Simulation Modelling Practice and Theory最新文献_第7页

CCCR: Combining CNP and RTT for congestion control in datacenter networks CCCR：结合CNP和RTT实现数据中心网络的拥塞控制

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-28 DOI: 10.1016/j.simpat.2025.103189

Haopeng Li , Dingyu Yan , Yaping Liu , Shuo Zhang

With the rapid development of cloud computing, AI, and big data, data center networks face challenges in achieving ultra-low latency, high bandwidth, and stability. Many data centers still rely on traditional switches, which lack programmable features for advanced congestion control algorithms. In this environment, existing algorithms like DCQCN and TIMELY face two major challenges: (1) a single congestion signal (such as ECN or RTT) struggles to accurately reflect network conditions, leading to delayed congestion detection; (2) heuristic rate control strategies are prone to causing network fluctuations and slow convergence, making it difficult to meet the demands of high-bandwidth links. To address these issues, we propose CCCR, a congestion control algorithm that combines ECN (via CNP) and RTT signals. CCCR enables rapid, accurate rate reduction using receiver-side feedback and employs a adaptive rate increase based on minimum, average, and target RTT. It also adjusts in-flight data using per-flow BDP estimation. Simulations show that compared to DCQCN, TIMELY, and Swift, CCCR reduces the average flow completion time by 11%, 20%, and 12% respectively in incast scenarios, with better fairness than HPCC, and achieves up to 82% reduction in tail flow completion time for medium flows and up to 74% for long flows. In large-scale simulations, CCCR achieves comparable performance to programmable switch-based HPCC algorithms.

随着云计算、人工智能和大数据的快速发展，数据中心网络在实现超低延迟、高带宽和稳定性方面面临着挑战。许多数据中心仍然依赖于传统的交换机，而这种交换机缺乏用于高级拥塞控制算法的可编程功能。在这种环境下，DCQCN和TIMELY等现有算法面临两大挑战：(1)单个拥塞信号（如ECN或RTT）难以准确反映网络状况，导致拥塞检测延迟；(2)启发式速率控制策略容易引起网络波动，收敛速度慢，难以满足高带宽链路的需求。为了解决这些问题，我们提出了CCCR，一种结合ECN（通过CNP）和RTT信号的拥塞控制算法。CCCR使用接收端反馈实现快速、准确的速率降低，并采用基于最小、平均和目标RTT的自适应速率增加。它还使用每流BDP估计来调整飞行中的数据。仿真结果表明，与DCQCN、TIMELY和Swift相比，CCCR在随机场景下的平均流完成时间分别减少了11%、20%和12%，且比HPCC具有更好的公平性，对于中等流尾流完成时间最多减少82%，对于长流尾流完成时间最多减少74%。在大规模仿真中，CCCR达到了与基于可编程开关的HPCC算法相当的性能。

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引用次数: 0

Surgical operating theater scheduling: From Discrete-Event Systems point of view 外科手术室调度：从离散事件系统的角度

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-28 DOI: 10.1016/j.simpat.2025.103185

Oumaima Boulkhoukh , Ahmed Nait Sidi Moh , Elhoucine Chakir El Alaoui

This paper addresses the decision-making problem of surgical operations scheduling in healthcare systems. The problem involves arranging elective surgeries with assigned intervention dates under the constraint of limited resources such as operating rooms and surgeons. In the present work, we tackle this problem in the point of view of Discrete Event Systems. Our objective is to model and analyze the healthcare systems using two complementary formalisms Timed Colored Petri Nets (TCPN) and (max, ＋) Algebra. To this end, we first develop a TCPN model that represents and studies the behavior of patient care flow. This model allows us to evaluate the performance of the system. Based on the TCPN model, we develop (max, ＋) equations that represent the system behavior using linear mathematical equations. These equations help calculate easily the occurrence dates of surgery activities. Thanks to (max, +) theory we propose a provisional schedule of elective interventions. We show that (max, ＋) powerful lies in its ability to calculate the beginning date and end date of each surgical operation, taking into account limited human and material resources. An illustrative example is presented to demonstrate the effectiveness of the proposed approach.

