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

共 30822 条记录，以下是1691-1700 订阅

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Chen-Fliess Series for Linear distributed systems with One Spatial Dimension 26

Chen-Fliess Series for Linear Distributed Systems with One S...

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26th international conference on System Theory, Control and computing (ICSTCC)

作者： Pham, Natalie Gray, W. Steven Old Dominion Univ Dept Elect & Comp Engn Norfolk VA 23529 USA

ISBN: (数字)9781665467469

ISBN: (纸本)9781665467469

Given a smooth finite-dimensional state space system which is linear in the input, its input-output map can be represented by a Chen-Fliess series, namely, a weighted sum of iterated integrals of the input's component functions. The objective of this paper is to propose a generalized notion of a Chen-Fliess series for infinite-dimensional systems. The basic idea is to replace the real field of series coefficients with a ring of linear operators which act on the iterated integrals. The specific goals are to provide sufficient conditions for convergence of this generalized series and to exercise the theory on two specific examples: the transport equation and second-order hyperbolic partial differential equations. It will be shown in these examples that the generalized Chen-Fliess series under suitable conditions yields solutions that converge pointwise to the known classical solutions.

关键词： Linear distributed systems infinite-dimensional systems Chen-Riess series formal power series

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Hybrid Resource Scheduling Algorithms in Heterogeneous distributed computing: a Comparative Study and Further Enhancements

Hybrid Resource Scheduling Algorithms in Heterogeneous Distr...

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2023 international conference on IT Innovation and Knowledge Discovery, ITIKD 2023

作者： Ba, Mandicou Fall, Ahmad Haggar, Bachar Salim UCAD/ESPIDGI Laboratoire Limbi Dakar Senegal Enastic Laboratoire Limbi Ndjamena Chad

ISBN: (纸本)9781665463720

In the context of heterogeneous distributed systems like modern High-Performnace computing (HPC) that must respond to unpredictable requests of variable complexity with variable resource requirements (processing power as well as storage capacity), a classical scheduling algorithm would not be suitable. Therefore, hybrid dynamic scheduling approaches have been adopted. These later have the ability to adapt over time based on the knowledge gained from the results of previous work. Several techniques are thus used to optimize these algorithms such as resources clustering. In this paper, we propose a comparative study of some of most popular algorithms in order to highlight the situations in which each algorithm is more suitable. We evaluate their performance and evolution in a realistic setting of CloudSim tool without neglecting load-balancing, and measure these performance metrics at runtime. © 2023 ieee.

关键词： Scheduling algorithms

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Leveraging Blockchain for Secure Data Sharing and Cloud computing: Implementing distributed Timestamping with Machine Learning and Cryptographic Protocols 1

Leveraging Blockchain for Secure Data Sharing and Cloud Comp...

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1st international conference on computing, Sciences and Communications, ICCSC 2024

作者： Mallreddy, Sukender Reddy Vasa, Yeshwanth Bonala, Sapan Bharadwaj Macha, Sharath chandra Salesforce Consultant City of Dallas DallasTX United States Milwaukee United States Middletown United States Dallas TX United States

ISBN: (纸本)9798350353648

In the last ten years-blockchain technology has changed a lot. It started as basic records shared across many computers and has become advanced networks that can do many things. Therefore, this study looks at how well blockchain systems can handle complex math problems for security. We focus on creating a system that puts timestamps on events. This method combines Schnorr signatures and Pedersen commitments. We use the Ethereum network to store and check data. The system uses a smart contract to manage data and connect servers and clients. Servers put timestamps on events and clients send data to be timestamped and checked. This setup makes sure they are clear and reliable. However, the study tests how well the system works by looking at cost-how much memory it uses and how fast it runs. The study also talks about using Ethereum. Ethereum lets everyone see timestamps and what happen-which is good for trust. But it can't keep secrets-so it's not good for private data. This study shows that blockchain is useful for more than just money. It can make sure events are real and safe. By mixing math ideas in blockchain-the study shows how to make data safer and more reliable in many places. © 2024 ieee.

关键词： Ethereum

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Performance Assessment of Routing Protocols in an Internet of Things by communicating in a Wireless sensor Networks 6

Performance Assessment of Routing Protocols in an Internet o...

