{"title":"电网5G网络切片确定性服务质量保障研究","authors":"Lv Yuxiang, Xiang Hui, Chen Julong, Wang Hongyan, Wu Hui, Dong Yawen","doi":"10.1109/ITNEC56291.2023.10082638","DOIUrl":null,"url":null,"abstract":"Providing end-to-end and deterministic service level protocols for different power services, such as bandwidth, delay, packet loss rate, delay jitter, and resource isolation degree, is one of the key technologies to support complex and heterogeneous power grid business data transmission in 5G network slices. The optimization problem of cross-layer resource collaboration for 5G network slicing service function chain has been proved to be NP-Hard. In order to solve this problem, we propose a two-layer iterative optimization algorithm to solve the slice deployment and application strategy of electric 5G network under the constraint of multi-service level agreement index, so as to realize the deterministic guarantee of business communication requirements. The outer iteration of the algorithm adopted the fastest gradient method, and the initial value of the inner iteration was dynamically adjusted by checking the penalty weight of constraints. The memory iteration adopted the swarm intelligent optimization method to obtain the optimal solution. After two-layer iterative optimization, the optimal solution of cross-layer resource allocation of the 5G network slicing service function chain was finally obtained. Numerical simulation results show that this algorithm has the advantages of fast convergence and low computational complexity.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"113 S10","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on deterministic service quality guarantee for 5G network slice in power grid\",\"authors\":\"Lv Yuxiang, Xiang Hui, Chen Julong, Wang Hongyan, Wu Hui, Dong Yawen\",\"doi\":\"10.1109/ITNEC56291.2023.10082638\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Providing end-to-end and deterministic service level protocols for different power services, such as bandwidth, delay, packet loss rate, delay jitter, and resource isolation degree, is one of the key technologies to support complex and heterogeneous power grid business data transmission in 5G network slices. The optimization problem of cross-layer resource collaboration for 5G network slicing service function chain has been proved to be NP-Hard. In order to solve this problem, we propose a two-layer iterative optimization algorithm to solve the slice deployment and application strategy of electric 5G network under the constraint of multi-service level agreement index, so as to realize the deterministic guarantee of business communication requirements. The outer iteration of the algorithm adopted the fastest gradient method, and the initial value of the inner iteration was dynamically adjusted by checking the penalty weight of constraints. The memory iteration adopted the swarm intelligent optimization method to obtain the optimal solution. After two-layer iterative optimization, the optimal solution of cross-layer resource allocation of the 5G network slicing service function chain was finally obtained. Numerical simulation results show that this algorithm has the advantages of fast convergence and low computational complexity.\",\"PeriodicalId\":218770,\"journal\":{\"name\":\"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)\",\"volume\":\"113 S10\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITNEC56291.2023.10082638\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNEC56291.2023.10082638","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on deterministic service quality guarantee for 5G network slice in power grid
Providing end-to-end and deterministic service level protocols for different power services, such as bandwidth, delay, packet loss rate, delay jitter, and resource isolation degree, is one of the key technologies to support complex and heterogeneous power grid business data transmission in 5G network slices. The optimization problem of cross-layer resource collaboration for 5G network slicing service function chain has been proved to be NP-Hard. In order to solve this problem, we propose a two-layer iterative optimization algorithm to solve the slice deployment and application strategy of electric 5G network under the constraint of multi-service level agreement index, so as to realize the deterministic guarantee of business communication requirements. The outer iteration of the algorithm adopted the fastest gradient method, and the initial value of the inner iteration was dynamically adjusted by checking the penalty weight of constraints. The memory iteration adopted the swarm intelligent optimization method to obtain the optimal solution. After two-layer iterative optimization, the optimal solution of cross-layer resource allocation of the 5G network slicing service function chain was finally obtained. Numerical simulation results show that this algorithm has the advantages of fast convergence and low computational complexity.