本文讨论了医疗保健系统中外科手术计划的决策问题。该问题涉及在手术室和外科医生等有限资源的约束下，安排具有指定干预日期的选择性手术。在目前的工作中，我们从离散事件系统的角度来解决这个问题。我们的目标是使用两个互补的形式：定时彩色Petri网（TCPN）和（max, +）代数来建模和分析医疗保健系统。为此，我们首先开发了一个TCPN模型来表示和研究患者护理流程的行为。这个模型使我们能够评估系统的性能。基于TCPN模型，我们开发了使用线性数学方程表示系统行为的（max, +）方程。这些方程有助于计算手术活动的发生日期。由于（max, +）理论，我们提出了一个选择性干预的临时时间表。我们证明（max, +）的强大之处在于它能够计算每次手术的开始日期和结束日期，同时考虑到有限的人力和物力资源。最后通过一个实例验证了该方法的有效性。

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引用次数: 0

Preference-based D2D offloading in IoT-edge-cloud continuum 物联网边缘云连续体中基于偏好的D2D卸载

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-19 DOI: 10.1016/j.simpat.2025.103188

Haripriya Chaturvedi, Gaurav Baranwal

Computation tasks are offloaded to the edge server from the Internet of Things (IoT) and mobile devices due to their restricted computation capacity and battery life. However, the fixed capacity of edge servers makes serving multiple IoT and mobile devices challenging for edge servers. The collaborative architecture, i.e. Device-to-Device (D2D)-edge computing, plays a great role in solving this resource gap problem between the IoT and mobile devices and edge servers. The architecture allows the offloading from IoT and mobile devices with restricted resources to IoT and mobile devices with resource-rich resources instead of only edge servers. This collaborative architecture also provides solutions to other edge server-related problems like workload, congestion, bandwidth consumption, and energy consumption along with the utilization of idle resources of nearby IoT and mobile devices. This paper proposes a preference-based D2D offloading model in IoT-Edge-Cloud Continuum. The proposed business model introduces the concept of surcharges to increase the utilization of computing resources. Compared to state-of-the-art work, the model generates more social welfare, increases the number of allocations, and increases participants' utility. With the help of simulation work, we have shown that the work is effective and outperforms.

由于物联网（IoT）和移动设备的计算能力和电池寿命有限，计算任务被转移到边缘服务器。然而，边缘服务器的固定容量使得为多个物联网和移动设备提供服务对边缘服务器来说具有挑战性。协同架构，即设备到设备（Device-to-Device, D2D）边缘计算，在解决物联网与移动设备和边缘服务器之间的资源缺口问题方面发挥了重要作用。该架构允许从资源有限的物联网和移动设备卸载到资源丰富的物联网和移动设备，而不仅仅是边缘服务器。这种协作架构还为其他与边缘服务器相关的问题提供解决方案，如工作负载、拥塞、带宽消耗和能耗，以及附近物联网和移动设备的空闲资源的利用。本文提出了一种基于偏好的物联网边缘云连续体D2D卸载模型。提出的商业模式引入了附加费的概念，以提高计算资源的利用率。与最先进的工作相比，该模型产生了更多的社会福利，增加了分配的数量，并增加了参与者的效用。通过仿真工作，证明了该方法的有效性和优越性。

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引用次数: 0

Peridynamics simulation method and application of hydro-mechanical coupling in fractured rock masses under dynamic disturbance 动态扰动下裂隙岩体水-力耦合动力学模拟方法及应用

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-17 DOI: 10.1016/j.simpat.2025.103187

Daosheng Zhang , Zongqing Zhou , Liping Li , Chenglu Gao , Minghao Li , Panpan Gai , Xiaochu Chen

The hydro-mechanical coupling failure mechanism of fractured rock masses under dynamic disturbance remains a significant challenge in the field of rock mechanics. To address this, a peridynamics-based simulation method is developed to scientifically characterise the water pressure variations within water-bearing fractures subjected to dynamic disturbance and the associated rock mass damage. First, a governing equation for fracture seepage in the peridynamics framework is proposed. Building on this, a three-dimensional hydro-mechanical coupled peridynamics model for fractured rock masses is established, based on the principle of effective stress. Next, the response characteristics of fracture water pressure under dynamic disturbance (e.g., blasting impact) are analysed, and a mathematical expression describing the relationship between fracture deformation and water pressure variation is formulated. A three-dimensional peridynamics simulation method is then constructed to capture the coupled stress–seepage behaviour of fractured rock masses under dynamic loading. The evolution of water pressure and the dynamic propagation mechanisms of water-bearing fractures are subsequently investigated. The accuracy of the proposed method is validated through a series of numerical examples. Finally, the method is utilised to assess the stability of the surrounding rock during subsea tunnel construction using the drilling–blasting method. The influence of dynamic disturbance on tunnel stability is revealed, offering valuable insights for the safe construction of subsea tunnels.

