industry 1

Distributed manufacturing in knitting industry

引用

1st ieee international conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Li, Lijun Sun, Pingfan Lu, Jixiang School of Automation Southeast University Nanjing China Institute of Knitting Ningbo Cixing Co. Ltd. Ningbo China College of Science and Technology Ningbo University Ningbo China

ISBN: (纸本)9781665433372

Knitwear is the second largest product category in the traditional clothing industry. The traditional clothing product supply chain is difficult to meet consumer's demand of fast fashion. AI and industrial Internet technology, together with intelligent knitting equipments make C2M flexible supply chain possible through digitization. distributed cloud factory is built as regional node of production supported by digital twin and parallel intelligence. Personalized needs of end consumers can be quickly responded, and the cost is close to traditional large-scale assembly line. Parallel manufacturing applies industrial robots, Internet of things, cloud computing, AR and AI technologies comprehensively to build virtual factory in Cloud that carries out decision-making and management simultaneously, with highly automated production equipments in workshop. Meanwhile, it combines with smart knitting factories to build a global distributed collaborative production management platform based on parallel manufacturing architecture system through virtual reality interaction, distributed manufacturing, managed and controlled through Cloud. Intelligent upgrading of traditional knitting industry can effectively improve labor productivity, reduce production cost and number of employees. © 2021 ieee.

关键词： Decision making

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Collaborative User Mobility Prediction in distributed Edge computing Framework

Collaborative User Mobility Prediction in Distributed Edge C...

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ieee Internatonal conference on Mobile Adhoc and sensor systems (MASS)

作者： Sardar Jaffar Ali Syed M. Raza Hyunseung Choo Dept. of AI Systems Engineering Sungkyunkwan University Suwon South Korea James Watt School of Engineering University of Glasgow Glasgow United Kingdom Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

User attachment forecasting with Deep Learning (DL) is an effective tool for proactive mobility management in dense Beyond 5G (B5G)/6G deployments with reduced cell sizes. However, collecting user data in a central cloud to facilitate DL model learning causes extensive overhead and privacy concerns. distributed edge cloud-based federated learning solves these issues, but it faces challenges in handling out-of-distribution data from decentralized edges at the network periphery, and the model biases due to data heterogeneity. This paper addresses these limitations by proposing a fully distributed Collaborative User Mobility Prediction (CUMP) framework that mitigates the out-of-distribution data issue through collaboration among initial layers of DL models in edges that are selected using inter-edge mobility rates. The remaining part of each model only trains on local data, preserving biases towards their respective edges. This enhances the generalization, robustness, and predictive performance of the DL models. Results show that CUMP outperforms conventional global learning and state-of-the-art distributed personalized federated learning and cyclic incremental institutional learning by 63%, 12%, and 10% in predicting the next Point of Attachment (PoA) of a user and by 70%, 22%, and 28% in predicting user dwell time in current PoA, respectively. Thus, CUMP improves prediction performance while reducing network and storage overheads while preserving privacy.

关键词： Privacy Federated learning Microprocessors distributed databases Collaboration Predictive models Smart systems Data models Robustness Forecasting

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2022 IEEE International Conference on Blockchain and Distrib...

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2022 ieee international conference on Blockchain and distributed systems Security, ICBDS 2022 2022年

作者： Oboler, Andre Ieee Computer Society United States

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Autonomous Power Management for Hybrid AC/DC Nano Grid Using ESS and DG 1

Autonomous Power Management for Hybrid AC/DC Nano Grid Using...

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1st international conference on Intelligent Controller and computing for Smart Power, ICICCSP 2022

作者： Razzaq, Syed Abdul Jayasankar, Vairavasamy Vel-Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Dept. Electrical and Electronics Engineering Chennai India

ISBN: (数字)9781665472586

ISBN: (纸本)9781665472586

The increasing power demand with energy management is turning out to be an important aspect for electrical power system. Integration of Renewable Energy Source (RES) has indeed minimized the carbon emission and succeeded in delivering clean green energy. Power electronic converters are the major building block of power transmission and conversion at economical cost and also in reducing the design and installation of bulky electrical devices in remote zones, rural, congested place and consumers with few kilo watts of power. Designing a Nano Grid (NG) with less than 50kW of capacity will be benefit for the electrical distribution board. The proposed design discuss the design of Photo Voltaic (PV) with MPPT, DC/DC converter, single phase bidirectional Voltage Source Converter(VSC), Battery Energy storage System (BESS) and three phase converter. The control technique for autonomous bidirectional power transfer to hybrid AC/DC NG with a simple PI controller. NG structure is simulated in Matlab/Simulink. This NG is equally adoptable for Pico Grids (PG), domestic and commercial consumers. It also features a load management strategy. The proposed work is reliable in upgrading to Micro Grid (MG) or integrating with MG with decentralized control scheme. This NG is plug and play type also suitable for Internet of Things (IoT) for various electrical farms and other applications. © 2022 ieee.

关键词： distributed power generation

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Adaptive Protection Coordination Scheme for Distribution Networks with distributed Generation

Adaptive Protection Coordination Scheme for Distribution Net...

