Pub Date : 2022-09-26DOI: 10.1109/DS-RT55542.2022.9932054
Vikash Kumar
Determining Worst-Case Execution Time (WCET) is essential for temporal verification of Real-Time and Embedded Systems. These systems are designed to meet the stringent timing constraints imposed by the regulations. If a system gets delayed due to non-compliance with the deadline, it will lead to disastrous events. Worst-Case Data which gives maximum execution time, plays a vital role in the estimation of WCET. An evolutionary algorithm such as the Genetic Algorithm has been employed to generate the Worst-Case Data. The complexity of an evolutionary algorithm requires the use of several computational resources. This paper presents a novel method to replace the hardware and simulator used in the evolution process with machine learning models. This method reduces the overall time required to generate Worst-Case Data. Different machine learning models are trained to integrate with genetic algorithms. Our machine learning models are created using the Pygad Framework. The feasibility of the proposed approach is validated using benchmarks from different domains. The results show the speedup in the generation of Worst-Case Data.
{"title":"An integrated approach of Genetic Algorithm and Machine Learning for generation of Worst-Case Data for Real-Time Systems","authors":"Vikash Kumar","doi":"10.1109/DS-RT55542.2022.9932054","DOIUrl":"https://doi.org/10.1109/DS-RT55542.2022.9932054","url":null,"abstract":"Determining Worst-Case Execution Time (WCET) is essential for temporal verification of Real-Time and Embedded Systems. These systems are designed to meet the stringent timing constraints imposed by the regulations. If a system gets delayed due to non-compliance with the deadline, it will lead to disastrous events. Worst-Case Data which gives maximum execution time, plays a vital role in the estimation of WCET. An evolutionary algorithm such as the Genetic Algorithm has been employed to generate the Worst-Case Data. The complexity of an evolutionary algorithm requires the use of several computational resources. This paper presents a novel method to replace the hardware and simulator used in the evolution process with machine learning models. This method reduces the overall time required to generate Worst-Case Data. Different machine learning models are trained to integrate with genetic algorithms. Our machine learning models are created using the Pygad Framework. The feasibility of the proposed approach is validated using benchmarks from different domains. The results show the speedup in the generation of Worst-Case Data.","PeriodicalId":243042,"journal":{"name":"2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"277 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122854121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-26DOI: 10.1109/DS-RT55542.2022.9932047
J. Possik, D. Azar, A. Solis, A. Asgary, G. Zacharewicz, Abir Karami, M. Tofighi, M. Najafabadi, Mohammad Ali Shafiee, Asad A Merchant, M. Aarabi, Jianhong Wu
In order to monitor and assess the spread of the Omicron variant of COVID-19, we propose a Distributed Digital Twin that virtually mirrors a hemodialysis unit in a hospital in Toronto, Canada. Since the solution involves heterogeneous components, we rely on the IEEE HLA distributed simulation standard. Based on the standard, we use an agent-based/discrete event simulator together with a virtual reality environment in order to provide to the medical staff an immersive experience that incorporates a platform showing predictive analytics during a simulation run. This can help professionals monitor the number of exposed, symptomatic, asymptomatic, recovered, and deceased agents. Agents are modeled using a redesigned version of the susceptible-exposed-infected-recovered (SEIR) model. A contact matrix is generated to help identify those agents that increase the risk of the virus transmission within the unit.