裂隙岩体在动力扰动作用下的水-力耦合破坏机制一直是岩石力学领域的一个重大挑战。为了解决这一问题，开发了一种基于周动力学的模拟方法，以科学地表征受动力扰动和伴生岩体破坏的含水裂缝内的水压变化。首先，提出了围动力框架下的裂缝渗流控制方程。在此基础上，基于有效应力原理，建立了裂隙岩体三维水-力耦合动力学模型。其次，分析了裂隙水压在动力扰动（如爆破冲击）作用下的响应特征，建立了裂隙变形与水压变化关系的数学表达式。在此基础上，建立了裂隙岩体在动力加载作用下的三维围动力模拟方法。在此基础上，研究了水压力的演化和含水裂缝的动态扩展机制。通过一系列数值算例验证了该方法的准确性。最后，将该方法应用于钻爆法海底隧道施工过程中围岩稳定性的评估。揭示了动力扰动对隧道稳定性的影响，为海底隧道的安全施工提供了有价值的见解。

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引用次数: 0

Mesoscopic deformation mechanisms and engineering applications of soil-rock mixtures: effects of varying stone content 土石混合体的细观变形机制和工程应用：不同石料含量的影响

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-17 DOI: 10.1016/j.simpat.2025.103186

Yucheng Wu , Jie Yang , Chunhui Ma , Li Ran , Lin Cheng

This study explores the meso-mechanical characteristics and structural evolution of soil-rock mixtures (SRM) under complex stress conditions using six triaxial test models with varying stone content. Experimental simulations revealed that stone content significantly affects peak stress. A three-dimensional mesoscale structural fabric was employed to analyze the spatial distribution of normal and tangential contact forces, while a two-dimensional fabric tensor analysis highlighted the dominant role of stone content in mesoscale mechanical behavior. Results showed that increasing stone content leads to higher normal and tangential contact forces. Further analysis revealed a strong correlation between rock crushing and overall deformation, with higher rock content enhancing the anti-slip capability of SRMs. To extend these findings, a discrete element model was developed to simulate the rolling construction process of the anti-seepage core wall in a dam. This model evaluated the effects of varying stone content on coordination number, settlement rate, and porosity, as well as the influence of gravel mixing strategies on dam deformation. This research provides insights into the meso-deformation mechanisms of SRMs and the role of stone content in dam construction, offering valuable guidance for improving the design and performance of soil-rock structures in engineering applications.

采用6个不同含石量的三轴试验模型，探讨了复杂应力条件下土石混合体的细观力学特征和结构演化。实验模拟表明，岩石含量对峰值应力有显著影响。采用三维中尺度结构织物分析了法向和切向接触力的空间分布，而二维织物张量分析强调了石材含量对中尺度力学行为的主导作用。结果表明，随着石材含量的增加，法向接触力和切向接触力增大。进一步分析表明，岩石破碎与整体变形之间存在很强的相关性，岩石含量越高，srm的抗滑能力越强。为了推广这些发现，建立了一个离散元模型来模拟大坝防渗心墙的滚动施工过程。该模型评估了不同含石量对配位数、沉降速率和孔隙率的影响，以及碎石混合策略对大坝变形的影响。本研究揭示了土石结构细观变形机制和含石量在大坝建设中的作用，为工程应用中改进土石结构的设计和性能提供了有价值的指导。

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引用次数: 0

Evaluating traffic and safety impacts of diverging diamond interchange replacing roundabouts: A microsimulation study 分道菱形立交取代环形交叉路口对交通和安全影响的微观模拟研究

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-17 DOI: 10.1016/j.simpat.2025.103179

Jingshuo Qiu , Léah Camarcat , Paraskevi Koliou , Yuxiang Feng , Nicolette Formosa , Georgios Zacharopoulos , Paraskevi Michalaki , Panagiotis Angeloudis , Mohammed Quddus

With increasing traffic volumes and worsening congestion, conventional interchanges are facing ever-growing challenges. These issues can potentially be mitigated by implementing suitable alternative designs, such as the Diverging Diamond Interchange (DDI). While simulation studies and real-world implementations have validated the DDI’s superiority over conventional interchanges, existing research primarily focuses on right-hand driving and has not considered roundabout layouts prevalent in the UK. This study employs the simulation of the UK Strategic Road Network (SRN) to address this gap. Four hypothetical scenarios are constructed, transitioning conventional junctions between J23 and J26 on the M1 Motorway of SRN to DDIs. By comparing a series of Key Performance Indicators (KPIs), the study quantitatively assesses the impact of DDI implementation on traffic flow, delay and safety. The simulation results reveal that replacing roundabouts to DDIs in a motorway corridor can lead to a 55% reduction in average delay and a 5.96% increase in average speed. However, upon evaluating traffic safety through the Surrogate Safety Assessment Model, a slight decline in the majority of safety performance measures is observed. This study provides evidence to support the adoption of DDIs in the UK, highlighting the trade-offs between improved traffic flow and potential safety concerns.

