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

共 149974 条记录，以下是741-750 订阅

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Exploring the linkage between partition-based distributed extended Kalman filter and distributed full-information estimation 7

Exploring the linkage between partition-based distributed ex...

引用

ieee 7th international conference on Industrial Cyber-Physical systems (ICPS)

作者： Li, Xiaojie Yin, Xunyuan Nanyang Technol Univ Sch Chem Chem Engn & Biotechnol 62 Nanyang Dr Singapore 637459 Singapore

ISBN: (纸本)9798350363029;9798350363012

In this paper, we revisit a partition-based distributed extended Kalman filter (DEKF) method proposed in [1] for continuous-time nonlinear systems. Our objective is to offer a comprehensive perspective on the development of this DEKF method, elucidating its relationship with partition-based distributed full-information estimation within a discrete-time linear framework. Specifically, we present a partition-based distributed full-information estimation formulation for discrete-time linear systems. We derive an analytical solution for this full-information estimation problem which is in the form of a partition-based distributed Kalman filter (DKF). The DKF approach is extended to address nonlinear systems through successive linearization of nonlinear subsystem models, and a discrete-time distributed extended Kalman filter (DEKF) approach is derived. We compare the derived discrete-time DEKF with the continuous-time DEKF approach in [1] to reveal the connection between the DEKF approach in [1] and the distributed full-information estimation in a discrete-time context. A simulated process is utilized to verify the effectiveness and assess the performance of the distributed extended Kalman filter.

关键词： distributed state estimation partition-based framework extended Kalman filter nonlinear process

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Helping Faculty Teach Software Performance Engineering

Helping Faculty Teach Software Performance Engineering

引用

1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Owens, John D. Hoppe, Bruce Univ Calif Davis Dept Elect & Comp Engr Davis CA 95616 USA Connect Associates Arlington MA USA

ISBN: (纸本)9798350364613;9798350364606

Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with an existing interest in this course material. These discussions revealed an enthusiasm for making software pertimmance engineering a more prominent part of a curriculum for computer scientists and engineers. Here, we discuss how MIT's longstanding efforts in this area may serve as a launching point for community development of a software performance engineering curriculum, challenges in and solutions for providing the necessary infrastructure to universities, and future directions.

关键词： Performance distributed parallel cluster computing data structures and algorithms software performance engineering

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A Hybrid Communication Approach for Metadata Exchange in Geo-distributed Fog Environments 16

A Hybrid Communication Approach for Metadata Exchange in Geo...

引用

16th ieee/ACM international conference on Utility and Cloud computing (UCC) / 10th ieee/ACM international conference on Big Data computing, Applications and Technologies (BDCAT)

作者： Kruber, Marvin Pfandzelter, Tobias Bermbach, David TU Berlin Berlin Germany ECDF Berlin Germany

ISBN: (纸本)9798400702341

Metadata exchange is crucial for efficient geo-distributed fog computing. Existing solutions for metadata exchange overlook geo-awareness or lack adequate failure tolerance. We propose HFCS, a novel hybrid communication system that combines hierarchical and peer-to-peer elements, along with edge pools. HFCS utilizes a gossip protocol for dynamic metadata exchange. In simulation, we investigate the impact of node density and edge pool size on HFCS performance. We observe a performance improvement for clustered node distributions, aligning well with real-world scenarios. HFCS outperforms a hierarchical and a P2P approach in task fulfillment at a slight cost to failure detection.

关键词： fog computing metadata exchange hybrid communication

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Parallel computing Optimization of Tourism Big Data based on Crawler Programs 1

Parallel Computing Optimization of Tourism Big Data based on...

引用

1st international conference on Intelligent systems and Computational Networks, ICISCN 2025

作者： Zhou, Xiaoyu Wuhan Donghu University School of Management Hubei Wuhan China

ISBN: (纸本)9798331529246

With the rapid development of the tourism industry, traditional tourism methods are undergoing significant transformation, and online tourism is gradually becoming a new highlight in the market. However, faced with the challenges of big data, online tourism data experiences tremendous pressure in terms of storage, computation, and management, and the issue of information overload seriously affects the user experience. Therefore, there is an urgent need for innovative platforms and recommendation algorithms to optimize the screening and recommendation of tourism information. This paper proposes an optimization scheme based on the Spark cloud computing platform to improve the efficiency of tourism data processing. First, utilizing Spark's distributed computing and memory management capabilities, tourism data can be stored and processed in a distributed manner, thus accelerating the computation speed of recommendation algorithms. Secondly, a Python-written crawler program is used to obtain real tourism data, including user ratings and comments on attractions, to evaluate the effectiveness of the improved algorithm. Finally, a weighted algorithm combining the LDA topic model is proposed. This algorithm analyzes the topic distribution of comment texts and weights the comments based on user ratings, calculating the predicted score for unrated attractions for the target user, thereby achieving accurate attraction recommendations. The experimental results show that the algorithm proposed in this study demonstrates significant advantages in prediction accuracy. © 2025 ieee.