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Innovative Sustainable Technologies for Energy, Mechatronics, and Smart systems (IstEMS), international conference on

作者： Rani Kumari Bhukya Krishna Naick Dept. of Electrical Engineering Indian Institute of Technology (IIT) Dhanbad India

ISBN: (数字)9798350384246

ISBN: (纸本)9798350384253

As distributed generation (DG) supported by renew-able energy become more and more prevalent in the distribution network (DN), the coordination of directional overcurrent relays (DOCRs) in their presence needs to be addressed. Numerous meta-heuristic optimization strategies have been used to address this problem in order to determine the optimal relay settings and to achieve the best possible coordination of the protective relays considering coordination constraints. This study presents an adaptive protection coordination strategy for DNs with inter-connected DG units. The scheme utilizes Chicken swarm opti-mization (CSO) to achieve optimal coordination. It dynamically adjusts protective device (DOCR) settings in response to changes in the system, such as fluctuations in DG output or modifications to the network topology. The effectiveness of the proposed adaptive scheme is demonstrated through its application to two benchmark systems: the 9-bus Canadian system and the ieee 30-bus system. The results are presented and analyzed, showcasing the scheme's capabilities. This approach significantly enhances power system protection and enhances reliability and efficiency of power DNs.

关键词： Adaptive systems Network topology Heuristic algorithms Power system protection Protective relaying Distribution networks Benchmark testing

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Deriving Interaction Scenarios for Timed distributed systems by Symbolic Execution 10th

Deriving Interaction Scenarios for Timed Distributed Systems...

引用

10th international conference on New Trends in Model and Data Engineering, MEDI 2021 held with 4th international Workshop on Modeling, Verification and Testing of Dependable Critical systems, DETECT 2021, Symposium on Intelligent and Autonomous systems, SIAS 2021, 1st Workshop on Control Software: Methods, Models, and Languages, CSMML 2021, Workshop on Blockchain for Inter-Organizational Collaboration, BIOC 2021 and 1st international Health Data Workshop, HEDA 2021

作者： Bannour, Boutheina Lapitre, Arnault Gall, Pascale Le Université Paris-Saclay CEA List Palaiseau91120 France Université Paris-Saclay CentraleSupélec MICS Gif-sur-Yvette Cedex91192 France

ISBN: (纸本)9783030876562

In this paper, we propose a symbolic framework to analyze and debug communicating distributed models. We implement dedicated symbolic execution techniques for such models and use them to compute interaction scenarios satisfying a particular user coverage objective. These scenarios reveal emergent temporal and data correlations that are part of the system specification. To support the understanding and the analysis of such learned knowledge, our tooling allows for an intuitive annotated scenario visualization using sequence diagrams. As an application, we develop behavioral models for the so-called distributed Trickle algorithm which manages information dissemination in Wireless sensor Networks (WSN). We select relevant scenarios which cover critical communications achieving an up-to-date or outdated state of the network. © 2021, Springer Nature Switzerland AG.

关键词： Wireless sensor networks

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Web sensor Network for Health Monitoring systems 1

Web Sensor Network for Health Monitoring Systems

引用

1st ieee international Interdisciplinary Humanitarian conference for Sustainability, IIHC 2022

作者： Anitha, G.S. Sumathi, M.S. Rahaman, Sabina Thejaswini, S. RV College of Engineering Department of Electronics and Electrical Engineering Bengaluru India BMS Institute of Technology Electronics and Telecommunication Bangalore India BMS Institute of Technology Electronics and Communication Bangalore India

ISBN: (纸本)9781665456876

Patient checking is an urgent piece of the medical care framework these days, either at clinics or home. By utilizing IoT innovation, it is feasible to defeat the issues looked at by truly unsteady patients and needy individuals in counseling a specialist consistently. The essential thought behind the task is, that it suggests that whether an individual is at home, out traveling, or at his workplace, he/she can remain associated with the specialists in the emergency clinic or project that offers an IoT-based patient observation platform that includes wearable sensors that collect information on many factors affecting patients' welfare. The sensors are bridged to the Node MCU Microcontroller which has a Wi-Fi Module with a built-in TCP\IP protocol stack that can connect any microcontroller to your Wi-Fi module. The specialists bring the well-being data of patients using a UI (PDA). Additionally from the information put away in the cloud server the well-being boundaries, for example, temperature and moistness, pulse and SPO2 levels of the patients and needy individuals for general medical care. © 2022 ieee.

关键词： Wearable sensors

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distributed Deep Reinforcement Learning for Autonomous Iot Healthcare Devices in the Cloud 1

Distributed Deep Reinforcement Learning for Autonomous Iot H...

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1st international conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Shukla, Aasheesh Pokhariya, Hemant Singh Michaelson, Jacob Laxminarayanamma, K. Kumar, Mukesh Krishna, Om Gla University Department of Electronics and Communication Mathura India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Institute of Aeronautical Engineering Department of Information Technology Telangana Hyderabad India Lloyd Institute of Engineering and Technology Greater Noida India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350330915

The ethical and philosophical problems concerning the cooperation of AI systems and human artists are also examined in this study. In addressing authorship, agency, and the very essence of creation, the changing position of artists as co-creators with intelligent algorithms is explored. It also looks at how AI can question and change conventional ideas of creative competence. Additionally, this study looks into how AI affects the promotion and distribution of art. AI-driven marketing tactics provide improved targeting of customers, personalized experiences, and optimal promotional efforts by utilizing insights based on data and predictive analytics. The study focuses on how these developments transform the relationships between galleries and artists and their patrons, ultimately fostering a more varied and inclusive art scene. The system's potential in many healthcare scenarios has been validated through simulations and practical experiments, which have received excellent feedback from healthcare providers. A critical review emphasizes the need to address practical deployment issues and data security concerns, while also highlighting the exciting convergence of IoT healthcare devices and DDRL. The paper ends with suggestions for more research, highlighting the significance of ethical issues, user interface improvements, and real-world validation. Through the smooth integration of DDRL-enhanced Internet of Things (IoT) medical equipment into clinical practice, our research eventually improves patient care and transforms the delivery of healthcare. © 2023 ieee.

关键词： data processing healthcare Internet of Things learning process technology

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