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Real-Time Adaptive Anomaly Detection in Industrial IoT Environments 工业物联网环境中的实时自适应异常检测
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-21 DOI: 10.1109/tnsm.2024.3447532
Mahsa Raeiszadeh, Amin Ebrahimzadeh, Roch H. Glitho, Johan Eker, Raquel A. F. Mini
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引用次数: 0
Group Feature Aggregation for Web Service Recommendations 针对网络服务推荐的群体特征聚合
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-19 DOI: 10.1109/tnsm.2024.3444275
Yong Xiao, Jianxun Liu, Guosheng Kang, Buqing Cao
{"title":"Group Feature Aggregation for Web Service Recommendations","authors":"Yong Xiao, Jianxun Liu, Guosheng Kang, Buqing Cao","doi":"10.1109/tnsm.2024.3444275","DOIUrl":"https://doi.org/10.1109/tnsm.2024.3444275","url":null,"abstract":"","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"27 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187225","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}
引用次数: 0
DLLF-2EN: Energy-Efficient Next Generation Mobile Network With Deep Learning-Based Load Forecasting DLLF-2EN:基于深度学习负载预测的高能效下一代移动网络
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-19 DOI: 10.1109/tnsm.2024.3445369
Xin Wang, Jianhui Lv, Adam Slowik, B.D. Parameshachari, Keqin Li, Chien-Ming Chen, Saru Kumari
{"title":"DLLF-2EN: Energy-Efficient Next Generation Mobile Network With Deep Learning-Based Load Forecasting","authors":"Xin Wang, Jianhui Lv, Adam Slowik, B.D. Parameshachari, Keqin Li, Chien-Ming Chen, Saru Kumari","doi":"10.1109/tnsm.2024.3445369","DOIUrl":"https://doi.org/10.1109/tnsm.2024.3445369","url":null,"abstract":"","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"38 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187226","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}
引用次数: 0
Joint Optimization of Microservice Deployment and Routing in Edge via Multi-Objective Deep Reinforcement Learning 通过多目标深度强化学习对边缘微服务部署和路由进行联合优化
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-19 DOI: 10.1109/tnsm.2024.3443872
Menglan Hu, Hao Wang, Xiaohui Xu, Jianwen He, Yi Hu, Tianping Deng, Kai Peng
{"title":"Joint Optimization of Microservice Deployment and Routing in Edge via Multi-Objective Deep Reinforcement Learning","authors":"Menglan Hu, Hao Wang, Xiaohui Xu, Jianwen He, Yi Hu, Tianping Deng, Kai Peng","doi":"10.1109/tnsm.2024.3443872","DOIUrl":"https://doi.org/10.1109/tnsm.2024.3443872","url":null,"abstract":"","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"18 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187224","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}
引用次数: 0
Cloud-Edge-End Collaborative Intelligent Service Computation Offloading: A Digital Twin Driven Edge Coalition Approach for Industrial IoT 云-端协作智能服务计算卸载:面向工业物联网的数字孪生驱动边缘联盟方法
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-19 DOI: 10.1109/tnsm.2024.3441231
Xiaohuan Li, Bitao Chen, Junchuan Fan, Jiawen Kang, Jin Ye, Xun Wang, Dusit Niyato
{"title":"Cloud-Edge-End Collaborative Intelligent Service Computation Offloading: A Digital Twin Driven Edge Coalition Approach for Industrial IoT","authors":"Xiaohuan Li, Bitao Chen, Junchuan Fan, Jiawen Kang, Jin Ye, Xun Wang, Dusit Niyato","doi":"10.1109/tnsm.2024.3441231","DOIUrl":"https://doi.org/10.1109/tnsm.2024.3441231","url":null,"abstract":"","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"44 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187228","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}
引用次数: 0
A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features 基于非线性增强显性特征的跨域入侵检测方法
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-16 DOI: 10.1109/tnsm.2024.3444909
Xu Yu, Yan Lu, Feng Jiang, Qiang Hu, Junwei Du, Dunwei Gong
{"title":"A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features","authors":"Xu Yu, Yan Lu, Feng Jiang, Qiang Hu, Junwei Du, Dunwei Gong","doi":"10.1109/tnsm.2024.3444909","DOIUrl":"https://doi.org/10.1109/tnsm.2024.3444909","url":null,"abstract":"","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"7 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187227","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}
引用次数: 0
A Reinforcement Learning Approach for D2D Spectrum Sharing in Wireless Industrial URLLC Networks 无线工业 URLLC 网络中 D2D 频谱共享的强化学习方法
IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-16 DOI: 10.1109/TNSM.2024.3445123
Idayat O. Sanusi;Karim M. Nasr
Distributed Radio Resource Management (RRM) solutions are gaining an increasing interest recently, especially when a large number of devices are present as in the case of a wireless industrial network. Self-organisation relying on distributed RRM schemes is envisioned to be one of the key pillars of 5G and beyond Ultra Reliable Low Latency Communication (URLLC) networks. Reinforcement learning is emerging as a powerful distributed technique to facilitate self-organisation. In this paper, spectrum sharing in a Device-to-Device (D2D)-enabled wireless network is investigated, targeting URLLC applications. A distributed scheme denoted as Reinforcement Learning Based Matching (RLBM) which combines reinforcement learning and matching theory, is presented with the aim of achieving an autonomous device-based resource allocation. A distributed local Q-table is used to avoid global information gathering and a stateless Q-learning approach is adopted, therefore reducing requirements for a large state-action mapping. Simulation case studies are used to verify the performance of the presented approach in comparison with other RRM techniques. The presented RLBM approach results in a good tradeoff of throughput, complexity and signalling overheads while maintaining the target Quality of Service/Experience (QoS/QoE) requirements of the different users in the network.