随着交通流量的增加和拥堵的加剧，传统的立交面临着越来越大的挑战。这些问题可以通过实施合适的替代设计来缓解，例如分流钻石交换（DDI）。虽然仿真研究和实际应用已经验证了DDI相对于传统立交的优越性，但现有的研究主要集中在右侧驾驶，并没有考虑到英国普遍存在的环形交叉路口布局。本研究采用英国战略道路网络（SRN）的模拟来解决这一差距。构建了四种假设情景，将SRN M1高速公路J23和J26之间的传统路口转换为ddi。本研究通过比较一系列关键绩效指标（kpi），定量评估实施DDI对交通流、延误和安全的影响。仿真结果表明，在高速公路走廊内，将环形交叉路改为ddi，平均延误减少55%，平均速度提高5.96%。然而，在通过替代安全评估模型评估交通安全时，观察到大多数安全绩效指标略有下降。这项研究为支持英国采用ddi提供了证据，强调了改善交通流量和潜在安全问题之间的权衡。

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引用次数: 0

Modeling the asymmetric thermo-mechanical behavior and failure of gray cast irons: An experimental–numerical study with separate Johnson–Cook parameters 模拟灰铸铁的不对称热力学行为和失效：具有单独Johnson-Cook参数的实验-数值研究

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-14 DOI: 10.1016/j.simpat.2025.103182

Burak Özcan , Umut Çalışkan , Murat Aydın , Onur Çavuşoğlu , Ulvi Şeker

In this study, the asymmetric (different tensile and compressive behavior) thermo-mechanical behavior and damage of gray cast irons (EN-GJL-200, EN-GJL-250, EN-GJL-300), which are widely used in industrial applications, under different strain rates and temperatures were investigated by a combination of experimental and numerical methods. The mechanical response of the materials was characterized by quasi-static tensile and compression tests at room temperature and elevated temperatures up to 700 °C, Split Hopkinson Compression Bar (SHPB) tests for high strain rates (up to ∼3600 s⁻¹) and tensile tests with specimens of different notch radii to analyze the damage behavior. Based on the experimental data obtained, the Johnson-Cook (JC) material (A, B, n, C, m) and damage (D1-D5) model parameters were calibrated separately for both loading cases in order to capture the apparent asymmetric behavior of gray cast irons under tensile and compression loading. These separate parameter sets were integrated into ANSYS Autodyn finite element software through FORTRAN-based user-defined subroutines and virtual tensile, compression and SHPB tests were performed. Comparing the numerical simulation results with the experimental data, it was observed that the developed asymmetric modeling approach, in particular, represents the thermo-mechanical behavior and damage of the material with high accuracy (deviations in the range of 2–8 % for maximum stress and elongation at break values). This study provides reliable and decoupled JC parameter sets for modeling the asymmetric thermo-mechanical behavior and damage of gray cast irons, allowing more realistic simulations to predict the performance of these materials in demanding engineering applications.

采用实验与数值相结合的方法，研究了工业上广泛应用的灰口铸铁（EN-GJL-200、EN-GJL-250、EN-GJL-300）在不同应变速率和温度下的不对称（不同的拉伸和压缩行为）热力学行为和损伤。材料的力学响应通过室温和高达700°C的高温下的准静态拉伸和压缩试验、高应变率（高达~ 3600 s−1）的劈裂霍普金森压缩杆（SHPB）试验和不同缺口半径试样的拉伸试验来分析损伤行为。基于获得的实验数据，分别校准了两种加载情况下的Johnson-Cook （JC）材料（A， B, n， C, m）和损伤（D1-D5）模型参数，以捕捉灰口铸铁在拉伸和压缩加载下的明显不对称行为。通过基于fortran的用户自定义子程序将这些单独的参数集集成到ANSYS Autodyn有限元软件中，并进行虚拟拉伸、压缩和SHPB试验。将数值模拟结果与实验数据进行比较，发现所开发的非对称建模方法能够高精度地表征材料的热力学行为和损伤（最大应力和断裂伸长率的偏差在2 - 8%范围内）。该研究为灰口铸铁的不对称热力学行为和损伤建模提供了可靠且解耦的JC参数集，允许更真实的模拟来预测这些材料在苛刻的工程应用中的性能。

