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2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)最新文献

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An Automated Deployment and Testing Framework for Resilient Distributed Smart Grid Applications 弹性分布式智能电网应用的自动化部署和测试框架
2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-06-27 DOI: 10.1109/COINS54846.2022.9854934
Purboday Ghosh, H. Tu, T. Krentz, G. Karsai, S. Lukic
{"title":"An Automated Deployment and Testing Framework for Resilient Distributed Smart Grid Applications","authors":"Purboday Ghosh, H. Tu, T. Krentz, G. Karsai, S. Lukic","doi":"10.1109/COINS54846.2022.9854934","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854934","url":null,"abstract":"Executing distributed cyber-physical software processes on edge devices that maintains the resiliency of the overall system while adhering to resource constraints is quite a challenging trade-off to consider for developers. Current approaches do not solve this problem of deploying software components to devices in a way that satisfies different resilience requirements that can be encoded by developers at design time. This paper introduces a resilient deployment framework that can achieve that by accepting user-defined constraints to optimize redundancy or cost for a given application deployment. Experiments with a microgrid energy management application developed using a decentralized software platform show that the deployment configuration can play an important role in enhancing the resilience capabilities of distributed applications as well as reducing the resource demands on individual nodes even without modifying the control logic.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115059935","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}
引用次数: 0
A Machine Learning-based Digital Twin for Electric Vehicle Battery Modeling 基于机器学习的电动汽车电池建模数字孪生
2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2022-06-16 DOI: 10.1109/COINS54846.2022.9854960
Khaled Alamin, Yukai Chen, E. Macii, M. Poncino, S. Vinco
{"title":"A Machine Learning-based Digital Twin for Electric Vehicle Battery Modeling","authors":"Khaled Alamin, Yukai Chen, E. Macii, M. Poncino, S. Vinco","doi":"10.1109/COINS54846.2022.9854960","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9854960","url":null,"abstract":"The widespread adoption of EVs is limited by their reliance on batteries with presently low energy and power densities compared to liquid fuels and are subject to aging and performance deterioration over time. For this reason, monitoring the battery state of charge and state of health during the EV lifetime is a very relevant problem. This work proposes the structure of a battery digital twin designed to reflect battery dynamics at the run time accurately. To ensure a high degree of correctness concerning non-linear phenomena, the digital twin relies on data-driven models trained on traces of battery evolution over time: a state of health model, repeatedly executed to estimate the degradation of maximum battery capacity, and a state of charge model, retrained periodically to reflect the impact of aging. The proposed digital twin structure will be exemplified on a public dataset to motivate its adoption and prove its effectiveness, with a high degree of accuracy and inference and retraining times compatible with onboard execution.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127112707","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}
引用次数: 2
Using Cyber Terrain in Reinforcement Learning for Penetration Testing 网络地形在渗透测试强化学习中的应用
2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 2021-08-16 DOI: 10.1109/COINS54846.2022.9855011
Rohit Gangupantulu, Tyler Cody, Paul Park, Abdul Rahman, Logan Eisenbeiser, Dan Radke, Ryan Clark
{"title":"Using Cyber Terrain in Reinforcement Learning for Penetration Testing","authors":"Rohit Gangupantulu, Tyler Cody, Paul Park, Abdul Rahman, Logan Eisenbeiser, Dan Radke, Ryan Clark","doi":"10.1109/COINS54846.2022.9855011","DOIUrl":"https://doi.org/10.1109/COINS54846.2022.9855011","url":null,"abstract":"Reinforcement learning (RL) has been applied to attack graphs for penetration testing, however, trained agents do not reflect reality because the attack graphs lack operational nuances typically captured within the intelligence preparation of the battlefield (IPB) that include notions of (cyber) terrain. In particular, current practice constructs attack graphs exclusively using the Common Vulnerability Scoring System (CVSS) and its components. We present methods for constructing attack graphs using notions from IPB on cyber terrain. We consider a motivating example where firewalls are treated as obstacles and represented in (1) the reward space and (2) the state dynamics. We show that terrain analysis can be used to bring realism to attack graphs for RL. We use an attack graph with roughly 1000 vertices and 2300 edges and deep Q reinforcement learning with experience replay to demonstrate the method.","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126981812","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}
引用次数: 23
Copyright Page 版权页
2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS) Pub Date : 1975-01-01 DOI: 10.1109/ispdc2018.2018.00003
{"title":"Copyright Page","authors":"","doi":"10.1109/ispdc2018.2018.00003","DOIUrl":"https://doi.org/10.1109/ispdc2018.2018.00003","url":null,"abstract":"","PeriodicalId":187055,"journal":{"name":"2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1975-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129519588","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}
引用次数: 0
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