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

共 30781 条记录，以下是1001-1010 订阅

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Detection and Classification of Human Activities using distributed Sensing of Environmental Vibrations

Detection and Classification of Human Activities using Distr...

引用

ieee international conference on Omni-Layer Intelligent systems (ieee COINS)

作者： Koch, Marcel Schlenke, Fabian Kohlmorgen, Fabian Kuller, Markus Bauer, Joerg Woehrle, Hendrik Dortmund Univ Appl Sci & Arts Dept Informat Technol Dortmund Germany

ISBN: (数字)9781665483568

ISBN: (纸本)9781665483568

The recognition of human activities in a smart home is an essential prerequisite in order to derive typical behaviors and needs of the inhabitants and adapt the functions of the smart home to them. Different sensor modalities, such as video or audio data in combination with machine learning methods can be used for this purpose. However, the use of video and audio data is associated with a strong infringement on the privacy of the inhabitants. In this paper, we present an alternative approach that uses vibrational data that is acquired by stationary wall-mounted sensors to detect a specific set of inhabitant activities using machine learning. We compare different neural-network based time series classifiers and show that is possible to detect the selected activities with up to 95% accuracy.

关键词： IoT Machine Learning Human Activity Recognition Edge computing

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An End-to-End Framework for Benchmarking Edge-Cloud Cluster Management Techniques 10

An End-to-End Framework for Benchmarking Edge-Cloud Cluster ...

引用

10th ieee international conference on Cloud Engineering (IC2E)

作者： Raith, Philipp Rausch, Thomas Prueller, Paul Furutanpey, Alireza Dustdar, Schahram TU Wien Distributed Syst Grp Vienna Austria

ISBN: (数字)9781665491150

ISBN: (纸本)9781665491150

This paper presents a framework for defining, performing, and analyzing distributed load testing experiments for benchmarking edge-cloud clusters. This end-to-end workflow helps researchers build reproducible environments to evaluate cluster management techniques. Our implementation extends the open source tool Galileo by adding support for distributed execution on Kubernetes clusters, additional system monitoring instruments, as well as out-of-the box experiment workloads. We focus on providing tools that run across popular CPU architectures and provide a set of representative workloads, such as edge AI functions. We demonstrate our framework's capabilities in a set of experiments based on use cases commonly found in edge computing systems research. Additionally, we show that the resource usage of our system is minimal and that it can run on resource-constrained devices.

关键词： Edge computing Cloud computing Benchmarking Cluster management

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Improving the MPI Remote Memory Access Model for distributed-memory systems by Implementing One-sided Broadcast 27

Improving the MPI Remote Memory Access Model for Distributed...

引用

27th international conference on Soft computing and Measurements, SCM 2024

作者： Abuelsoud, Mohamed Paznikov, Aleksej A. Saint Petersburg Electrotechnical University 'LETI' Department of Computer Science and Engineering Saint Petersburg Russia

ISBN: (纸本)9798350363708

Currently, processing large volumes of expanding data efficiently and consistently is a significant challenge. Traditional distributed-memory high-performance computers (HPC) based on message-passing model struggle with inherent synchronization difficulties, limiting their ability to keep pace. Remote Memory Access (RMA, also known as one-sided MPI communications) allows a process to directly read from or write to the memory of another process, bypassing the need for message exchange. Unfortunately, there is no collective operation interface in the current MPI RMA standard. However, RMA has the potential to reduce synchronization costs by enabling concurrent access to shared data structures, distributed among MPI processes' memories. Existing onesided MPI standards offer a linear interface only that hampers parallelization and far from efficient. To bridge this gap, we propose an algorithm design for efficient collective (parallelizable) operations in the RMA paradigm. Our study primarily examines the benefits of collective operations using the broadcast algorithm as an example. Our implementations surpass traditional methods, demonstrating the promising potential of this technique, as more performance tests indicate. © 2024 ieee.

关键词： Parallel programming

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SmartPipe: Intelligently Freezing Layers in Pipeline Parallelism for distributed DNN Training 29

SmartPipe: Intelligently Freezing Layers in Pipeline Paralle...