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引用次数: 0

An advanced 3D continuum finite element model for field-scale in-situ stress simulation of rock media 用于岩石介质现场地应力模拟的先进三维连续体有限元模型

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-14 DOI: 10.1016/j.simpat.2025.103183

Atefeh Dargahizarandi , Hossein Masoumi , Abolfazl Hashemi , Biswachetan Saha , Hamid Roshan

Accurate field-scale three-dimensional (3D) stress inversion using numerical simulation is crucial for obtaining in-situ stresses required for the safety and efficiency of underground minerals and energy resources extraction. However, existing commercial packages fall short in dealing with large-scale 3D stress inversion simulations and handling complex geological models containing faults and fractures. This work lays the foundation for the development of an optimised continuum Finite Element (FE) code (3DiStress) to simulate the 3D stress state in elastic media, capable of handling complex geological models. Such a computational framework employs advanced algorithms and state-of-the-art techniques, including the implementation of fault modelling through the effective medium theory, efficient large-scale model handling via vectorisation and sparse matrix storage, Superconvergent Patch Recovery (SPR) to calculate the stresses precisely, and iterative boundary conditions adjustment using Genetic Algorithm (GA) for stress inversion. For large-scale simulations, an effective solver, renowned for its robust handling of large sparse systems (Pardiso), is implemented to solve the resultant system of equations with high efficiency in parallel on a workstation and supercomputers. Furthermore, an iterative boundary condition adjustment is performed using GA, to calibrate the model against on-site stress measurements, thereby optimising the stress distribution. The principal advantages of this computational tool include its capability to accurately simulate complex faulted elastic media, flexible boundary condition optimisation, and the ability to easily adapt and integrate various algorithms, making it an asset for advanced geomechanical engineering applications.

利用数值模拟技术进行准确的场尺度三维应力反演对于获得地下矿产和能源开采安全高效所需的地应力至关重要。然而，现有的商业软件包在处理大规模三维应力反演模拟和处理包含断层和裂缝的复杂地质模型方面存在不足。这项工作为开发优化的连续体有限元（FE）代码（3DiStress）奠定了基础，以模拟弹性介质中的三维应力状态，能够处理复杂的地质模型。这种计算框架采用了先进的算法和技术，包括通过有效介质理论实现断层建模，通过矢量化和稀疏矩阵存储进行高效的大规模模型处理，超收敛补丁恢复（SPR）精确计算应力，以及使用遗传算法（GA）进行应力反演的迭代边界条件调整。对于大规模模拟，实现了一个有效的求解器，以其对大型稀疏系统的鲁棒处理（Pardiso）而闻名，在工作站和超级计算机上并行高效地求解所得方程组。此外，使用遗传算法进行迭代边界条件调整，以根据现场应力测量校准模型，从而优化应力分布。该计算工具的主要优点包括其精确模拟复杂断层弹性介质的能力，灵活的边界条件优化，以及轻松适应和集成各种算法的能力，使其成为先进地质力学工程应用的资产。

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引用次数: 0

Exploring the performance of real-time data imputation to enhance fault tolerance on the edge: A study on environmental data 基于边缘容错的实时数据输入性能研究——以环境数据为例

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-12 DOI: 10.1016/j.simpat.2025.103178

Dimitris Gkoulis, Anargyros Tsadimas, George Kousiouris, Cleopatra Bardaki, Mara Nikolaidou

Real-time data streams from edge-based IoT sensors are frequently affected by transmission errors, sensor faults, and network disruptions, leading to missing or incomplete data. This paper investigates the application of lightweight, real-time imputation methods to enhance fault tolerance in edge computing systems. To this end, we propose to integrate a modular imputation engine on edge system supporting lightweight forecasting models selected for their computational efficiency and suitability to operate on real-time data streams. To assess the performance of different popular lightweight forecasting models for real-time applications, a simulation framework is introduced that simulates the operation of the imputation engine, replicates sensor failure scenarios and allows controlled testing on real-world systems. Imputation accuracy is evaluated using Mean Absolute Error (MAE), 95th percentile error, and maximum error, with results benchmarked against sensor tolerance thresholds. The simulation framework is used to explore imputation on environmental data based on observations collected from a weather station. The findings show that Holt–Winters Exponential Smoothing delivers the highest accuracy for real-time imputation across environmental variables, outperforming simpler models suited only for short-term gaps. Errors grow with longer forecasts, confirming imputation as a temporary solution. Evaluations against sensor-specific thresholds offer practical insights, and execution profiling proves these models are lightweight enough for deployment on low-power edge devices, enabling real-time, fault-tolerant monitoring without cloud dependence.

