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

共 30762 条记录，以下是661-670 订阅

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Energy Efficient Node Re-positioning Algorithm for Uniform node Distribution in Wireless sensor Networks 4

Energy Efficient Node Re-positioning Algorithm for Uniform n...

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4th international conference on Communication systems, computing and IT Applications, CSCITA 2023

作者： Jain, Aarti Electronics and Communication Engineering Depatment Netaji Subash University of Technology Delhi India

ISBN: (纸本)9781665459877

Modelling of wireless sensor networks (WSNs) can be addressed from various aspects, such as energy efficiency, scalability, fault tolerance and network lifetime. Most of the algorithms proposed in literature which address these aspects assume uniform distribution of nodes in the area under consideration (AUC). However, in real life random deployment of nodes is done in the presence of geographical constraints posed by these networks along with limitations of cost & time. In order to ascertain efficient utilization of the proposed algorithms in literature, a method which repositions the nodes to obtain uniform distribution in the given AUC is required. The present work proposes energy efficient molecule equilibrium (EEME) based decentralized algorithm to reposition the sensor nodes (SNs) uniformly which are randomly distributed at the time of network initialization. In the proposed method, the SNs are assumed to be mobile and are proposed to move cautiously so as to minimize the energy consumption incurred due to repositioning of nodes. The performance of algorithm after its simulation has been compared with state-of the-art node repositioning algorithms for WSNs. The results show that the proposed repositioning algorithm outperforms the compared methods in terms of energy consumption, uniformity, coverage and average distance covered by nodes. © 2023 ieee.

关键词： Energy efficiency

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MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on distributed systems 51

MAD-Max Beyond Single-Node: Enabling Large Machine Learning ...

引用

ACM/ieee 51st Annual international Symposium on Computer Architecture (ISCA)

作者： Hsia, Samuel Golden, Alicia Acun, Bilge Ardalani, Newsha DeVito, Zachary Wei, Gu-Yeon Brooks, David Wu, Carole-Jean FAIR Meta Menlo Pk CA 94025 USA Harvard Univ Cambridge MA 02138 USA

ISBN: (纸本)9798350326598;9798350326581

Training and deploying large-scale machine learning models is time-consuming, requires significant distributed computing infrastructures, and incurs high operational costs. Our analysis, grounded in real-world large model training on datacenter-scale infrastructures, reveals that 14 similar to 32% of all GPU hours are spent on communication with no overlapping computation. To minimize this outstanding communication latency and other inherent at-scale inefficiencies, we introduce an agile performance modeling framework, MAD-Max. This framework is designed to optimize parallelization strategies and facilitate hardware-software co-design opportunities. Through the application of MAD-Max to a suite of real-world large-scale ML models on state-of-the-art GPU clusters, we showcase potential throughput enhancements of up to 2.24x for pre-training and up to 5.27x for inference scenarios, respectively.

关键词： Data Center distributed Inference distributed Training GPU Hardware-Software Co-Design Machine Learning Parallelization Performance Model Simulator

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distributed Sensing and Collaborative Edge computing for LEO Constellations 17

Distributed Sensing and Collaborative Edge Computing for LEO...

引用

17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Jaipuria, Saumya Banerjee, Ansuman Paul, Himadri Sekhar Indian Statistical Institute India TCS Research India

ISBN: (纸本)9798331531195

In recent years, constellations of low Earth orbit (LEO) satellites are being used extensively for a wide multitude of remote sensing applications starting from forest fire imaging to maritime applications like tracking of enemy ships. These satellites fly in low earth orbits and collectively image a wide area for data collection. Traditionally, satellites are used as passive sensing devices, which sense and download observations to Earth bound ground stations. This mechanism at times faces transfer bottlenecks and significantly limits the number of image collections. Building on recent developments in orbital edge computing, wherein small satellites are also equipped with computing power, this paper proposes an integrated sense and compute framework for these satellite constellations. Given a set of regions of interest to be imaged, we propose an integer linear programming (ILP) based solution approach to set up a collect communicate compute schedule that can maximize the number of region images collected and analyzed. We present preliminary experimental results of our framework on simulated datasets. © 2025 ieee.

关键词： Small satellites

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CLOUD-ENHANCED WIRELESS sensor NETWORKS FOR AIR QUALITY MONITORING

CLOUD-ENHANCED WIRELESS SENSOR NETWORKS FOR AIR QUALITY MONI...