引用

29th ieee international conference on Parallel and distributed systems, ICPADS 2023

作者： Niknami, Nadia Sawwan, Abdalaziz Wu, Jie Temple University Center for Networked Computing United States

ISBN: (纸本)9798350330717

Deep Neural Network (DNN) models have been widely utilized in various applications. However, the growing complexity of DNNs has led to increased challenges and prolonged training durations. Despite the availability of high-performance computing systems, certain DNNs still require several days for successful training. This study aims to address this issue by proposing a method for significantly reducing the training time of deep learning models while maintaining test accuracy. Existing approaches primarily concentrate on optimizing training efficiency through computational and communication overlap/scheduling. In contrast, this research takes a step further by inspiring transfer learning. Transfer learning is a useful way to quickly retrain a model on new data without having to retrain the entire network. During transfer learning, the first layers of the network are frozen while leaving the end layers open to modification. By doing so, computation and communication requirements in these frozen layers are eliminated. This intelligent approach involves freezing some of the specific DNN layers and allocating resources to the remaining active layers during the training process, thereby minimizing DNN training time. To achieve this objective, we propose an intelligently freezing DNN using pipeline parallelism. Through trace-based simulation results, our scheme has demonstrated its effectiveness in efficiently reducing the time cost of a training iteration. © 2023 ieee.

关键词： DNN training gradient descent intelligent freezing machine learning neural networks pipeline

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Bring the BitCODE - Moving Compute and Data in distributed Heterogeneous systems

Bring the BitCODE - Moving Compute and Data in Distributed H...

引用

ieee international conference on Cluster computing (CLUSTER)

作者： Lu, Wenbin Pena, Luis E. Shamis, Pavel Churavy, Valentin Chapman, Barbara Poole, Steve SUNY Stony Brook Stony Brook NY 11794 USA Arm Res Austin TX USA MIT 77 Massachusetts Ave Cambridge MA 02139 USA Los Alamos Natl Lab Los Alamos NM USA

ISBN: (数字)9781665498562

ISBN: (纸本)9781665498562

In this paper, we present a framework for moving compute and data between processing elements in a distributed heterogeneous system. The implementation of the framework is based on the LLVM compiler toolchain combined with the UCX communication framework. The framework can generate binary machine code or LLVM bitcode for multiple CPU architectures and move the code to remote machines while dynamically optimizing and linking the code on the target platform. The remotely injected code can recursively propagate itself to other remote machines or generate new code. The goal of this paper is threefold: (a) to present an architecture and implementation of the framework that provides essential infrastructure to program a new class of disaggregated systems wherein heterogeneous programming elements such as compute nodes and data processing units (DPUs) are distributed across the system, (b) to demonstrate how the framework can be integrated with modern, high-level programming languages such as Julia, and (c) to demonstrate and evaluate a new class of eXtended Remote Direct Memory Access (X-RDMA) communication operations that are enabled by this framework. To evaluate the capabilities of the framework, we used a cluster with Fujitsu CPUs and heterogeneous cluster with Intel CPUs and BlueField-2 DPUs interconnected using high-performance RDMA fabric. We demonstrated an X-RDMA pointer chase application that outperforms an RDMA GET-based implementation by 70% and is as fast as Active Messages, but does not require function predeployment on remote platforms.

关键词： distributed systems SmartNIC DPU Programming Models HPC

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Towards A Massive-scale distributed Neighborhood Graph Construction

Towards A Massive-scale Distributed Neighborhood Graph Const...

引用

2023 international conference on High Performance computing, Network, Storage, and Analysis, SC Workshops 2023

作者： Iwabuchi, Keita Steil, Trevor Priest, Benjamin Pearce, Roger Sanders, Geoffrey Lawrence Livermore National Laboratory LivermoreCA United States

ISBN: (纸本)9798400707858

Graph-based approximate nearest neighbor algorithms have shown high performance and quality. However, such approaches require a large amount of memory and still take a long time to construct high-quality nearest neighbor graphs (NNGs). Using distributed memory systems is important when data is large or a shorter indexing time is desired. We develop a distributed memory version of NN-Descent, a widely known graph-based ANN algorithm, closely following algorithmic advances by PyNN-Descent authors. Our distributed NN-Descent (DNND) is built on top of MPI and leverages two existing high-performance computing libraries: YGM (an asynchronous communication library) and Metall (a persistent memory allocator). We evaluate the performance of DNND on an HPC system using billion-scale datasets, demonstrating that our approach shows high performance and strong scaling and has great potential for developing massive-scale NNG frameworks. © 2023 Owner/Author.

关键词： Nearest neighbor search

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Certain Investigation of Optimization Methods of sensor Nodes in Biomedical Recording systems 9

Certain Investigation of Optimization Methods of Sensor Node...