关键词： Cloud platforms

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Evaluating an Analog Main Memory Architecture for All-Analog In-Memory computing Accelerators 6

Evaluating an Analog Main Memory Architecture for All-Analog...

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6th international conference on AI Circuits and systems (AICAS)

作者： Adam, Kazybek Monga, Dipesh Numan, Omar Singh, Gaurav Halonen, Kari Andraud, Martin Aalto Univ Dept Elect & Nanoengn Espoo Finland UC Louvain ICTEAM Louvain Belgium

ISBN: (纸本)9798350383638;9798350383645

Analog in memory computing (IMC) has emerged as a promising method to accelerate deep neural networks (DNNs) on hardware efficiently. Yet, analog computation typically focuses on the multiply and accumulate operation, while other operations are still being computed digitally. Hence, these mixed-signal IMC cores require extensive use of data converters, which can take a third of the total energy and area consumption. Alternatively, all-analog DNN computation is possible but requires increasingly challenging analog storage solutions, due to noise and leakage of advanced technologies. To enable all-analog DNN acceleration, this work demonstrates a feasible IMC architecture using an efficient analog main memory (AMM) cell. The proposed AMM cell is 42x and 5x more power and area efficient than a baseline analog storage cell. An all-analog architecture using this cell achieves potential efficiency gains of 15x compared with a mixed-signal IMC core using data converters.

关键词： Analog in memory computing Analog Memory

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A Dynamic Weighting Strategy to Mitigate Worker Node Failure in distributed Deep Learning

A Dynamic Weighting Strategy to Mitigate Worker Node Failure...

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2024 ieee High Performance Extreme computing conference, HPEC 2024

作者： Xu, Yuesheng Carr, Arielle Lehigh University Bethlehem United States

ISBN: (纸本)9798350387131

The increasing complexity of deep learning models and the demand for processing vast amounts of data make the utilization of large-scale distributed systems for efficient training essential. These systems, however, face significant challenges such as communication overhead, hardware limitations, and node failure. This paper investigates various optimization techniques in distributed deep learning, including Elastic Averaging SGD (EASGD) and the second-order method AdaHessian. We propose a dynamic weighting strategy to mitigate the problem of straggler nodes due to failure, enhancing the performance and efficiency of the overall training process. We conduct experiments with different numbers of workers and communication periods to demonstrate improved convergence rates and test performance using our strategy. © 2024 ieee.

关键词： Adversarial machine learning

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A Design and Implementation of Decentralized Edge Intelligent LoRa Gateway 26

A Design and Implementation of Decentralized Edge Intelligen...

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26th ieee international Symposium on Real-Time distributed computing (ISORC)

作者： Zhang, Xiaobo Huang, Zhangqin Beijing Univ Technol Beijing Engn Res Ctr IoT Software & Syst Beijing Peoples R China

ISBN: (纸本)9798350339024

As a narrowband communication technology, Long Range (LoRa) contributes to the long development of Internet of Things (IoT) applications. The LoRa gateway plays an important role in the IoT transport layer, and security and efficiency are the key issues of current research. On the one hand, in the centralized working model of IoT systems built by traditional LoRa gateways, all the data generated and reported by end devices are processed and stored in cloud servers, which are susceptible to security issues such as data loss and data falsification. On the other hand, edge computing, as an innovative approach that brings data processing and storage closer to the endpoints, can create a decentralized security infrastructure for LoRa gateway systems, resulting in an edge intelligent IoT working model. Although this paradigm delivers unique features and improved quality of service (QoS), installing IoT applications at LoRa gateways with limited computing and memory capabilities presents considerable obstacles. To address this challenge, an edge intelligent LoRa gateway is designed and implemented in this paper. Firstly, we developed an edge intelligent LoRa gateway prototype on an FPGA-based embedded hardware system. Then, we proposed Latency-Aware Algorithm (LAA) can greatly improve the reliability of the network system by using a distributed edge computing network technology that can achieve maintenance operations such as detection, repair, and replacement of failures of edge nodes in the network. Finally, many experiments were conducted to evaluate the performance of the proposed edge-intelligent LoRa gateway. The results indicate that the proposed edge intelligent LoRa gateway is more effective in latency-aware in IoT applications, while greatly ensuring system availability and IoT network reliability.

关键词： LoRa gateway edge intelligent computing Internet of Things embedded system distributed computing

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CCacheSim: A Circuit-Architecture Cross-Level Simulation Framework for SRAM-Based In-Cache computing System Evaluation 42

CCacheSim: A Circuit-Architecture Cross-Level Simulation Fra...

