Simulation Modelling Practice and Theory最新文献

{"title":"A Petri Net-based framework for modeling and simulation of resource scheduling policies in Edge Cloud Continuum","authors":"Christoforos Vardakis,&nbsp;Ioannis Dimolitsas,&nbsp;Dimitrios Spatharakis,&nbsp;Dimitrios Dechouniotis,&nbsp;Anastasios Zafeiropoulos,&nbsp;Symeon Papavassiliou","doi":"10.1016/j.simpat.2025.103098","DOIUrl":"10.1016/j.simpat.2025.103098","url":null,"abstract":"<div><div>The emergence of new technologies of 5G/6G networks and the Internet of Things (IoT) drives the transition from traditional Cloud Computing systems to the Edge Cloud Continuum — an interconnected distributed computing environment. Deploying modern applications in such a complex setting poses significant challenges for efficient dynamic resource management. Besides their several benefits, current orchestration platforms disregard aspects such as the dynamic behavior of applications’ demands, heterogeneity of the infrastructure’s resources, and the overall complexity when dealing with interdependent resource allocation decision parameters. The Digital Twin concept envisions assisting application deployments not only by providing offline simulations for experimental assessment in multi-cluster settings but also by actively guiding the orchestration process. In this paper, we aim to provide a modeling and simulation framework to optimize the performance of the underlying infrastructure in terms of resilience and sustainability. We investigate the application of automata theory to model such systems by analyzing their possible states, specifically, using Petri Nets, a mathematical framework for representing discrete event systems, as the primary modeling tool. Therefore, a comprehensive modeling approach is presented to simulate the resource scheduling decisions of an established multi-cluster framework, namely Karmada. Moreover, through this Petri Net modeling approach, we can efficiently optimize the performance of the orchestration process considering the power consumption and workload load balancing of a multi-cluster topology. Extensive evaluation indicates the efficacy of the proposed framework in accurately approximating Karmada’s behavior for various scheduling policies. Also, the proposed framework is capable of assessing the performance of several scheduling policies and guiding the system towards efficient resource management in complex scenarios, exploiting the polynomial complexity of the Petri Net to identify scheduling states.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"141 ","pages":"Article 103098"},"PeriodicalIF":3.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing communication policies in cooperative multi-agent reinforcement learning for traffic signal control: A simulation-based study","authors":"Sofiene Abidi,&nbsp;Philippe Mathieu,&nbsp;Antoine Nongaillard","doi":"10.1016/j.simpat.2025.103100","DOIUrl":"10.1016/j.simpat.2025.103100","url":null,"abstract":"<div><div>Traffic signal control (TSC) poses a significant challenge in intelligent transportation systems and has been addressed using multi-agent reinforcement learning (MARL). While centralized approaches are often impractical for large-scale TSC problems, decentralized approaches offer scalability but introduce new challenges, such as partial observability. Communication plays a crucial role in decentralized MARL, as agents must exchange information through messages to understand the system better and achieve effective coordination. Deep MARL has been applied, where multiple interacting agents share a common environment. However, many proposed deep MARL communication policies for TSC allow agents to communicate with all other agents and share global state. This can contribute to system noise and degrade overall performance since real-time global information sharing is impractical due to communication latency. This paper employs simulation-based approaches to assess the effectiveness of diverse information-sharing strategies to enhance overall system performance based on Cooperative Deep Q-Network (Co-DQN). Simulation experiment results suggest that the lack of a suitable sharing policy to provide a representative observation of the real state appears to affect performance more drastically than changes to the underlying traffic patterns.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"141 ","pages":"Article 103100"},"PeriodicalIF":3.