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检索条件"任意字段=10th International Conference on Parallel and Distributed Computing, Applications and Technologies"

共 1764 条记录，以下是11-20 订阅

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Proceeding Sixth international conference on parallel and distributed computing, applications and technologies PDCAT 2005

Proceeding Sixth International Conference on Parallel and Di...

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6th international conference on parallel and distributed computing, applications and technologies, PDCAT 2005

ISBN: (纸本)0769524052

the proceedings contain 249 papers. the topics discussed include: future technological challenges for high performance computers;an agile programming model for grid end users;scalable and practical nonblocking switching networks;an efficient distributed broadcasting algorithm for wireless ad hoc networks;a ring removal movement-based mobility location update scheme;a scalable security architecture for grid;a novel security model based on virtual organization for grid;a simple process calculus for the analysis of security protocols;the architecture of the large-scale distributed intrusion detection system;construction of a prototype of a volume communications environment;study of channel characteristics of power line communications networks;the maximal rates of more general complex orthogonal designs;and random walk routing for wireless sensor networks.

关键词： distributed computer systems

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Proceedings of the 15th international conference on Cloud computing and Services Science, CLOSER 2025

Proceedings of the 15th International Conference on Cloud Co...

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15th international conference on Cloud computing and Services Science, CLOSER 2025

ISBN: (纸本)9789897587474

the proceedings contain 28 papers. the topics discussed include: performance and usability implications of multiplatform and WebAssembly containers;operations patterns for hybrid quantum applications;optimization of cloud-native application execution over the edge cloud continuum enabled by DVFS;energy-aware node selection for cloud-based parallel workloads with machine learning and infrastructure as code;security-aware allocation of replicated data in distributed storage systems;performance analysis of mdx ii: a next-generation cloud platform for cross-disciplinary data science research;data orchestration platform for AI workflows execution across computing continuum;framework for decentralized data strategies in virtual banking: navigating scalability, innovation, and regulatory challenges in thailand;and anomaly detection for partially observable container systems based on architecture profiling.

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Proceedlngs - Seventh international conference on parallel and distributed computing, applications and technologies, PDCAT 2006

Proceedlngs - Seventh International Conference on Parallel a...

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7th international conference on parallel and distributed computing, applications and technologies, PDCAT 2006

ISBN: (纸本)0769527361

the proceedings contain 109 papers. the topics discussed include: an intrusion detection architecture for ad hoc network based on artificial immune system;conditional fault-tolerant hamiltonicity of twisted cubes;conditional fault-tolerant hamiltonicity of star graphs;merging source and shared trees multicast in MPLS networks;java annotated concurrency based on the concurrent package;a high-efficiency vector interpolator using redundant CORDIC arithmetic in power-aware 3D graphics rendering;error-diffusion kernel estimation using least squares;remote sensing images classification/data fusion using distance weighted multiple classifiers systems;image encryption and decryption using SCAN methodology;an attribute-based access control model for web services;administrative usage control model for secure interoperability;an efficient assignment of transmission opportunity in qos guaranteed wireless LAN;and k-MCore for multicasting on mobile ad hoc networks.

关键词： parallel processing systems

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Containerized Data-Flow Processing for Scalable Real-Time Analytics on Edge Devices 25th

Containerized Data-Flow Processing for Scalable Real-Time A...

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25th international conference on parallel and distributed computing, applications and technologies, PDCAT 2024

作者： HoseinyFarahabady, MohammadReza Y. Zomaya, Albert School of Computer Science Center for Distributed and High Performance Computing The University of Sydney SydneyNSW2006 Australia

ISBN: (纸本)9789819642069

the increasing demand for real-time data analysis in Internet of things (IoT) ecosystems has created several challenges, particularly in environments where resources are limited, and minimizing data processing latency is critical. this paper investigates the use of Linux Containerization (LXC) as a lightweight, resource-efficient alternative to traditional virtual machine managers for accelerating data-flow processing applications. We propose an architecture that integrates Linux Containerization (LXC) with a Proportional-Integral-Derivative (PID) controller to dynamically manage I/O resource allocation, ensuring Quality of Service (QoS) for I/O-intensive data analytics workloads. the proposed PID controller continuously monitors system performance and dynamically adjusts I/O resource allocation to mitigate performance degradation. through a series of experiments, we demonstrate that LXC-based solutions outperform traditional methods in managing I/O-intensive data analytics workloads in IoT and edge ecosystems. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quality of service