引用

2024 international conference on Sustainable computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Shreenidhi, H.S. Agrawal, Trapty Kale, Kiran Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Electronics and Communication Engineering Presidency University Karnataka Bangalore India

ISBN: (纸本)9798350355338

A growing trend in environmental monitoring involves the use of inexpensive wireless sensors to create densely dispersed networks that provide higher spatial resolution than traditional air quality control systems. In this study, a novel air quality monitoring system-a wireless sensors network, or WSN, made up of a dispersed sensor network connected to a cloud system-is presented. The sensor nodes use low-power ZigBee motes to send field measurements in real time to the cloud via a dedicated gateway. An optimally calibrated cloud computing framework has been instituted to effectively retain, oversee, handle, and present the data originating from the sensor system. Optimised chemical and contaminant identification is made possible by using artificial intelligence tools in the cloud for sophisticated data handling and analysis. This system is unique in that it is small, light, and energy-efficient, allowing for the deployment of several nodes for thorough air quality evaluations in various locations. The effectiveness of the method in identifying common volatile organic chemicals including the compounds benzene, toluene, ethane, and xylene to is validated by a practical example in a laboratory environment. Principal component analysis, perceptron networks with backpropagation learning, and help vector computation methods are all used in the data processing. The results show that the volatile organic compound concentrations may be distinguished and quantified with good accuracy. Cloud computing, air quality, chemical sensors, and wireless sensor networks are among the key themes. © 2024 ieee.

关键词： Zigbee

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Design of a Scaled-Vehicle Research Platform for Software-Defined Vehicles 11

Design of a Scaled-Vehicle Research Platform for Software-De...

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11th international conference on Mechatronics and Robotics Engineering, ICMRE 2025

作者： Oh, Sung Bhin Do, Young Soo Lim, Se Jeong Choi, Hyeok Jun Cha, Sung Keun Hong, Hyeong Keun Lim, Seong Hyeon Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798331509293

Modern vehicles are integrated systems of complex software that support advanced features such as autonomous driving and over-the-air updates. Software-defined vehicles (SDVs) are emerging as a future automotive paradigm for managing increasing software complexity by centralizing computing resources and enabling flexible software updates and feature deployment. However, most SDV research is conducted in simulation environments because using real vehicles presents many challenges, including high cost, safety concerns, and implementation difficulties. In this paper, we present the design of an SDV research platform using a 1/5-scale vehicle model to overcome these limitations of SDV research. The platform implements a zone architecture and integrates various embedded systems to replicate the distributed computing environment of a modern vehicle. The platform allows researchers to experiment with different SDV concepts such as distributed computing, OTA updates, middleware, and vehicle software management without the constraints of full-scale vehicle testing. Our design demonstrates the feasibility of using extended vehicles for SDV research and provides insights into platform design for SDV research. © 2025 ieee.

关键词： distributed cloud

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Super Artificial Intelligence Medical Care systems with IoT Wireless sensor

Super Artificial Intelligence Medical Care Systems with IoT ...

引用

2022 ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2022

作者： Mariappan, Ravichandran Manjunath, L. Ramachandran, G. Porkodi, M. Sheela, T. Crystal Crop Protection Ltd. Department of Biotechnology Hyderabad India Cvr College of Engineering Department of Ece Hyderabad India Department of Electronics and Communication Engineering Salem India Sona College of Technology Department of Eee Salem India

ISBN: (纸本)9781665483162

As well as the design and optimised parameters, will be transmitted for the essential information exchange. This research study focuses on integrating WSN architecture. In actuality, many automated systems still require extensive human engagement;for example, a patient may need to visit multiple pharmacies in order to locate a specific sort of drug. A smart inventory system integrating Wireless sensor Networks (WSN), Quick Response Codes (QR), and cloud services (Web) would solve numerous difficulties while also saving money for both patients and stakeholders. What we're attempting to figure out with all of these chores is that we need a speedier, more reliable system to manage operational, repeatable processes. Low-power devices are employed at the architectural level so that each component dissipates less power during signal transmission. By optimising load usage in data transmission depending on application-specific demand, significant electricity can be saved. However, in addition to the aforementioned strategies, using a cognitive power management controller can help IoT-enabled systems save even more power, regardless of application. © 2022 ieee.

关键词： Wireless sensor networks

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Topology Identification Technology for Low-voltage distributed Photovoltaic Distribution Network Lines 3

Topology Identification Technology for Low-voltage Distribut...

引用

3rd international conference on Energy and Electrical Power systems (ICEEPS)

作者： Zheng, Guoquan Zhu, Enguo Zhang, Hailong Liu, Yan Wang, Junlong Liu, Zhe China Elect Power Res Inst Beijing Peoples R China State Grid Hebei Elect Power Beijing Peoples R China

ISBN: (纸本)9798350375145;9798350375138

The large-scale penetration of distributed photovoltaic (PV) power generation systems has brought new challenges to the topology identification and detection of traditional distribution networks. This article mainly studies the topology identification technology (TIT) of distributed PV low-voltage (LV) distribution network lines, aiming to design a topology identification method that can adapt to the dynamic changes of the power grid, have large-scale capacity, and improve system accuracy under the same conditions. At the same time, the data processing speed has been improved. This article first constructs a system model, including node model, edge model, and parameter model. It mathematically represents the topology structure of the power grid using graph theory and designs a topology recognition algorithm based on optimization techniques and state estimation. This algorithm is used to solve the distributed characteristics of power grid topology recognition, the difficulty of data collection, the dynamic diversity of power grid structure, the uncertainty of equipment parameters, the high computational complexity of data processing, and the communication constraints of power grid topology recognition. This algorithm adopts modern programming languages and parallel computing frameworks, making it easy to implement efficiently. The results on the simulation platform show that the highest recall rate for 22 test cases is 93.8%, and the response time for test cases is 425 ms to 980 ms, providing a fast response to the information space of the grid.