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simulation approach with heuristic rules for reliability estimation of two-terminal multi-state networks based on minimal cuts and parallel computations","authors":"Paweł Marcin Kozyra","doi":"10.1016/j.simpat.2025.103095","DOIUrl":"10.1016/j.simpat.2025.103095","url":null,"abstract":"<div><div>Both the system reliability and the resilience evaluation of multi-state flow networks (MFNs) play a crucial role in designing and analyzing these networks. The system reliability at level <span><math><mi>d</mi></math></span> is the probability of successfully transmitting at least <span><math><mi>d</mi></math></span> units of flow. In turn, system resilience allows us to analyze the ability of systems to withstand and bounce back from disruptive events. The paper presents a new simulation approach based on minimal cuts (MCs) and parallel computations to compute the system reliability for all possible non-integer levels. An extension with a time attribute is also considered to investigate the reliability degradation with time. Moreover, it also introduces a novel heuristic that for a given integer <span><math><mi>K</mi></math></span> and a state vector <span><math><mi>x</mi></math></span>, finds an MC for which the capacity under the system state <span><math><mi>x</mi></math></span> is the smallest among MCs containing some of <span><math><mi>K</mi></math></span> coordinates of <span><math><mi>x</mi></math></span> with the smallest capacities. It is also shown how this approach can be used to compute the network resilience at a given time and the system integrated resilience metric is introduced. Numerical experiments are conducted to demonstrate the efficiency and advantages of the presented algorithm.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"141 ","pages":"Article 103095"},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"B2RAM: Design and practical implementation of a secured information management framework for dynamic resource allocation using a novel 2-Tier blockchain model","authors":"Tamal Chakraborty ,&nbsp;Abhinav Ashish ,&nbsp;Priyanshu Das ,&nbsp;Satyajeet Jha ,&nbsp;Debanik Saha ,&nbsp;Sumit Kumar Shahi","doi":"10.1016/j.simpat.2025.103096","DOIUrl":"10.1016/j.simpat.2025.103096","url":null,"abstract":"<div><div>Resource allocation problems involve the intricate task of equitably and consistently distributing typically limited resources among competing clients, all while dealing with the issues of fairness, starvation, scalability and deadlock. The effectiveness of these solutions hinges on a secure and transparent underlying information flow model, ensuring timely and synchronized exchange of information about resource usage among the clients. Both centralized and distributed system architectures present their own challenges when devising such information flow strategies for optimal resource allocation. This paper efficiently addresses the constraints inherent in resource allocation and the associated information flows within a hybrid system-of-systems framework. It further integrates both distributed and centralized models while maintaining an optimal trade-off between the computational and communication costs. In this context, a secure and transparent information management framework is proposed, leveraging a novel 2-Tier blockchain model — B2RAM. The first Tier establishes a consortium blockchain within a distributed network, while the second Tier creates multiple private blockchain networks in centralized client–server models. Together, these two tiers establish a distinctive resource allocation policy that engages both cooperative and competitive users, further incorporating a novel dual-token model and resource ranking strategy. Extensive performance evaluation facilitates fine-tuning of B2RAM through parameter configurations and enhancement strategies. This not only refines its performance but also solidifies its superiority over existing models like greedy, Markov, prediction, random, and rank-based approaches. Finally, practical applicability of B2RAM is established through its implementation in Cognitive Radio Networks, where the operational feasibility is ensured through successful test-bed design and execution using a modular system framework.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"141 ","pages":"Article 103096"},"PeriodicalIF":3.5,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-dimensional optimization for collaborative task scheduling in cloud-edge-end system","authors":"Da Wu ,&nbsp;Zhuo Li ,&nbsp;Heping Shi ,&nbsp;Peng Luo ,&nbsp;Yongtao Ma ,&nbsp;Kaihua Liu","doi":"10.1016/j.simpat.2025.103099","DOIUrl":"10.1016/j.simpat.2025.103099","url":null,"abstract":"<div><div>As we all know, Mobile Edge Computing (MEC) can effectively reduce data transmission delay by scheduling tasks to edge servers. However, current research often fails to comprehensively evaluate the joint impact of key factors such as server location, service placement decision, caching ratio, computing power, computation offloading ratio, and offloading location on the effectiveness of task scheduling, which to a certain extent limits the comprehensiveness and effectiveness of task scheduling strategies. Moreover, in practical engineering applications, it is particularly crucial to comprehensively consider the key factors for the placement of edge devices. In view of this, this paper proposes a multi-dimensional optimization model for task scheduling that jointly considers factors such as Server placement, Service placement, Caching placement, Resource allocation, and Computation offloading (SSCRC) in a cloud-edge-end collaborative system. This model transforms the task scheduling multi-dimensional optimization problem into a Mixed Integer Nonlinear Programming (MINLP) problem to high-quality feasible solutions. To address this complex problem, we adopt a Branch-and-Bound with Parallel Interior Point (BBPIP) algorithm to obtain the optimal solution. Simulation results show that compared with several other schemes, the proposed scheme SSCRC exhibits significant performance improvements in terms of average delay, energy consumption and load balancing.