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6th international conference on Intelligent computing and Control systems, ICICCS 2022

作者： Jaganathan, D. Archana, T. Saranya, S. Srinivasan, Sathiyandrakumar Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology India Saveetha Engineering College India Panimalar Institute of Technology India Kalasalingam Academy of Research and Education India

ISBN: (纸本)9781665410359

Protocols have an important role on the overall performance of Wireless sensor Networks, including throughput and power consumption, postponement and transmission rate. This research study has a portion of suggested computations that focus on network performance concerns in the proposed sensor network. The directing convention monitors the energy and draws out the steadiness time of organization as well as organization life time. As a result of this convention, sensor nodes will no longer establish pairs with one another and share information about what is being detected. Additionally, the Cluster Head selection technique has been improved and CHs are selected based on the remaining power of the sensor nodes. The reenactment has been done on MATLAB for assessing the exhibition of these conventions on various boundaries thinking about two situations. In all scenarios, the suggested convention outperforms alternative steering conventions, according to the findings of the simulations. © 2022 ieee.

关键词： sensor nodes

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Empowering Smart Homes with Fog computing for IoT Connectivity

Empowering Smart Homes with Fog Computing for IoT Connectivi...

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2024 international conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Mahdi, Ali Jafer Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq AI-Zahraa University for Women Department of Scientific Affairs Bangi43600 Malaysia College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Innovative grid technology leverages Information and Communication Technology (ICT) to enhance energy efficiency and mitigate losses. This paper introduces a 'novel three-tier hierarchical framework for smart homes within the Internet of Things (IoT)' ecosystem, addressing the current shortage of intelligent solutions that underutilize IoT advantages. Our framework's primary objective is to elevate smart homes to the microgrid level, enabling the seamless integration from the microgrid's renewable distributed energy sources and attaining maximum energy efficiency. In addition to traditional data processing, we propose the application of fog computing in smart homes. Through a rigorous simulation using real smart meter datasets, our study demonstrates that fog computing, mainly when using predictive filtering, may drastically cut down on the amount of data being sent and the load on the home's network. This innovation holds immense potential for revolutionizing energy management and resource allocation in the context of smart homes, thus contributing to a sustainable and efficient future. This research represents a critical step towards harnessing the power of IoT and fog computing in smart grids and homes, offering a promising path towards more intelligent, eco-friendly, and energy-efficient living spaces. © 2024 ieee.

关键词： Smart homes

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Review of Ecological Environment Monitoring Methods of Northern Wetland in Inner Mongolia Based on WSN 7

Review of Ecological Environment Monitoring Methods of North...

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7th international conference on Communication and Information systems, ICCIS 2023

作者： Li, Wenyu Bai, Xiangyu Zhou, Kexin College of Computer Inner Mongolia University Inner Mongolia Key Laboratory of Wireless Networking and Mobile Computing Hohhot China

ISBN: (纸本)9798350330540

Wetland ecosystem is a special ecosystem, which refers to the area where water and land intersect, including swamps, rivers, lakes, estuaries, bays, etc. These areas usually have special biodiversity and ecological functions, which are of great significance to both human beings and the natural environment. In recent years, the northern wetland ecosystem of Inner Mongolia with Hulun Lake, Wuliangsuhai Lake and Daihai Lake as the core, is facing the problems of reduced water area, poor water quality and serious pollution due to natural and human factors, which has begun to affect other environmental changes and hindered social and economic development. It is urgent to monitor the ecological environment and control pollution in relevant areas. The core of environmental monitoring is data collection. The traditional data acquisition methods have some defects, such as high cost and low efficiency. This paper proposes to use wireless sensor network to carry out long-term automatic monitoring of ecological environment in this area, and summarizes the relevant experience and technology. © 2023 ieee.

关键词： Environmental monitoring Wetland ecosystem in the North Wireless sensor network

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Cloud-Connected Wearable Devices for Lone Worker Protection With Wireless sensor Networks 4

Cloud-Connected Wearable Devices for Lone Worker Protection ...

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4th international conference on Sustainable Expert systems, ICSES 2024

作者： Mohankumar, N. Manivannan, K.K. Babu, A. Ramesh Sampoornam, M. Maria Kovarasan, Rajesh Kambattan Srinivasan, C. Nagpur Campus Maharashtra Pune India Kcg College of Technology Department of Mechatronics Engineering Tamil Nadu Chennai India School of Computer Applications Vidya Vikas Institute of Engineering and Technology Karnataka Mysore India J.J College of Engineering and Technology Department of Information Technology Tamil Nadu Tiruchirappalli India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331540364

Various sectors continue to prioritize lone worker safety, which requires creative ways to provide quick support and monitoring. To safeguard lone workers, this paper introduces a new method that makes use of cloud-connected wearable devices that are coupled with Wireless sensor Networks (WSNs). The system design relies on sensors embedded in wearable devices that can monitor a range of environmental elements as well as the vital signs of workers. A central cloud platform receives data in real-time via wireless communication from these devices and processes and analyzes it. The system may detect possible dangers or crises using smart techniques and immediately notify those who are supposed to react or the proper authorities. Cloud computing also makes it easy to store, analyze, and monitor large amounts of data over time, which is great for doing proactive risk assessments and improving safety standards. It demonstrates solution's capacity to improve lone worker safety, reduce reaction times, and mitigate hazards via simulations and actual deployment scenarios, efficacy and dependability. This growing body of knowledge on how to protect lone workers in various workplaces by using the power of IoT and cloud computing. © 2024 ieee.