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9th international conference on Advanced computing and Communication systems, ICACCS 2023

作者： Ashokkumar, N. Pappa, C. Kanmani Siva Kumar, A. Srinivasan, Dhamodharan Vijay, M.M. Mohan Babu University Department of ECE Tirupati India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of ECE Tamilnadu Chennai India SRM Institute of Science and Technology Department of Data Science and Business Systems Chennai India Sri Eshwar College of Engineering Department of Computer and Communication Engineering Tamilnadu Coimbatore India SCAD College of Engineering and Technology Department of ECE Tirunelveli India

ISBN: (纸本)9798350397376

Biosensors will monitor a patient's physiological signals (ECG, EEG, etc.) and send an alarm as soon as irregularities are discovered. Downsized biomedical sensors are the focus of this article, which explores innovative circuit approaches for miniaturised sensors. In order to demonstrate the proposed biomedical compression engine, ECG compression was applied and assessed. A MIP (mixed-integer programming model) is used to represent and solve the clustering issue based on the power consumption analysis. It follows that an architectural model that may be used to design ECG monitoring systems has been provided, as well as an in-depth study of the ECG monitoring system's value chain and a complete evaluation of relevant literature based on an expert classification. Time synchronisation and signal synthesis are the two stages of the distributed cooperative sensing algorithm's execution of ECG signal gathering. This method uses the mutation probability of each solution to prevent local convergence. © 2023 ieee.

关键词： Electrocardiograms

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A Low-Cost Approach for Robot-to-Robot Cooperation 15

A Low-Cost Approach for Robot-to-Robot Cooperation

引用

15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Lopamudra Dhami, Sukhdeep Singh Kumar, Rajesh National Institute of Technical Teachers Training & Research Mechanical Engineering Department Chandigarh India Punjab Engineering College Mechanical Engineering Department Chandigarh India

ISBN: (纸本)9798350370249

Industrial robots have become an indispensable part of industry owing to constant increase in performance, accompanied by a steady decline in prices. Availability of robots having high dexterity, multitude of sensors and intelligent controllers opened the way to new paradigms such as robot-to-robot cooperation and human-robot collaboration. Integration of such robotic systems in industry increases efficiency, flexibility, safety and adaptability. However, establishing communication between robots for collaborative or cooperative working is a complicated task requiring either to deploy a centralized control systems to coordinate the actions of multiple robots or to use communication protocols to send coordinate information between robots. In the present paper, a low-cost approach is presented for cooperative working of two articulated robots in which an external IMU sensor provides the joint movements of the master robot to a generic controller which further controls the slave robot joint motors accordingly. Off the shelf available components were used for experimentation. The results validated the proposed hardware solution and algorithm for achieving cooperation between two robots having different types of controllers without any hardware/software interface. © 2024 ieee.

关键词： Arduino microcontroller board IMU sensor MATLAB robot-robot cooperation

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Development of Wireless Optical Communication Link for Secure Underwater Communication

Development of Wireless Optical Communication Link for Secur...

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2024 international conference on Integrated Circuits, Communication, and computing systems, ICIC3S 2024

作者： Yadav, Ajay Dev Kumawat, Mahesh Mukherjee, Rahul Kumar, Ashok Bennett University Electronics and Communication Engineering Department Greater Noida India

ISBN: (纸本)9798350364088

In this research paper, we have developed an underwater wireless optical communication (UWOC) system. For faster data rates, UWOC emerges as a key enabler in enhancing communication within underwater sensor networks (UWSNs). In the proposed work, a blue colored LED is controlled by microcontroller for data transmission. The data pulses are passed through the water. At the receiver, photo-diode is used to detect the pulses. Further, optical code division multiple access (OCDMA) codes have been used for emulating the multi-user system at the transmitter. The simulation is performed on Vivado. For single user system, the data transmission and reception has been implemented using Nexsys 4 DDR field programmable gate array (FPGA) board. In future, the multi-user communication system with OCDMA will be implemented on the Nexsys 4 DDR FPGA board. © 2024 ieee.

关键词： Wireless sensor networks

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Keynote: Engineering the New Fabric of the distributed Compute Continuum

Keynote: Engineering the New Fabric of the Distributed Compu...

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20th ieee international conference on Pervasive computing and Communications (ieee PerCom)

作者： Dustdar, Schahram TU Wien Distributed Syst Grp Vienna Austria

ISBN: (纸本)9781665416436

As humans, things, software and AI continue to become the entangled fabric of distributed systems, systems engineers and researchers are facing novel challenges. In this talk, we analyze the role of IoT, Edge, and Cloud, as well as AI in the co-evolution of distributed systems for the new decade. We identify challenges and discuss a roadmap that these new distributed systems have to address. We take a closer look at how a cyber-physical fabric will be complemented by AI operationalization to enable seamless end-to-end distributed systems.

关键词： Pervasive computing conferences Fabrics Software Artificial intelligence

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