Journal of Parallel and Distributed Computing最新文献_第4页

Threat to trust: A systematic review on Internet of medical things security 对信任的威胁：医疗物联网安全系统综述

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-12-01 Epub Date: 2025-09-03 DOI: 10.1016/j.jpdc.2025.105172

Elham Shammar , Xiaohui Cui , Ammar Zahary , Saeed Hamood Alsamhi , Mohammed A.A. Al-qaness

{"title":"Threat to trust: A systematic review on Internet of medical things security","authors":"Elham Shammar , Xiaohui Cui , Ammar Zahary , Saeed Hamood Alsamhi , Mohammed A.A. Al-qaness","doi":"10.1016/j.jpdc.2025.105172","DOIUrl":"10.1016/j.jpdc.2025.105172","url":null,"abstract":"<div><div>The Internet of Medical Things (IoMT) has transformed healthcare by enabling seamless communication among medical devices, supporting real-time monitoring, diagnostics, vital patient data tracking, improved patient care, disease prediction, early warning, and enhanced operational efficiency. Due to the sensitive nature of health-related data, the adoption of IoMT has raised significant privacy and security concerns, prompting comprehensive evaluation of IoMT security and making it a prime target for cyberattacks such as ransomware, denial-of-service (DoS) attacks, and malware. Securing IoMT requires efficient data processing across distributed systems to ensure both confidentiality and availability. Parallel and distributed computing can address scalability and performance challenges in IoMT security, particularly in enabling real-time monitoring and threat detection across multiple interconnected devices. This survey conducts a systematic literature review (SLR) of IoMT security to analyze key issues, categorize security threats, attack vectors, and vulnerabilities, and examine how emerging technologies such as blockchain, machine learning (ML), and physically unclonable functions (PUF) are strengthening IoMT security. This SLR reviews IoMT security research published between 2020 and 2024 to identify challenges and provide insights for future researchers and developers of new IoMT security models. This SLR offers practitioners and researchers guidance for developing reliable and resilient IoMT security systems in the decentralized healthcare industry.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"206 ","pages":"Article 105172"},"PeriodicalIF":4.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145026873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FSCD: File system controlled coupled defragmenter for mobile storage systems 移动存储系统的文件系统控制耦合碎片整理程序

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-12-01 Epub Date: 2025-07-31 DOI: 10.1016/j.jpdc.2025.105159

Pingyang Huang, Chenxi Liu, Jilong Yang, Ting Chen, Zhiyuan Cheng

{"title":"FSCD: File system controlled coupled defragmenter for mobile storage systems","authors":"Pingyang Huang, Chenxi Liu, Jilong Yang, Ting Chen, Zhiyuan Cheng","doi":"10.1016/j.jpdc.2025.105159","DOIUrl":"10.1016/j.jpdc.2025.105159","url":null,"abstract":"<div><div>NAND-Flash-based mobile devices have gained increasing popularity. However, fragmentation in flash storage significantly impedes the I/O performance of the system, which leads to a poor user experience. Currently, the logical fragmentation is decoupled from the physical fragmentation and garbage collection is typically controlled by the <em>Flash Translation Layer</em> (FTL), degrading the garbage collection efficiency. In this paper, a novel fragmentation handling strategy, namely the <em>File System controlled Coupled Defragmenter</em> (FSCD), is proposed in which the file system is used to control the garbage collection, and couple the logical and physical fragmentations, synchronizing between the logical and physical defragmentation. As a result, FSCD can significantly reduce fragmentation and improve system performance in the fragmented state. Experimental results showed that the performance of Sequential Read/Sequential Write and Random Read/Random Write had been improved by 393.7%, 356.2% and 126.0%, 296.0% over the conventional FTL, respectively. FSCD alleviates fragmentation, improves I/O performance, and enables a better user experience, which provides a solution for the next generation of the NAND-flash-based mobile storage system.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"206 ","pages":"Article 105159"},"PeriodicalIF":4.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144772621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sensor failure mitigation in RTOS based internet of things (IoT) systems using machine learning 基于RTOS的物联网（IoT）系统中使用机器学习的传感器故障缓解

