{"title":"实现异构服务器平台下高效的网络业务功能链部署","authors":"Yang Hu, Tao Li","doi":"10.1109/HPCA.2018.00013","DOIUrl":null,"url":null,"abstract":"Network Function Virtualization (NFV) aims to run software-implemented network functions on general hardware such as Commodity Off-the-Shelf (COTS) servers to trade the application-specific performance with generality and re-configurability. Nevertheless, with the wide adoption of general accelerators such as GPU, the researchers seek to boost the performance of software-based network functions while trying to maintain the reusability and programmability in the meantime. The Service Function Chain (SFC) is a key enabler of service flexibility of NFV. The network functions stitch into a chain to provide differentiated services to multi-tenants. However, our characterization results show that existing heterogeneous packet processing frameworks do not handle NFV SFC well since two new overheads, the aggregated processing overheads and co-existence interference overheads, are introduced by SFC.,,,, Motivated by our characterization, we propose NFCompass, a runtime framework that employs SFC re-organization technique and graph-partition based task scheduling technique to conquer the two challenges brought by SFC. By re-organizing the SFC components, the length and complexity of processing paths are reduced and the aggregated overheads are mitigated. By applying the graph-partition based task allocation, better load balance is achieved and the data transfer overheads are considerably reduced.","PeriodicalId":154694,"journal":{"name":"2018 IEEE International Symposium on High Performance Computer Architecture (HPCA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Enabling Efficient Network Service Function Chain Deployment on Heterogeneous Server Platform\",\"authors\":\"Yang Hu, Tao Li\",\"doi\":\"10.1109/HPCA.2018.00013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network Function Virtualization (NFV) aims to run software-implemented network functions on general hardware such as Commodity Off-the-Shelf (COTS) servers to trade the application-specific performance with generality and re-configurability. Nevertheless, with the wide adoption of general accelerators such as GPU, the researchers seek to boost the performance of software-based network functions while trying to maintain the reusability and programmability in the meantime. The Service Function Chain (SFC) is a key enabler of service flexibility of NFV. The network functions stitch into a chain to provide differentiated services to multi-tenants. However, our characterization results show that existing heterogeneous packet processing frameworks do not handle NFV SFC well since two new overheads, the aggregated processing overheads and co-existence interference overheads, are introduced by SFC.,,,, Motivated by our characterization, we propose NFCompass, a runtime framework that employs SFC re-organization technique and graph-partition based task scheduling technique to conquer the two challenges brought by SFC. By re-organizing the SFC components, the length and complexity of processing paths are reduced and the aggregated overheads are mitigated. By applying the graph-partition based task allocation, better load balance is achieved and the data transfer overheads are considerably reduced.\",\"PeriodicalId\":154694,\"journal\":{\"name\":\"2018 IEEE International Symposium on High Performance Computer Architecture (HPCA)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Symposium on High Performance Computer Architecture (HPCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCA.2018.00013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Symposium on High Performance Computer Architecture (HPCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA.2018.00013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enabling Efficient Network Service Function Chain Deployment on Heterogeneous Server Platform
Network Function Virtualization (NFV) aims to run software-implemented network functions on general hardware such as Commodity Off-the-Shelf (COTS) servers to trade the application-specific performance with generality and re-configurability. Nevertheless, with the wide adoption of general accelerators such as GPU, the researchers seek to boost the performance of software-based network functions while trying to maintain the reusability and programmability in the meantime. The Service Function Chain (SFC) is a key enabler of service flexibility of NFV. The network functions stitch into a chain to provide differentiated services to multi-tenants. However, our characterization results show that existing heterogeneous packet processing frameworks do not handle NFV SFC well since two new overheads, the aggregated processing overheads and co-existence interference overheads, are introduced by SFC.,,,, Motivated by our characterization, we propose NFCompass, a runtime framework that employs SFC re-organization technique and graph-partition based task scheduling technique to conquer the two challenges brought by SFC. By re-organizing the SFC components, the length and complexity of processing paths are reduced and the aggregated overheads are mitigated. By applying the graph-partition based task allocation, better load balance is achieved and the data transfer overheads are considerably reduced.