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"141 ","pages":"Article 103099"},"PeriodicalIF":3.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143592715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiphysics thermo-fluid modeling and experimental validation of crater formation and rim development in EDM of inconel C-276","authors":"Panagiotis Karmiris-Obratański","doi":"10.1016/j.simpat.2025.103097","DOIUrl":"10.1016/j.simpat.2025.103097","url":null,"abstract":"<div><div>Electric Discharge Machining (EDM) is a non-conventional process well-suited for machining hard-to-machine materials, offering high dimensional accuracy and an acceptable surface finish where traditional methods fall short. This study investigates the machining of Hastelloy C-276 using a composite copper-tungsten electrode through a combined experimental approach and a multiphysics thermo-fluid FEM model to simulate crater formation. The model incorporates a Gaussian heat source, energy absorption coefficients, and molten material flow under plasma pressure gradients, considering latent heat, mushy zone viscosity, and temperature-dependent thermophysical properties. Results indicate that optimizing plasma flushing efficiency (∼30 %) at low current and pulse-on time (9 A, 50 µs) enhances material removal while minimizing white layer formation. Higher pulse-on times lead to increased white layer thickness, stabilizing at 25 [A] and 200 [µs]. Surface roughness rises by 33.3 % at 9 [A] and up to 40 % at 25 [A] as pulse duration extends from 50 to 200 µs, highlighting the influence of increased energy input. The model accurately predicts material removal rates and white layer thicknesses, with deviations of 1–5 % from experimental results. These findings provide insights for optimizing EDM parameters to balance material removal efficiency, surface integrity, and process stability.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"141 ","pages":"Article 103097"},"PeriodicalIF":3.5,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Edge-computing-enabled hybrid and multi-objective geographic routing for mesh IoT networks: An IMOGWO-based approach","authors":"Sihem Tlili ,&nbsp;Sami Mnasri ,&nbsp;Thierry Val","doi":"10.1016/j.simpat.2025.103093","DOIUrl":"10.1016/j.simpat.2025.103093","url":null,"abstract":"<div><div>Due to their robustness and resource limitations, IoT objects pose several multi-objective optimization challenges, making routing in mesh IoT networks a critical issue. Meanwhile, meta-heuristic and multi-objective optimization approaches provide promising results. This paper proposes a novel geographic, hybrid and multi-objective routing method for IoT mesh networks. Routing is formulated as an optimization problem with multiple objective functions. The proposed Improved Multi-Objective Gray Wolf Optimizer (IMOGWO) meta-heuristic is applied between communicating objects in a distributed manner to solve and optimize routing decisions. The work presents the first application and evaluation of IMOGWO to a real-world problem, specifically routing in IoT mesh networks. Combined IoT simulations (using both real and simulated nodes) are performed to evaluate the introduced approach and show its effectiveness in comparison to other existing routing methods, including MOGWO-based routing, an AcNSGA-III-based QoS routing and a BFOA-based geographic routing algorithm. Results indicate that the proposed approach enhances network performance. Particularly, IMOGWO increases the stability period by 9.30% compared to MOGWO, 20.51% compared to AcNSGA-III and 38.24% compared to BFOA. In addition, it ensures a better packet delivery ratio (92.2%). Furthermore, it maintains a lower average transmission latency (1.93s) than AcNSGA-III and BFOA. These improvements, validated through inferential statistical tests, demonstrate that IMOGWO optimizes routing for IoT mesh networks effectively.