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-12-01 Epub Date: 2025-07-29 DOI: 10.1016/j.jpdc.2025.105161

Saugat Sharma, Grzegorz Chmaj, Henry Selvaraj

{"title":"Sensor failure mitigation in RTOS based internet of things (IoT) systems using machine learning","authors":"Saugat Sharma, Grzegorz Chmaj, Henry Selvaraj","doi":"10.1016/j.jpdc.2025.105161","DOIUrl":"10.1016/j.jpdc.2025.105161","url":null,"abstract":"<div><div>In IoT systems, issues like data loss can severely impact application performance, often resulting in missed deadlines in real-time operating systems (RTOS). Missed deadlines can lead to incomplete or delayed data, compromising system reliability and user safety. To address these challenges, this paper proposes a solution that reduces missed deadlines and effectively manages data gaps when they occur. This paper presents a novel approach, FP-DVFS-CC, which combines Fixed Priority (FP) scheduling with Dynamic Voltage and Frequency Scaling (DVFS) and Cycle Conserving (CC) to dynamically adjust CPU speeds in RTOS-based IoT systems. This method optimizes deadline adherence by adapting processing power based on task priority and system load, significantly reducing missed deadlines and energy consumption in real-time applications. Additionally, it proposes a MQTT-based cache to handle the delivery of missed messages with sensor data and suggests using machine learning to provide synthetic data to the system in case of data absence. Further, for addressing data gaps due to sensor malfunctions or delays, we introduce FeatureSync, an imputation technique that utilizes only highly correlated features integrating with machine learning algorithms to generate synthetic data. Experimental validation demonstrates enhanced performance with machine learning integration. If missing data is treated as zero instead of performing data imputation, it will lower accuracy, as seen in the case analysis, and increase prediction error. However, using data imputation can reduce the errors caused by treating missing values as zero. Testing on datasets with varied missing data reaffirms the approach's effectiveness.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"206 ","pages":"Article 105161"},"PeriodicalIF":4.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of single node load balancing for lattice Boltzmann method on heterogeneous high performance computers 异构高性能计算机上晶格玻尔兹曼方法的单节点负载均衡优化

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-12-01 Epub Date: 2025-08-21 DOI: 10.1016/j.jpdc.2025.105169

Adrian Kummerländer , Fedor Bukreev , Dennis Teutscher , Marcio Dorn , Mathias J. Krause

{"title":"Optimization of single node load balancing for lattice Boltzmann method on heterogeneous high performance computers","authors":"Adrian Kummerländer , Fedor Bukreev , Dennis Teutscher , Marcio Dorn , Mathias J. Krause","doi":"10.1016/j.jpdc.2025.105169","DOIUrl":"10.1016/j.jpdc.2025.105169","url":null,"abstract":"<div><div>Lattice Boltzmann Methods (LBM) are particularly suited for highly parallel computational fluid dynamics simulations on heterogeneous HPC systems combining CPUs and GPUs. However, the computationally dominant collide-and-stream loops commonly utilize only GPUs, leaving CPU resources underutilized. To overcome this limitation, this article proposes a novel load balancing strategy based on a genetic algorithm for bottom-up, cost-aware optimization of spatial domain decompositions. This approach generates subdomains and rank assignments inherently suited for cooperative execution on both CPUs and GPUs. Implemented in the open source framework OpenLB, the strategy is applied to turbulent flow reference cases, including a multi-physics reactive mixer. A detailed evaluation on heterogeneous HPC nodes demonstrates significant performance gains, achieving speedups of up to 87% compared to traditional GPU-only execution. This work therefore establishes cost-aware, bottom-up decomposition as a suitable strategy for exploiting the native heterogeneity of modern compute nodes.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"206 ","pages":"Article 105169"},"PeriodicalIF":4.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues) 封面1 -完整的扉页（每期）/特刊扉页（每期）

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-12-01 Epub Date: 2025-09-24 DOI: 10.1016/S0743-7315(25)00143-1

引用次数: 0

Optimizing parallel heterogeneous system efficiency: Dynamic task graph adaptation with recursive tasks 优化并行异构系统效率：递归任务的动态任务图自适应

