IEEE international Symposium on Broadband Multimedia Systems and Broadcasting最新文献_第7页

Fault Management Platform based on Knowledge Graph in Network Slicing Environment 网络切片环境下基于知识图的故障管理平台

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211138

Detai Pan, Yunzhou Dong, Minglu Qi, Qiujia Fu, Zhengdong Lin, Guanliang Chen, Yingkun Liao, Peng Lin

{"title":"Fault Management Platform based on Knowledge Graph in Network Slicing Environment","authors":"Detai Pan, Yunzhou Dong, Minglu Qi, Qiujia Fu, Zhengdong Lin, Guanliang Chen, Yingkun Liao, Peng Lin","doi":"10.1109/BMSB58369.2023.10211138","DOIUrl":"https://doi.org/10.1109/BMSB58369.2023.10211138","url":null,"abstract":"In the network slicing environment, SDN and NFV technologies improve the utilization of network resources. However, these technologies lead to the greater dynamic nature of network resources and bring greater challenges to network fault management. Firstly, based on the analysis of network elements in network slicing environment, the fault management platform architecture in network slicing environment is proposed. Secondly, in order to improve the efficiency of the fault management mechanism, the knowledge graph is applied to the fault management field and the fault management knowledge graph is constructed. The functions that the knowledge framework can realize include fault prediction, elastic strategy, fault location, and fault self-healing. Finally, according to the requirements of fault management, a fault management question answering system based on knowledge graph is designed. From the two dimensions of business feasibility and implementation feasibility, the feasibility of the fault management platform is verified.","PeriodicalId":13080,"journal":{"name":"IEEE international Symposium on Broadband Multimedia Systems and Broadcasting","volume":"637 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78987306","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

Indoor Dual-indicator Precision Localization Network based on Multitask Learning 基于多任务学习的室内双指标精确定位网络

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211244

Ran An, Zexuan Jing, Quan Zhou, Junsheng Mu

引用次数: 0

Broadcast Service Technology Empowered by Integrated Communication and Navigation 以综合通信和导航为动力的广播服务技术

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211097

Huai Yang, Xingyu Hou, Xia Jing, Junsheng Mu

引用次数: 0

Microservice-based Fault Management Platform and Mechanism in Power Communication Network 基于微服务的电力通信网络故障管理平台与机制

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211140

Zhongmiao Kang, Zanhong Wu, Peiming Zhang, Donghai Huang, Chang Liu

{"title":"Microservice-based Fault Management Platform and Mechanism in Power Communication Network","authors":"Zhongmiao Kang, Zanhong Wu, Peiming Zhang, Donghai Huang, Chang Liu","doi":"10.1109/BMSB58369.2023.10211140","DOIUrl":"https://doi.org/10.1109/BMSB58369.2023.10211140","url":null,"abstract":"The power communication network uses SDN and NFV technology to improve the utilization of network resources, while bringing the characteristics of on-demand expansion and dynamic migration to the network. These new features pose new challenges to network fault management. To solve the problem that the existing research results lack an efficient fault management platform and mechanism for front-line maintenance personnel, this paper proposes a micro-service-based fault management platform and mechanism. Firstly, according to the technical composition and characteristics of the power communication network, the power communication network architecture is designed. Secondly, in order to make the network fault management mechanism programmable, fast adaptive, and dynamic, a fault management platform architecture based on microservices is designed according to the power communication network model, and the operation mechanisms of four business services, data collection, data processing, data analysis, and data view, are designed in detail. Finally, the feasibility of the platform and mechanism is analyzed from the four levels of the technical architecture.","PeriodicalId":13080,"journal":{"name":"IEEE international Symposium on Broadband Multimedia Systems and Broadcasting","volume":"35 6 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82799733","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

Configurable Rule Engine for Industrial Data Flow Scenarios 面向工业数据流场景的可配置规则引擎

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211632

Fangning Shi, Zhong Na, Zhifeng Gao

引用次数: 0

Mobile Edge Computing Tasking Offloading Strategy in Cell-Free Massive MIMO with Graph Neural Network 基于图神经网络的无小区大规模MIMO移动边缘计算任务卸载策略

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211224

Shiwei Li, Fangqing Tan, Qiang Liu

引用次数: 0

Blockchain-Aided Distributed Device-Free Wireless Sensing with IoT Devices in Edge Network 边缘网络中物联网设备的区块链辅助分布式无设备无线传感

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211278

Yanxi Xie, Ziyue Li, Chaoyi Li, Yonghui Zhu, Hao Zhang

引用次数: 0

Cost Minimization in Serverless Computing with Energy Harvesting SECs 利用能量收集sec实现无服务器计算的成本最小化

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211170

Yunqi Li, J. Liu, Bin Jiang, Chan-Ming Yang, Qingtian Wang

引用次数: 0

Simple Anomaly Detection Technique from Long-term Time-series Data by ATSC 3.0 Single Frequency Broadcast Network Monitoring System 基于ATSC 3.0单频广播网络监测系统的长期时间序列数据简单异常检测技术

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211288

S. Jeon, Seongman Min, Dawoon Chung, Kangsoo Kim, Jahoon Ku, Sunhyung Kwon, Sung-Ik Park

引用次数: 0

Logical-Cluster-Based Personalized Federated Multi-Task Learning for Internet of Vehicles 基于逻辑聚类的车联网个性化联合多任务学习

IEEE international Symposium on Broadband Multimedia Systems and Broadcasting Pub Date : 2023-06-14 DOI: 10.1109/BMSB58369.2023.10211135

Biao Zhang, Siya Xu, Xusong Qiu, Jingyue Tian

{"title":"Logical-Cluster-Based Personalized Federated Multi-Task Learning for Internet of Vehicles","authors":"Biao Zhang, Siya Xu, Xusong Qiu, Jingyue Tian","doi":"10.1109/BMSB58369.2023.10211135","DOIUrl":"https://doi.org/10.1109/BMSB58369.2023.10211135","url":null,"abstract":"Federated learning (FL) is an emerging distributed machine learning paradigm that emphasizes user privacy. The majority of current federated learning systems are oriented for single task while participants in the Internet of Vehicles (IoV) demand to train different models for multiple intelligent services simultaneously. As one of transfer learning methods, multi-task learning (MTL) has the potential to integrate with federated learning to realize personalized local training. However, the existing federated multi-task learning (FMTL) algorithms are faced with the problems of high implementation complexity and communication overhead. To solve the above issues, we propose a logical-cluster-based personalized federated multi-task learning framework named pFMTL. In the framework, the multi-task model is decomposed into a basic module for extracting features and K task-specific modules for outputting inferences. We leverage logical clusters and multi-task learning to enhance the personalization and generalization capability of task models, respectively. To improve the communication efficiency further, we also design a module-wise task scheduling strategy, which supports both user module scheduling and cluster aggregation scheduling to ensure the convergence of multi-task model with less communication overhead. Finally, the simulation results imply that pFMTL can increase task accuracy and reduce communication latency compared with other benchmarks.","PeriodicalId":13080,"journal":{"name":"IEEE international Symposium on Broadband Multimedia Systems and Broadcasting","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88805899","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