2023 IEEE International Conference on Smart Computing (SMARTCOMP)最新文献_第6页

DOT - Digital Orchestration of Things DOT -数字编排的东西

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00064

Carlos Resende

引用次数: 0

Knowledge-embedded Prompt Learning for Zero-shot Social Media Text Classification 基于知识嵌入的社交媒体文本分类提示学习

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00054

Jingyi Li, Qi Chen, Wen Wang, Fangyu Wu

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SmartSys 2023 Organizing Committees SmartSys 2023组委会

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/smartcomp58114.2023.00015

引用次数: 0

Single Camera-enabled Reinforcement Learning Traffic Signal Control System supporting Life-long Assessment 支持终身评估的单摄像头强化学习交通信号控制系统

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00055

Toan V. Tran, Mina Sartipi

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TACSim: An Extendable Simulator for Task Allocation Mechanisms in CrowdSensing TACSim:一个可扩展的任务分配机制模拟器

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00027

Christine Bassem

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Cooperative Multi-Agent Reinforcement Learning for Large Scale Variable Speed Limit Control 大规模变限速控制的协同多智能体强化学习

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00036

Yuhang Zhang, Marcos Quiñones-Grueiro, William Barbour, Zhiyao Zhang, Joshua Scherer, Gautam Biswas, D. Work

{"title":"Cooperative Multi-Agent Reinforcement Learning for Large Scale Variable Speed Limit Control","authors":"Yuhang Zhang, Marcos Quiñones-Grueiro, William Barbour, Zhiyao Zhang, Joshua Scherer, Gautam Biswas, D. Work","doi":"10.1109/SMARTCOMP58114.2023.00036","DOIUrl":"https://doi.org/10.1109/SMARTCOMP58114.2023.00036","url":null,"abstract":"Variable speed limit (VSL) control has emerged as a promising traffic management strategy for enhancing safety and mobility. In this study, we introduce a multi-agent reinforcement learning framework for implementing a large-scale VSL system to address recurring congestion in transportation corridors. The VSL control problem is modeled as a Markov game, using only data widely available on freeways. By employing parameter sharing among all VSL agents, the proposed algorithm can efficiently scale to cover extensive corridors. The agents are trained using a reward structure that incorporates adaptability, safety, mobility, and penalty terms; enabling agents to learn a coordinated policy that effectively reduces spatial speed variations while minimizing the impact on mobility. Our findings reveal that the proposed algorithm leads to a significant reduction in speed variation, which holds the potential to reduce incidents. Furthermore, the proposed approach performs satisfactorily under varying traffic demand and compliance rates.","PeriodicalId":163556,"journal":{"name":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122723138","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: 1

ReplayMPC: A Fast Failure Recovery Protocol for Secure Multiparty Computation Applications using Blockchain ReplayMPC:用于使用区块链的安全多方计算应用程序的快速故障恢复协议

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00033

Oscar G. Bautista, K. Akkaya, Soamar Homsi

{"title":"ReplayMPC: A Fast Failure Recovery Protocol for Secure Multiparty Computation Applications using Blockchain","authors":"Oscar G. Bautista, K. Akkaya, Soamar Homsi","doi":"10.1109/SMARTCOMP58114.2023.00033","DOIUrl":"https://doi.org/10.1109/SMARTCOMP58114.2023.00033","url":null,"abstract":"Although recent performance improvements to Secure Multiparty Computation (SMPC) made it a practical solution for complex applications such as privacy-preserving machine learning (ML), other characteristics such as robustness are also critical for its practical viability. For instance, since ML training under SMPC may take longer times (e.g., hours or days in many cases), any interruption of the computation will require restarting the process, which results in more delays and waste of computing resources. While one can maintain exchanged SMPC messages in a separate database, their integrity and authenticity should be guaranteed to be able to re-use them later. Therefore, in this paper, we propose ReplayMPC, an efficient failure recovery mechanism for SMPC based on blockchain technology that enables resuming and re-synchronizing SMPC parties after any type of communication or system failures. Our approach allows SMPC parties to save computation state snapshots they use as restoration points during the recovery and then reproduce the last computation rounds by retrieving information from immutable messages stored on a blockchain. Our experiment results on Algorand blockchain show that recovery is much faster than starting the whole process from scratch, saving time, computation, and networking resources.","PeriodicalId":163556,"journal":{"name":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117145393","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