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-11-01 Epub Date: 2025-07-28 DOI: 10.1016/j.jpdc.2025.105157

Nathalie Furmento, Abdou Guermouche, Gwenolé Lucas, Thomas Morin, Samuel Thibault, Pierre-André Wacrenier

{"title":"Optimizing parallel heterogeneous system efficiency: Dynamic task graph adaptation with recursive tasks","authors":"Nathalie Furmento, Abdou Guermouche, Gwenolé Lucas, Thomas Morin, Samuel Thibault, Pierre-André Wacrenier","doi":"10.1016/j.jpdc.2025.105157","DOIUrl":"10.1016/j.jpdc.2025.105157","url":null,"abstract":"<div><div>Task-based programming models are currently an ample trend to leverage heterogeneous parallel systems in a productive way (OpenACC, Kokkos, Legion, OmpSs, <span>PaRSEC</span>, <span>StarPU</span>, XKaapi, ...). Among these models, the Sequential Task Flow (STF) model is widely embraced (<span>PaRSEC</span>'s DTD, OmpSs, <span>StarPU</span>) since it allows to express task graphs naturally through a sequential-looking submission of tasks, and tasks dependencies are inferred automatically. However, STF is limited to task graphs with task sizes that are fixed at submission, posing a challenge in determining the optimal task granularity. Notably, in heterogeneous systems, the optimal task size varies across different processing units, so a single task size would not fit all units. <span>StarPU</span>'s recursive tasks allow graphs with several task granularities by turning some tasks into sub-graphs dynamically at runtime. The decision to transform these tasks into sub-graphs is decided by a <span>StarPU</span> component called the Splitter. After deciding to transform some tasks, classical scheduling approaches are used, making this component generic, and orthogonal to the scheduler. In this paper, we propose a new policy for the Splitter, which is designed for heterogeneous platforms, that relies on linear programming aimed at minimizing execution time and maximizing resource utilization. This results in a dynamic well-balanced set comprising both small tasks to fill multiple CPU cores, and large tasks for efficient execution on accelerators like GPU devices. We then present an experimental evaluation showing that just-in-time adaptations of the task graph lead to improved performance across various dense linear algebra algorithms.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"205 ","pages":"Article 105157"},"PeriodicalIF":4.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues) 封面1 -完整的扉页（每期）/特刊扉页（每期）

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-11-01 Epub Date: 2025-08-14 DOI: 10.1016/S0743-7315(25)00131-5

引用次数: 0

Complexity analysis and scalability of a matrix-free extrapolated geometric multigrid solver for curvilinear coordinates representations from fusion plasma applications 融合等离子体曲线坐标表示的无矩阵外推几何多网格求解器的复杂性分析和可扩展性

IF 3.4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-11-01 Epub Date: 2025-07-03 DOI: 10.1016/j.jpdc.2025.105143

Philippe Leleux , Christina Schwarz , Martin J. Kühn , Carola Kruse , Ulrich Rüde

{"title":"Complexity analysis and scalability of a matrix-free extrapolated geometric multigrid solver for curvilinear coordinates representations from fusion plasma applications","authors":"Philippe Leleux , Christina Schwarz , Martin J. Kühn , Carola Kruse , Ulrich Rüde","doi":"10.1016/j.jpdc.2025.105143","DOIUrl":"10.1016/j.jpdc.2025.105143","url":null,"abstract":"<div><div>Tokamak fusion reactors are promising alternatives for future energy production. Gyrokinetic simulations are important tools to understand physical processes inside tokamaks and to improve the design of future plants. In gyrokinetic codes such as Gysela, these simulations involve at each time step the solution of a gyrokinetic Poisson equation defined on disk-like cross sections. The authors of <span><span>[14]</span></span>, <span><span>[15]</span></span> proposed to discretize a simplified differential equation using symmetric finite differences derived from the resulting energy functional and to use an implicitly extrapolated geometric multigrid scheme tailored to problems in curvilinear coordinates. In this article, we extend the discretization to a more realistic partial differential equation and demonstrate the optimal linear complexity of the proposed solver, in terms of computation and memory. We provide a general framework to analyze floating point operations and memory usage of matrix-free approaches for stencil-based operators. Finally, we give an efficient matrix-free implementation for the considered solver exploiting a task-based multithreaded parallelism which takes advantage of the disk-shaped geometry of the problem. We demonstrate the parallel efficiency for the solution of problems of size up to 50 million unknowns.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"205 ","pages":"Article 105143"},"PeriodicalIF":3.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