来自边缘物联网传感器的实时数据流经常受到传输错误、传感器故障和网络中断的影响，导致数据丢失或不完整。本文研究了在边缘计算系统中应用轻量、实时的插值方法来增强容错性。为此，我们建议在边缘系统上集成一个模块化的输入引擎，支持轻量级的预测模型，这些预测模型是根据其计算效率和对实时数据流的适用性而选择的。为了评估实时应用中不同流行的轻量级预测模型的性能，引入了一个仿真框架，该框架模拟了输入引擎的操作，复制了传感器故障场景，并允许在真实系统上进行受控测试。使用平均绝对误差（MAE）、第95百分位误差和最大误差来评估插入精度，结果以传感器公差阈值为基准。利用模拟框架探讨了基于气象站观测数据的环境数据的拟合。研究结果表明，Holt-Winters指数平滑在跨环境变量的实时输入中提供了最高的准确性，优于仅适用于短期差距的简单模型。随着预测时间的延长，错误也会增加，这证实了归咎只是一种临时解决方案。针对特定传感器阈值的评估提供了实用的见解，执行分析证明这些模型足够轻量级，可以部署在低功耗边缘设备上，实现实时、容错监控，而不依赖云。

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引用次数: 0

CoFANN: A collaborative framework for accelerating DNN inference in drone-based agricultural monitoring systems CoFANN：在基于无人机的农业监测系统中加速DNN推理的协作框架

IF 3.5 2区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Simulation Modelling Practice and Theory

Pub Date : 2025-07-11 DOI: 10.1016/j.simpat.2025.103176

Nhu-Y Tran-Van, Kim-Hung Le

Plant leaf diseases pose a major threat to global agricultural productivity, causing substantial crop losses annually. While drone-based monitoring systems equipped with deep neural networks (DNNs) offer a promising solution for large-scale disease detection, their deployment is hindered by the computational limitations of IoT devices and the latency issues associated with cloud and edge computing. Existing collaborative inference approaches aim to mitigate end-to-end latency by offloading computation across devices. However, these methods often compromise model accuracy and add computing latency in generating inference strategies. To address these challenges, we present CoFANN, a novel collaborative framework to accelerate DNN inference in dynamic IoT environments. Our framework includes two key advances: a differentiable strategy search space with a gradient-based optimization algorithm for efficiently identify optimal partitioning strategies, and an adaptive model partitioning algorithm that effectively divides and allocates DNN components across computing devices based on their capabilities and network conditions. Experimental results in the plant disease dataset demonstrate that CoFANN reduces the total inference latency by up to 70% compared to device-only and 50% compared to edge-only approaches under varying network conditions, while maintaining comparable accuracy from 93.7% to 95.8%.

植物叶片病害对全球农业生产力构成重大威胁，每年造成大量作物损失。虽然配备深度神经网络（dnn）的无人机监测系统为大规模疾病检测提供了一个很有前途的解决方案，但它们的部署受到物联网设备的计算限制以及与云和边缘计算相关的延迟问题的阻碍。现有的协同推理方法旨在通过跨设备卸载计算来减轻端到端延迟。然而，这些方法往往会损害模型的准确性，并在生成推理策略时增加计算延迟。为了应对这些挑战，我们提出了CoFANN，这是一个新的协作框架，可以在动态物联网环境中加速DNN推理。我们的框架包括两个关键的进展：一个可微分的策略搜索空间，一个基于梯度的优化算法，用于有效地识别最优分区策略；一个自适应模型分区算法，根据计算设备的能力和网络条件，有效地在计算设备之间划分和分配DNN组件。植物病害数据集的实验结果表明，在不同的网络条件下，CoFANN比纯设备方法减少了70%的总推理延迟，比纯边缘方法减少了50%，同时保持了93.7%到95.8%的相当准确率。

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引用次数: 0