关键词： Cloud platforms

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distributed Deep Learning for Medical Image Processing in Cloud Environments 1

Distributed Deep Learning for Medical Image Processing in Cl...

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

作者： Varshney, Neeraj Madan, Parul Shrivastava, Anurag Kumar, C Praveen Rao, A Kakoli Srivastava, Amit Gla University Department of Computer Engineering and Applications 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 Tamilnadu Chennai India Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad India Lloyd Institute of Engineering and Technology Greater Noida India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350330915

The incorporation of distributed deep learning for medical image processing in cloud settings is the subject of this study. The findings demonstrate the high viability and significant performance advantages realized by cloud-based distributed systems, notably significant processing time savings, outstanding diagnostic accuracy, as well as improved scalability. The consequences for security and privacy have been discussed, with a focus on effective safeguards for private medical information. There is a void in the literature about resource and cost-effectiveness optimization tactics used in cloud-based systems. Future research must concentrate on resource optimization tactics for economic sustainability, study developing security risks and privacy techniques, and incorporate real-world implementations in order to improve this topic. This study informs the use of distributed deep learning in cloud-based medical image processing as well as adds to the body of knowledge in healthcare technology. © 2023 ieee.

关键词： cloud computing distributed deep learning medical image processing privacy resource optimization security

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Evaluation of distributed Collaborative Learning Approach for 5G Network Data Analytics Function 22

Evaluation of Distributed Collaborative Learning Approach fo...

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22nd ieee international conference on Trust, Security and Privacy in computing and Communications, TrustCom 2023

作者： Wang, Shoufeng Chen, Hua-Min Ouyang, Ye Li, Fan Chen, Xuan Ma, Limeng Li, Zhanwu Bian, Sen Ren, Zhidong INC. China Beijing University of Technology Faculty of Information Technology Beijing China China Unicom Beijing Branch Network Optimization Center Beijing China China Unicom Beijing China

ISBN: (纸本)9798350381993

As a key role in the future network functionalities, artificial intelligence (AI) has been studied widely. To match the envisioned traffic evolution trend and communication requirement, Network Data Analytic Function(NWDAF) is a new proposed 5G component to provide analytics for any Network Functions (NFs). Considering sending all data to a central NWDAF instance is extremely time-consuming and it raises concerns about security vulnerabilities and data overload, it's expected to design a distributed NWDAF architecture which is able to enhance NF data localization, improve security, reduce control overhead during model training, shorten the training time, and finally, enhance the accuracy of the trained models by virtue of local testing on a real-time network. Federated learning is considered in future NWDAF design, while its detailed structure and processes are not standardized yet. This paper studies the effectiveness of distributed federated learning based traffic characteristics analysis for NWDAF. Simulation shows that the learning accuracy is nolinear with data loss probability. Under the simulation assumption, the solution could endure 30% data loss, while the learning accuracy and the retransmission dramatically rise when data loss probability is greater than 45%. © 2023 ieee.

关键词： 5G mobile communication systems

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Robust-to-Noise Algorithms for distributed Resource Allocation and Scheduling 11

Robust-to-Noise Algorithms for Distributed Resource Allocati...

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11th RSI international conference on Robotics and Mechatronics, ICRoM 2023

作者： Doostmohammadian, Mohammadreza Aghasi, Alireza Semnan University Faculty of Mechanical Engineering Iran Oregon State University Electrical Engineering and Computer Science Department United States

ISBN: (纸本)9798350308105

Efficient resource allocation and scheduling algorithms are essential for various distributed applications, ranging from wireless networks and cloud computing platforms to autonomous multi-agent systems and swarm robotic networks. However, real-world environments are often plagued by uncertainties and noise, leading to sub-optimal performance and increased vulnerability of traditional algorithms. This paper addresses the challenge of robust resource allocation and scheduling in the presence of noise and disturbances. The proposed study introduces a novel sign-based dynamics for developing robust-to-noise algorithms distributed over a multi-agent network that can adaptively handle external disturbances. Leveraging concepts from convex optimization theory, control theory, and network science the framework establishes a principled approach to design algorithms that can maintain key properties such as resource-demand balance and constraint feasibility. Meanwhile, notions of uniform-connectivity and versatile networking conditions are also addressed. © 2023 ieee.

关键词： Graph theory

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