关键词： Low-voltage distributed Photovoltaic Distribution Network Topology Identification Technology Simulation Platform Recall Ratio

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Performance Analysis of Greedy and Auction-Based Resource Allocation Algorithms in Ubiquitous computing Environments 32

Performance Analysis of Greedy and Auction-Based Resource Al...

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32nd IFIP/ieee international conference on Very Large Scale Integration, VLSI-SoC 2024

作者： Nagpal, Akshay Jayaram, Vivekananda Krishnappa, Manjunatha Sughaturu Bangad, Nikhil Jagdish Bidkar, Darshan Mohan Kathiriya, Manoj Jayantilal Aarella, Seema G NJ United States Texas TX United States Oracle America Inc CA United States Gartner Inc CT United States University of North Texas TX United States

ISBN: (纸本)9798331539672

In the era of ubiquitous computing, efficient resource allocation is critical to managing the diverse and dynamic environments created by interconnected devices. This paper presents a comprehensive comparative analysis of greedy and auction-based resource allocation algorithms within ubiquitous computing systems. The study examines the performance of these algorithms under three implementation approaches: centralized, decentralized, and hierarchical. We use a process-based discrete-event simulation model to evaluate the algorithms based on key performance metrics, including throughput, average response time, and energy utilization. Our results demonstrate that auction-based algorithms, particularly in a hierarchical implementation, consistently outperform greedy algorithms in both throughput and energy efficiency while maintaining competitive response times. The findings highlight the advantages of auction-based strategies in dynamically adapting to changing conditions and optimizing resource use in complex, decentralized environments. This research contributes valuable insights into optimal resource management strategies for ubiquitous computing, guiding system designers and researchers toward more efficient and scalable solutions. Future work should address the limitations of simplified network and energy models to enhance the applicability of these findings in real-world scenarios. © 2024 ieee.

关键词： Auction-Based Algorithms distributed computing Greedy Algorithms Performance Analysis Resource Allocation Ubiquitous computing

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Reliable Federated Learning for Age Sensitive Mobile Edge computing systems

Reliable Federated Learning for Age Sensitive Mobile Edge Co...

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ieee international conference on Communications (ieee ICC)

作者： Abdellatif, Alaa Awad Allahham, Mhd Saria Khial, Noor Mohamed, Amr Erbad, Aiman Shaban, Khaled Qatar Univ Coll Engn Doha Qatar Queens Univ Sch Comp Kingston ON Canada Hamad Bin Khalifa Univ Coll Sci & Engn Ar Rayyan Qatar

ISBN: (纸本)9781538674628

The conventional approach for Federated Learning (FL) is to train a global model by averaging local models trained on local data sets. However, given the limited computing resources at the mobile-edge nodes, unreliable models may be received from the Edge Nodes (ENs), which can lead to a significant performance degradation in the FL. Thus, this paper proposes a reliable and age sensitive FL framework that captures the dynamic nature of the local data and computing resources at each participating EN. Specifically, we formulate two optimization problems to select the optimal subset of ENs that can upload their local models in each round of the global model training, given a limited learning cost budget. The first problem aims at selecting the most reliable ENs that should cooperate to complete the FL process, while considering stationary data distributions at different ENs. The second problem aims at minimizing the average age of information experienced by each EN while selecting the most reliable ENs, given fast changing data distributions. Efficient solutions are proposed for the two problems with a worst-case linear complexity. Our Results, leveraging a real-world dataset, depict the efficiency of our solutions in obtaining a better performance compared to conventional FL approach.

关键词： Collaborative learning distributed computing Federated learning Age of Information edge computing

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distributed Voltage Regulation of Distribution Network Based on Partition Control 2

Distributed Voltage Regulation of Distribution Network Based...

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2nd international conference on Cyber-Energy systems and Intelligent Energy, ICCSIE 2024

作者： Jine, Wang Hui, Chen Liying, Zhao Guangxin, Zhang School of Electrical Information Changchun University of Architecture and Civil Engineering Changchun City China School of Computer Technology and Engineering Changchun Institute of Technology Changchun City China School of Information and Engineering College of Science & Technology Ningbo University Ningbo City China

ISBN: (纸本)9798350373318

As China's social economy progresses, the amount of equipment in distribution networks continues to grow, leading to increasingly complex system operations. In this environment, traditional centralized control methods consume excessive computing resources and fail to achieve the processing speeds required by modern intelligent distribution networks. To address these challenges, this article introduces the concept of electrical distance to segment the distribution network and proposes voltage regulation algorithms based on the alternating direction multiplier method and dual ascent method for efficient distributed voltage regulation. © 2024 ieee.

关键词： DC distribution systems

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