To repair or not to repair: Assessing fault resilience in MPI stencil applications 修复或不修复：评估MPI模板应用中的故障恢复能力

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-11-01 Epub Date: 2025-07-25 DOI: 10.1016/j.jpdc.2025.105156

Roberto Rocco , Elisabetta Boella , Daniele Gregori , Gianluca Palermo

{"title":"To repair or not to repair: Assessing fault resilience in MPI stencil applications","authors":"Roberto Rocco , Elisabetta Boella , Daniele Gregori , Gianluca Palermo","doi":"10.1016/j.jpdc.2025.105156","DOIUrl":"10.1016/j.jpdc.2025.105156","url":null,"abstract":"<div><div>With the increasing size of HPC computations, faults are becoming more and more relevant in the HPC field. The MPI standard does not define the application behaviour after a fault, leaving the burden of fault management to the user, who usually resorts to checkpoint and restart mechanisms. This trend is especially true in stencil applications, as their regular pattern simplifies the selection of checkpoint locations. However, checkpoint and restart mechanisms introduce non-negligible overhead, disk load, and scalability concerns. In this paper, we show an alternative through fault resilience, enabled by the features provided by the User Level Fault Mitigation extension and shipped within the Legio fault resilience framework. Through fault resilience, we continue executing only the non-failed processes, thus sacrificing result accuracy for faster fault recovery. Our experiments on some specimen stencil applications show that, despite the fault impact visible in the result, we produced meaningful values usable for scientific research, proving the possibilities of a fault resilience approach in a stencil scenario.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"205 ","pages":"Article 105156"},"PeriodicalIF":4.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144720967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Federated multi-task learning with cross-device heterogeneous task subsets 跨设备异构任务子集的联邦多任务学习

IF 4 3区计算机科学

Journal of Parallel and Distributed Computing Pub Date : 2025-11-01 Epub Date: 2025-07-25 DOI: 10.1016/j.jpdc.2025.105155

Zewei Xin, Qinya Li, Chaoyue Niu, Fan Wu, Guihai Chen

{"title":"Federated multi-task learning with cross-device heterogeneous task subsets","authors":"Zewei Xin, Qinya Li, Chaoyue Niu, Fan Wu, Guihai Chen","doi":"10.1016/j.jpdc.2025.105155","DOIUrl":"10.1016/j.jpdc.2025.105155","url":null,"abstract":"<div><div>Traditional Federated Learning (FL) predominantly focuses on task-consistent scenarios, assuming clients possess identical tasks or task sets. However, in multi-task scenarios, client task sets can vary greatly due to their operating environments, available resources, and hardware configurations. Conventional task-consistent FL cannot address such heterogeneity effectively. We define this statistical heterogeneity of task sets, where each client performs a unique subset of server tasks, as cross-device task heterogeneity. In this work, we propose a novel Federated Partial Multi-task (FedPMT) method, allowing clients with diverse task sets to collaborate and train comprehensive models suitable for any task subset. Specifically, clients deploy partial multi-task models tailored to their localized task sets, while the server utilizes single-task models as an intermediate stage to address the model heterogeneity arising from differing task sets. Collaborative training is facilitated through bidirectional transformations between them. To alleviate the negative transfer caused by task set disparities, we introduce task attenuation factors to modulate the influence of different tasks. This adjustment enhances the performance and task generalization ability of cloud models, promoting models to converge towards a shared optimum across all task subsets. Extensive experiments conducted on the NYUD-v2, PASCAL Context and Cityscapes datasets validate the effectiveness and superiority of FedPMT.</div></div>","PeriodicalId":54775,"journal":{"name":"Journal of Parallel and Distributed Computing","volume":"205 ","pages":"Article 105155"},"PeriodicalIF":4.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144720966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0