AnB: Application-in-a-Box to Rapidly Deploy and Self-optimize 5G Apps AnB:盒中应用，快速部署和自优化5G应用

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00028

Kunal Rao, Murugan Sankaradas, G. Coviello, Ciro Giuseppe De Vita, Gennaro Mellone, Wang-Pin Hsiung, S. Chakradhar

{"title":"AnB: Application-in-a-Box to Rapidly Deploy and Self-optimize 5G Apps","authors":"Kunal Rao, Murugan Sankaradas, G. Coviello, Ciro Giuseppe De Vita, Gennaro Mellone, Wang-Pin Hsiung, S. Chakradhar","doi":"10.1109/SMARTCOMP58114.2023.00028","DOIUrl":"https://doi.org/10.1109/SMARTCOMP58114.2023.00028","url":null,"abstract":"We present \"Application in a Box\" (AnB) product concept aimed at simplifying the deployment and operation of remote 5G applications. AnB comes pre-configured with all necessary hardware and software components, including sensors like cameras, hardware and software components for a local 5G wireless network, and 5G-ready apps. Enterprises can easily download additional apps from an App Store. Setting up a 5G infrastructure and running applications on it is a significant challenge, but AnB is designed to make it fast, convenient, and easy, even for those without extensive knowledge of software, computers, wireless networks, or AI-based analytics. With AnB, customers only need to open the box, set up the sensors, turn on the 5G networking and edge computing devices, and start running their applications. Our system software automatically deploys and optimizes the pipeline of microservices in the application on a tiered computing infrastructure that includes device, edge, and cloud computing. Application scalability, dynamic resource management, placement of critical tasks for low-latency response, and dynamic network bandwidth allocation for efficient 5G network usage are all automatically orchestrated.AnB offers cost savings, simplified setup and management, and increased reliability and security. We’ve implemented several real-world applications, such as collision prediction at busy traffic light intersections and remote construction site monitoring using video analytics. With AnB, deployment and optimization effort can be reduced from several months to just a few minutes. This is the first-of-its-kind approach to easing deployment effort and automating self-optimization of the application during system operation.","PeriodicalId":163556,"journal":{"name":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123082590","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

SmartSys 2023 Message from Workshop Co-Chairs and Technical Program Co-Chairs SmartSys 2023研讨会联合主席和技术项目联合主席的讲话

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/smartcomp58114.2023.00014

引用次数: 0

A Demo of Microservice for Customized Faulty Product Detection System in Smart Manufacturing 智能制造中定制故障产品检测系统的微服务演示

2023 IEEE International Conference on Smart Computing (SMARTCOMP) Pub Date : 2023-06-01 DOI: 10.1109/SMARTCOMP58114.2023.00040

Nitesh Bharot, M. Soderi, J. Breslin

{"title":"A Demo of Microservice for Customized Faulty Product Detection System in Smart Manufacturing","authors":"Nitesh Bharot, M. Soderi, J. Breslin","doi":"10.1109/SMARTCOMP58114.2023.00040","DOIUrl":"https://doi.org/10.1109/SMARTCOMP58114.2023.00040","url":null,"abstract":"Product failure detection in smart manufacturing is important because it allows manufacturers to quickly identify and isolate faulty products before they reach the end of the production line. In today’s fast-paced and highly competitive business environment, manufacturers need to quickly and accurately identify product failures to stay competitive and meet customer expectations. Previously the product quality was inspected manually and now it is examined using a machine learning algorithm to overcome the limitations of manual inspection. However, in the latter case AI and ML experts are required to do the task. Therefore, to overcome such dependency, this work proposes a microservice to allow the end user (an industry person, as well as an automated hardware/software agent) to test different combinations of data science and AI tools and technologies without any AI expertise. The proposed microservice exposes APIs that make it possible to select different combinations of feature selection, sampling, and classification algorithm. A demo environment with a Postman collection that includes few API calls to demonstrate how the proposed module enables customized selection to detect faulty products, is also discussed.","PeriodicalId":163556,"journal":{"name":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"357 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122802346","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