{"title":"A distributed digital twin implementation of a hemodialysis unit aimed at helping prevent the spread of the Omicron COVID-19 variant","authors":"J. Possik, D. Azar, A. Solis, A. Asgary, G. Zacharewicz, Abir Karami, M. Tofighi, M. Najafabadi, Mohammad Ali Shafiee, Asad A Merchant, M. Aarabi, Jianhong Wu","doi":"10.1109/DS-RT55542.2022.9932047","DOIUrl":"https://doi.org/10.1109/DS-RT55542.2022.9932047","url":null,"abstract":"In order to monitor and assess the spread of the Omicron variant of COVID-19, we propose a Distributed Digital Twin that virtually mirrors a hemodialysis unit in a hospital in Toronto, Canada. Since the solution involves heterogeneous components, we rely on the IEEE HLA distributed simulation standard. Based on the standard, we use an agent-based/discrete event simulator together with a virtual reality environment in order to provide to the medical staff an immersive experience that incorporates a platform showing predictive analytics during a simulation run. This can help professionals monitor the number of exposed, symptomatic, asymptomatic, recovered, and deceased agents. Agents are modeled using a redesigned version of the susceptible-exposed-infected-recovered (SEIR) model. A contact matrix is generated to help identify those agents that increase the risk of the virus transmission within the unit.","PeriodicalId":243042,"journal":{"name":"2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133052984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-26DOI: 10.1109/DS-RT55542.2022.9932080
Luca Serena, M. Marzolla, Gabriele D’angelo, S. Ferretti
Multilevel modeling is increasingly relevant in the context of modelling and simulation since it leads to several potential benefits, such as software reuse and integration, the split of semantically separated levels into sub-models, the possibility to employ different levels of detail, and the potential for parallel execution. The coupling that inevitably exists between the sub-models, however, implies the need for maintaining consistency between the various components, more so when different simulation paradigms are employed (e.g., sequential vs parallel, discrete vs continuous). In this paper we argue that multilevel modelling is well suited for the simulation of human mobility, since it naturally leads to the decomposition of the model into two layers, the “micro” and “macro” layer, where individual entities (micro) and long-range interactions (macro) are described. In this paper we investigate the challenges of multilevel modeling, and describe some preliminary results using prototype implementations of multilayer simulators in the context of epidemic diffusion and vehicle pollution.
{"title":"Multilevel Modeling as a Methodology for the Simulation of Human Mobility","authors":"Luca Serena, M. Marzolla, Gabriele D’angelo, S. Ferretti","doi":"10.1109/DS-RT55542.2022.9932080","DOIUrl":"https://doi.org/10.1109/DS-RT55542.2022.9932080","url":null,"abstract":"Multilevel modeling is increasingly relevant in the context of modelling and simulation since it leads to several potential benefits, such as software reuse and integration, the split of semantically separated levels into sub-models, the possibility to employ different levels of detail, and the potential for parallel execution. The coupling that inevitably exists between the sub-models, however, implies the need for maintaining consistency between the various components, more so when different simulation paradigms are employed (e.g., sequential vs parallel, discrete vs continuous). In this paper we argue that multilevel modelling is well suited for the simulation of human mobility, since it naturally leads to the decomposition of the model into two layers, the “micro” and “macro” layer, where individual entities (micro) and long-range interactions (macro) are described. In this paper we investigate the challenges of multilevel modeling, and describe some preliminary results using prototype implementations of multilayer simulators in the context of epidemic diffusion and vehicle pollution.","PeriodicalId":243042,"journal":{"name":"2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131984549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-26DOI: 10.1109/DS-RT55542.2022.9932038
Maximilian Neubauer, Géraldine Ruddeck, Karl Schrab, Robert Protzmann, I. Radusch
In this paper a pedestrian model is introduced that builds on the Social Force Model and enhances it with various features. The main goal of this model is to produce more natural looking pedestrian movements in 3D-visualizations. This model aims to generate more realistic trajectories in situations where pedestrians evade each other, for example on narrow sidewalks. Unlike the Social Force Model, it takes the current velocity and walking direction of surrounding pedestrians into account. Additionally, this model lets pedestrians react on approaching opponents sooner and reduces unnatural body rotations. Through the above mentioned features, collisions of pedestrians are reduced, as well.