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A Comparative Evaluation of Zero Knowledge Proof Techniques

A Comparative Evaluation of Zero Knowledge Proof Techniques

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10th international conference on Internet of things, Big Data and Security, IoTBDS 2025

作者： Rostamkolaei Motlagh, Seyed Mohsen Pahl, Claus Barzegar, Hamid R. El Ioini, Nabil Free University of Bozen-Bolzano Bolzano39100 Italy University of Nottingham Semenyih43500 Malaysia

ISBN: (纸本)9789897587504

Common to many distributed systems such as the Internet-of-things (IoT) is decentralisation, often with a growing number of devices with diverse computational capabilities and security requirements. If integrated into critical applications, ensuring secure communication and data integrity is critical. In particular, privacy and security concerns are growing with the rise of these architectures. Zero-Knowledge Proof (ZKP) techniques are solutions to improve security without compromising on privacy. While the advantages of ZKP techniques are well-documented, it is important to consider the inherent limitations of these distributed environments, such as restricted processing power, memory capacity, and energy constraints, when aiming to solve security concerns. Here, we select two prominent ZKP techniques, Bulletproof and zk-STARK, and experimentally compare a number of their variants for a set of architecture-specific assessment criteria. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： parallel processing systems

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I/O Latency Management in Private Cloud Infrastructures 25th

I/O Latency Management in Private Cloud Infrastructures

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25th international conference on parallel and distributed computing, applications and technologies, PDCAT 2024

作者： HoseinyFarahabady, MohammadReza Zomaya, Albert Y. School of Computer Science Center for Distributed and High Performance Computing The University of Sydney SydneyNSW Australia

ISBN: (纸本)9789819642069

this paper examines how co-locating multiple VMs on a single physical server with shared storage impacts I/O performance, specifically focusing on latency of I/O operations, and the overall throughput. We introduce a Proportional-Integral-Derivative (PID) controller to maintain I/O latency close to a predefined target by dynamically adjusting I/O requests based on real-time measurements. through a series of experiments, we evaluated the effectiveness of our PID controller in comparison to VMware’s default QoS mechanism within a private cloud environment. the results indicate that the PID controller significantly enhances performance for latency-critical workloads, achieving substantially higher compliance with latency targets compared to the default mechanism. However, this prioritization of high-priority VMs comes at the expense of increased latency and reduced throughput for lower-priority workloads during periods of I/O contention. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： three term control systems

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Towards Optimizing Cost and Performance for parallel Workloads in Cloud computing

Towards Optimizing Cost and Performance for Parallel Workloa...

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15th international conference on Cloud computing and Services Science, CLOSER 2025

作者： Maas, William Rossi, Fábio Diniz Luizelli, Marcelo C. Navaux, Philippe O.A. Lorenzon, Arthur F. Institute of Informatics Federal University of Rio Grande do Sul Brazil Federal Institute Farroupilha Campus Alegrete Brazil Federal University of Pampa Campus Alegrete Brazil

ISBN: (纸本)9789897587474

the growing popularity of data-intensive applications in cloud computing necessitates a cost-effective approach to harnessing distributed processing capabilities. However, the wide variety of instance types and configurations available can lead to substantial costs if not selected based on the parallel workload requirements, such as CPU and memory usage and thread scalability. this situation underscores the need for scalable and economical infrastructure that effectively balances parallel workloads’ performance and expenses. To tackle this issue, this paper comprehensively analyzes performance, costs, and trade-offs across 18 parallel workloads utilizing 52 high-performance computing (HPC) optimized instances from three leading cloud providers. Our findings reveal that no single instance type can simultaneously offer the best performance and the lowest costs across all workloads. Instances that excel in performance do not always provide the best cost efficiency, while the most affordable options often struggle to deliver adequate performance. Moreover, we demonstrate that by customizing instance selection to meet the specific needs of each workload, users can achieve up to 81.2% higher performance and reduce costs by 95.5% compared to using a single instance type for every workload. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： parallel processing systems

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Advancing Evasion: distributed Backdoor Attacks in Federated Learning 25th

Advancing Evasion: Distributed Backdoor Attacks in Federate...