最近,分布式无线资源管理(RRM)解决方案越来越受到人们的关注,尤其是在无线工业网络中存在大量设备的情况下。依靠分布式 RRM 方案实现的自组织被认为是 5G 及以后的超可靠低延迟通信(URLLC)网络的关键支柱之一。强化学习正在成为促进自组织的一种强大的分布式技术。本文以 URLLC 应用为目标,研究了设备到设备(D2D)无线网络中的频谱共享。本文提出了一种名为 "基于强化学习的匹配"(RLBM)的分布式方案,该方案结合了强化学习和匹配理论,旨在实现基于设备的自主资源分配。该方案使用分布式本地 Q 表来避免全局信息收集,并采用无状态 Q 学习方法,从而降低了对大型状态-行动映射的要求。仿真案例研究用于验证所提出的方法与其他 RRM 技术相比的性能。所提出的 RLBM 方法在吞吐量、复杂性和信号开销之间实现了良好的权衡,同时保持了网络中不同用户对服务质量/体验(QoS/QoE)的目标要求。
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引用次数: 0
Collaborative Cloud Resource Management and Task Consolidation Using JAYA Variants 使用 JAYA 变体进行协作式云资源管理和任务整合
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-14 DOI: 10.1109/tnsm.2024.3443285
Kaushik Mishra, Santosh Kumar Majhi, Kshira Sagar Sahoo, Sourav Kumar Bhoi, Monowar Bhuyan, Amir H. Gandomi
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引用次数: 0
Machine Learning-Based Reliable Transmission for UAV Networks With Hybrid Multiple Access 基于机器学习的混合多址无人机网络可靠传输
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-14 DOI: 10.1109/tnsm.2024.3443644
Yibo Zhang, Xiangwang Hou, Guoyu Du, Qi Li, Mian Ahmad Jan, Alireza Jolfaei, Muhammad Usman
{"title":"Machine Learning-Based Reliable Transmission for UAV Networks With Hybrid Multiple Access","authors":"Yibo Zhang, Xiangwang Hou, Guoyu Du, Qi Li, Mian Ahmad Jan, Alireza Jolfaei, Muhammad Usman","doi":"10.1109/tnsm.2024.3443644","DOIUrl":"https://doi.org/10.1109/tnsm.2024.3443644","url":null,"abstract":"","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"60 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224454","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}
引用次数: 0
Quantum Scheme for Privacy-Preserving Range MAX/MIN Query in Edge-Based Internet of Things 基于边缘的物联网中保护隐私的范围 MAX/MIN 查询量子方案
IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-08-13 DOI: 10.1109/tnsm.2024.3442826
Run-Hua Shi, Xia-Qin Fang
{"title":"Quantum Scheme for Privacy-Preserving Range MAX/MIN Query in Edge-Based Internet of Things","authors":"Run-Hua Shi, Xia-Qin Fang","doi":"10.1109/tnsm.2024.3442826","DOIUrl":"https://doi.org/10.1109/tnsm.2024.3442826","url":null,"abstract":"","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"18 1","pages":""},"PeriodicalIF":5.3,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142187229","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}
引用次数: 0
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IEEE Transactions on Network and Service Management
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