{"title":"A Pedestrian Movement Model for 3D Visualization in a Driving Simulation Environment","authors":"Maximilian Neubauer, Géraldine Ruddeck, Karl Schrab, Robert Protzmann, I. Radusch","doi":"10.1109/DS-RT55542.2022.9932038","DOIUrl":"https://doi.org/10.1109/DS-RT55542.2022.9932038","url":null,"abstract":"In this paper a pedestrian model is introduced that builds on the Social Force Model and enhances it with various features. The main goal of this model is to produce more natural looking pedestrian movements in 3D-visualizations. This model aims to generate more realistic trajectories in situations where pedestrians evade each other, for example on narrow sidewalks. Unlike the Social Force Model, it takes the current velocity and walking direction of surrounding pedestrians into account. Additionally, this model lets pedestrians react on approaching opponents sooner and reduces unnatural body rotations. Through the above mentioned features, collisions of pedestrians are reduced, as well.","PeriodicalId":243042,"journal":{"name":"2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133083032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-26DOI: 10.1109/DS-RT55542.2022.9932042
Ahmad Almaksour, Hadi Gerges, S. Gorecki, G. Zacharewicz, J. Possik
Classical simulation methods become not flexible and performant enough in complex models, necessitating the use of a distributed simulation technique to split the load and heterogeneity into separate sub-components and manage the simulation time between them. In this type of simulation, interoperability and reusability issues arise and should be addressed. The IEEE High-Level Architecture (HLA) standard for distributed simulation emphasizes federates interoperability and reusability, as well as time management and advanced data distribution techniques. This paper presents the methodologies and techniques used to develop the HLA federates, as part of the Simulation Exploration Experience (SEE) project, to virtually recreate a mission on the moon. This project is organized by the National Aeronautics and Space Administration (NASA) and the Simulation Interoperability Standards Organization (SISO). For each SEE component, an HLA interface was developed to make it compliant with other SEE federates and reusable during the simulation run. Based on HLA mechanisms, heterogeneous components with an HLA interface were able to interexchange objects/attributes and interactions/parameters.
{"title":"The use of the IEEE HLA standard to tackle interoperability issues between heterogeneous components","authors":"Ahmad Almaksour, Hadi Gerges, S. Gorecki, G. Zacharewicz, J. Possik","doi":"10.1109/DS-RT55542.2022.9932042","DOIUrl":"https://doi.org/10.1109/DS-RT55542.2022.9932042","url":null,"abstract":"Classical simulation methods become not flexible and performant enough in complex models, necessitating the use of a distributed simulation technique to split the load and heterogeneity into separate sub-components and manage the simulation time between them. In this type of simulation, interoperability and reusability issues arise and should be addressed. The IEEE High-Level Architecture (HLA) standard for distributed simulation emphasizes federates interoperability and reusability, as well as time management and advanced data distribution techniques. This paper presents the methodologies and techniques used to develop the HLA federates, as part of the Simulation Exploration Experience (SEE) project, to virtually recreate a mission on the moon. This project is organized by the National Aeronautics and Space Administration (NASA) and the Simulation Interoperability Standards Organization (SISO). For each SEE component, an HLA interface was developed to make it compliant with other SEE federates and reusable during the simulation run. Based on HLA mechanisms, heterogeneous components with an HLA interface were able to interexchange objects/attributes and interactions/parameters.","PeriodicalId":243042,"journal":{"name":"2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117067235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-26DOI: 10.1109/DS-RT55542.2022.9932112
T. Potuzak
Road traffic simulation is one of the useful tools, which can help to cope with steadily increasing intensity of road traffic. A distributed or parallel computing environment can significantly speedup the simulation execution, but the road traffic network division is usually required. There are many existing methods for road traffic network division based on various approaches. However, there is a lack of surveys mapping these methods. For this reason, this paper is a survey of existing methods for road traffic network division published in last two decades. It is not a systematic review, as it does not try to answer specific scientific questions. Its purpose is to map and categorize the existing methods for road traffic network division and to summarize their common features. Such a survey can be useful as a good starting point for the related work exploration for any teams or individuals dealing with road traffic network division and distributed or parallel road traffic simulation.
{"title":"Current Trends in Road Traffic Network Division for Distributed or Parallel Road Traffic Simulation","authors":"T. Potuzak","doi":"10.1109/DS-RT55542.2022.9932112","DOIUrl":"https://doi.org/10.1109/DS-RT55542.2022.9932112","url":null,"abstract":"Road traffic simulation is one of the useful tools, which can help to cope with steadily increasing intensity of road traffic. A distributed or parallel computing environment can significantly speedup the simulation execution, but the road traffic network division is usually required. There are many existing methods for road traffic network division based on various approaches. However, there is a lack of surveys mapping these methods. For this reason, this paper is a survey of existing methods for road traffic network division published in last two decades. It is not a systematic review, as it does not try to answer specific scientific questions. Its purpose is to map and categorize the existing methods for road traffic network division and to summarize their common features. Such a survey can be useful as a good starting point for the related work exploration for any teams or individuals dealing with road traffic network division and distributed or parallel road traffic simulation.","PeriodicalId":243042,"journal":{"name":"2022 IEEE/ACM 26th International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129887675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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