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25th international conference on parallel and distributed computing, applications and technologies, PDCAT 2024

作者： Wang, Jian Shen, Hong Ke, Wei Faculty of Applied Sciences Macao Polytechnic University China School of Engineering and Technology Central Queensland University Rockhampton Australia School of Software Technology Guangzhou Institute of Software Guangzhou China

ISBN: (纸本)9789819642069

Federated Learning (FL) is vulnerable to backdoor attacks through data poisoning if the data is not scrutinized, as malicious participants can inject backdoor triggers in normal samples, leading to poisoned updates. distributed backdoor attacks pose a greater threat than centralized ones, as they often use fixed pixel blocks as triggers, increasing the risk of detection. this paper presents a novel distributed backdoor attack strategy that leverages edge structure poisoning to circumvent existing defense mechanisms, employing a distributed poisoning strategy to evade current defense mechanisms, thereby enhancing the stealth of the attack. Experimental results on multiple benchmark datasets demonstrate that this method is more effective and stealthy compared to other backdoor attack methods. Furthermore, this paper also proposes targeted defense strategies based on the experimental results, offering a new perspective on the security of FL systems. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Out-of-Memory GPU Sorting Using Asynchronous CUDA Streams 25th

Out-of-Memory GPU Sorting Using Asynchronous CUDA Streams

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25th international conference on parallel and distributed computing, applications and technologies, PDCAT 2024

作者： HoseinyFarahabady, MohammadReza Zomaya, Albert Y. School of Computer Science Center for Distributed and High Performance Computing The University of Sydney SydneyNSW Australia

ISBN: (纸本)9789819642069

Graphics Processing Units (GPUs) are widely used as powerful hardware accelerators for data-intensive tasks. However, their efficacy can be hindered by constraints in device memory and data transfer speeds via the PCI-E link. this paper explores the use of GPUs for executing scalable sorting operations that exceeds the GPU’s global memory by a factor of at least two orders of magnitude. To address this challenge, we leverage the power of NVIDIA’s asynchronous CUDA streams. Our solution enhances GPU performance by implementing a pipeline model to offload sorting operations from the Solid-State Drive (SSD) to GPU memory via the host’s main memory. this strategy maximizes the multiway concurrency level to reduce the overhead associated with data transfer within the GPU memory hierarchy. We perform extensive performance evaluations by sorting 128 billion data elements initially stored on an external NVMe SSD. the results confirm the effectiveness of our approach, showcasing a speed-up of 4.3× compared to the results for CPU-based out-of-memory sorting of skewed data based on Intel’s threading Building Blocks (TBB) sorting algorithm. Our results include the cost of transfer times to and from the main memory, a factor often overlooked in similar studies. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graphics processing unit

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Fast Approximation for Scheduling Malleable Jobs on parallel Batch Machines with Rejection 25th

Fast Approximation for Scheduling Malleable Jobs on Parall...

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25th international conference on parallel and distributed computing, applications and technologies, PDCAT 2024

作者： Xia, Fenghe Guo, Longkun Zhang, Xiaoyan School of Mathematics and Statistics Fuzhou University Fuzhou350116 China School of Mathematical Science Institute of Mathematics and Ministry of Education Key Laboratory of NSLSCS Nanjing Normal University Nanjing210023 China

ISBN: (纸本)9789819642069

the rapid growth of cloud computing has brought new challenges in parallel Batch Machine Scheduling (PBMS), particularly when incorporating malleability and rejection constraints. this has led to the parallel Batch Machine Scheduling with Malleability and Rejection problem (PBMSMR), which involves malleable jobs whose widths can be adjusted during execution within specified limits and incorporates job rejection subject to a penalty threshold. Based on an analysis of key properties of batch scheduling with job rejection, we develop an approximation algorithm for PBMSMR by employing a greedy approach that reorders and iteratively refines job sets to minimize the objective while respecting rejection constraints. the algorithm achieves a time complexity of O(n2logn) and an approximation ratio of (4-2Km), where K and m denote the capacities and the number of the machines, respectively. For jobs with identical release times, we fine-tune the algorithm to achieve an approximation ratio of (3+2(K-1)Km). Additionally, for PBMS with two machines of non-identical capacities and fixed-width jobs, we achieve a ratio of 175 with O(nlogn), improving upon the previous state-of-the-art approximation ratio of 5 with a runtime of O(n2). © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Job shop scheduling

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