引用

42nd international conference on Computer Design

作者： Zhong, Baiqing Wang, Mingyu Zhang, Yicong Li, Xiaojie Yu, Zhiyi Sun Yat Sen Univ Sch Microelect Sci & Technol Guangzhou Peoples R China

ISBN: (纸本)9798350380415;9798350380408

SRAM-based Compute-In-Memory (CIM) circuits have demonstrated significant performance and energy efficiency advantages. Although numerous frameworks or tools have emerged for simulating CIM-based systems, most frameworks are tailored for specific DNN accelerators and rarely consider SRAM-CIM solutions in general processor systems because it is difficult to establish an effective mechanism to build the CIM data path to integrate the SRAM-CIM module that is tightly coupled with the cache hierarchy into the system. To address this problem, we propose a circuit-architecture cross-level simulation framework named CCacheSim for in-cache computing system. CCacheSim integrates the simulation of SRAM-CIM circuit timing and energy consumption characteristics, providing circuit-level accuracy evaluation support for in-cache computing system simulations. For the circuit level, the SRAM-CIM model can automatically generate a circuit-level netlist and conduct accurate simulation through corresponding configurations, thus balancing accuracy and agility for early design exploration. For the architectural level, to efficiently support the portable integration of SRAM-CIM module to in-cache computing system, a configurable hardware programming interface is implemented within the cache model to manage the interaction of the control stream between processor and cache for CIM tasks. Moreover, a request queue based access mechanism is proposed to ensure the completeness of the operands required by CIM tasks. To validate the proposed framework, CCacheSim is implemented to simulate varying configurations of in-cache computing systems and SRAM-CIM modules. The results prove that CCacheSim can conduct accurate performance and energy consumption evaluation for given processor architecture with given CIM module. CCacheSim can support flexible and effective design space exploration for in-cache computing system.

关键词： Compute-In-Memory(CIM) SRAM in-cache computing simulation framework

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An Open Spatial computing Platform 2

An Open Spatial Computing Platform

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2024 international conference on Metaverse computing, Networking, and Application

作者： Soros, Gabor Jackson, James Vogt, Michael Salazar, Mikel Kadlubsky, Alina Vinje, Jan-Erik Open AR Cloud Nokia Bell Labs Budapest Hungary Open AR Cloud Austin TX USA Open AR Cloud Neubulach Germany Open AR Cloud IFE Halden Halden Norway Open AR Cloud Hamburg Germany Open AR Cloud Oslo Norway

ISBN: (纸本)9798331516000;9798331515997

Spatial computing has emerged as a potential new stage for personal and collaborative computing, however, existing systems are limited to small scale and/or are locked into proprietary silos. We present a fully open, scalable and distributed spatial computing platform, which can even bridge existing solutions. Drawing inspiration from the World Wide Web, we propose extensible protocols for discovering spatial services and spatial contents in a geographic area, representing position and orientation of real and virtual cameras and objects, exchanging content records, and interfacing with various spatial computing services such as localization. We present the design choices and a reference implementation of the platform components together with a reference client based on WebXR. We demonstrate the usage of the platform in multiple testbeds and application scenarios. We develop the whole platform as open source to foster further research on large-scale spatial computing.

关键词： Mixed/augmented reality Ubiquitous and mobile computing systems and tools Location based services

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Edge Device Selection For Industrial IoT Task Offloading In Mobile Edge computing

Edge Device Selection For Industrial IoT Task Offloading In ...

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

作者： Sharma, Megha Tomar, Abhinav Hazra, Abhishek Akhter, Zaid Dhangar, Daksh Singh, Rahul Kumar Aletaji Subhas Univ Technol New Delhi Dept Comp Sci & Engn New Delhi 110078 India Indian Inst Informat Technol Sri City Dept Comp Sci & Engn Sri City 517646 India

ISBN: (纸本)9798350349603;9798350349597

In the realm of Mobile Edge computing (MEC), mobile devices have the option to transfer their tasks to edge servers for processing, thereby significantly diminishing task completion duration and reducing the energy consumption of mobile devices. This offloading mechanism optimizes resource utilisation and enhances overall efficiency by leveraging the computational capabilities of nearby edge servers. This paper addresses the issue of efficient task offloading from mobile devices to edge servers in resource-constrained Industrial Internet of Things (IIoT) heterogenous networks, focusing on minimising energy consumption and heterogenous network delay. The methodology involves checking the matching feasibility using Hall's Marriage Theorem and employing a server selection algorithm for task assignment. The results show that the proposed approach minimizes energy consumption and overall time delay compared to standard algorithms. The implications include the potential for improving various QoS factors in future research.

关键词： Task Offloading Edge computing Energy Efficiency IIoT heterogenous networks Mobile Devices Edge Server Allocation

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