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"140 ","pages":"Article 103093"},"PeriodicalIF":3.5,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143463467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Active learning confidence measures for coupling strategies in digital twins integrating simulation and data-driven submodels","authors":"Sylvain Chabanet,&nbsp;Hind Bril El-Haouzi,&nbsp;Philippe Thomas","doi":"10.1016/j.simpat.2025.103092","DOIUrl":"10.1016/j.simpat.2025.103092","url":null,"abstract":"<div><div>Many challenges have been raised in the scientific literature regarding the development of digital twins that can predict future states of production processes from data streams. This study is concerned with the coordination of several of their submodels to balance precision with computational requirements. A method to use stream-based active learning sampling strategies to couple two such models is proposed. Both models perform the same prediction task but have different advantages and disadvantages. The first is a simulation model that is supposed to have a high fidelity level, but to be slow. The second is a machine learning model, which is fast but less accurate and requires many labeled examples to be trained on, which may require a lot of time and effort to gather. The objective is to leverage confidence measures in the predictions of the machine learning model. These measures are used to couple the two models and take advantage of their respective strengths. In particular, the aim is to reduce the digital twin’s average prediction error while operating under limited computational capacity. Moreover, an application within the sawmill industry and numerical experiments are presented.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"140 ","pages":"Article 103092"},"PeriodicalIF":3.5,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3D vision object detection for autonomous driving in fog using LiDaR","authors":"Alishba Tahir,&nbsp;Rafia Mumtaz,&nbsp;Muhammad Saqib Irshad","doi":"10.1016/j.simpat.2025.103089","DOIUrl":"10.1016/j.simpat.2025.103089","url":null,"abstract":"<div><div>Connected and Autonomous Vehicles (CAVs) are transforming transportation. The paper describes a new method of fog simulation applied to LiDAR data for self-driving cars with a focus on enhancing 3D object detection in low visibility conditions. As opposed to the previously used methods, synthetic fog augmentation is combined with deep learning models and it is proven that the proposed method is superior to the previous methods when it comes to object detection accuracy in various fog levels. Another challenge that has been discussed in the study to ensure the reliability of autonomous navigation is the question of how the fog and the LiDAR point cloud should be modeled which eventually helps in improving the decision-making safety and operation. Fog can drastically reduce visibility and safety, making it crucial to test LiDAR-based perception algorithms for CAVs under such conditions. These simulations aim to ensure CAVs can navigate safely and efficiently through fog. However, challenges like sensor calibration and data integration need to be addressed. Despite these hurdles, the research foresees a future where CAVs, equipped with advanced LiDAR-based perception algorithms and fog-handling capabilities, enhance safety and efficiency in transportation. Notably, using synthetic fog augmentation improved detection by 5.27% for cars and 8.11% for cyclists. Furthermore, the study showcases improvements of 4.76%, 2.92%, and 3% in Mean Average Precision (mAP) across the distinct object categories of easy, moderate, and hard difficulty levels, respectively.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"140 ","pages":"Article 103089"},"PeriodicalIF":3.5,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computation offloading and task caching in the cloud–edge collaborative IoVs: A multi-objective evolutionary algorithm","authors":"Zi-xin Chai ,&nbsp;Zheng-yi Chai ,&nbsp;Junjun Ren ,&nbsp;Dong Yuan","doi":"10.1016/j.simpat.2025.103087","DOIUrl":"10.1016/j.simpat.2025.103087","url":null,"abstract":"<div><div>With rapid development of Internet of Vehicles (IoVs), various computation-intensive vehicular applications impose great challenges on the limited computing resources of vehicles. To improve the user experience of vehicular applications, the emerging vehicular edge computing (VEC) offloads tasks to roadside edge servers. However, competition over communication and computing resources is inevitable among vehicles. How to make optimal task offloading decisions for vehicles, so as to reduce delay, balance server load and save energy, is worth researching in-depth. In this paper, first, a vehicle-to-vehicle (V2V) communication path acquisition algorithm is designed, and a task caching mechanism introduced which cache some completed applications and related codes on the edge server. Then, a vehicular networking model with joint task caching mechanism for edge–cloud collaboration is proposed. To obtain the near-optimal solutions to this problem, we design a multi-objective evolutionary algorithm based joint task caching and edge–cloud computing decision algorithm (JTCEC-MOEA/D) to maximize the utilities of vehicles. Finally, the proposed algorithm is evaluated by the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The simulation results show that the proposed algorithm can make optimal task offloading-making for vehicles.</div></div>","PeriodicalId":49518,"journal":{"name":"Simulation Modelling Practice and Theory","volume":"141 ","pages":"Article 103087"},"PeriodicalIF":3.5,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143486607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}