CFN (Computing Force Network) Ubiquitous Computing Force Scheduling
BP State: Incubation BP. It has already been approved and voted by Akraino TSC Incubation Review at TSC 2022-06-28 (Tuesday) 7:00 am Pacific - Akraino - Akraino Confluence .
Use case
Attributes | Description | Informational |
Type | New |
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Industry Sector | V2X、artificial Intelligence app、enterprise OA |
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Business driver | Real World needs: -92 percent of respondents reported having a multi-cloud strategy* and has multi cloud vendors. -Hybrid cloud management including public cloud, on premise and edge cloud. -Multi-cluster deployment strategy to achieve high availability. -Disaster recovery scenario. The application system is usually deployed in the geo-redundant mode. -... |
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Business use cases | According to the CFN Ubiquitous Computing Force Scheduling, the computing force of public cloud, edge cloud and external third parties is managed to achieve consistent cluster, policy, configuration and traffic management, and to achieve resource-level and task-level scheduling. * Ubiquitous Computing Force concept：Logically, the computing force is more three-dimensional, including three levels: center, edge and terminal. Physically, resources span data centers in different regions. The kernel is heterogeneous, including general computing force ( x86/ARM ) and special computing force ( GPU/DPU... ). |
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Business Cost - Initial Build Cost Target Objective | Set up the infrastructure environment preparation to achieve multiple clusters management. Multi Cloud environment should be deployed in more than 3 servers in a single rack at a low cost. |
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Business Cost – Target Operational Objective | Build the Ubiquitous Computing Force Scheduling BP which includes: -Set up the infrastructure environment to achieve multiple clusters management, and expand cluster from central cloud to edge cloud; -Scheduling mechanism based on cloud-edge collaboration, such as traffic governance and scheduling across nodes; -The management and monitoring of cloud and edge clusters; -Enrich scheduling strategy;（such as latency, task type, etc.） |
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Security need | N/A |
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Regulations | N/A |
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Other restrictions | N/A |
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Additional details | N/A | more details see the attachment please |
Blueprint Species:
Case Attributes | Description | Informational |
Type | New |
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Blueprint Family - Proposed Name | CFN (Computing Force Network) family |
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Use Case | XR, Video Streaming, V2X，Ubiquitous Computing Force Scheduling |
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Blueprint proposed Name | CFN (Computing Force Network) Ubiquitous Computing Force Scheduling |
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Initial POD Cost (capex) | At least 10 virtual machines, depends on deployment scale |
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Scale & Type | For large deployments, this could span to large number of virtual machines. |
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Applications | XR, Video Streaming, V2X（to be discussed） |
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Power Restrictions | N/A |
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Infrastructure orchestration | Upstream: Docker/K8s - Container Orchestration
Upstream Project： -Karmada: https://github.com/karmada-io/karmada -Kurator: https://github.com/kurator-dev/kurator
OS - Linux, such as Ubuntu |
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SDN | N/A |
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Workload Type | container |
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Additional Details | N/A |
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Committer | Committer Company | Committer Contact Info | Committer Bio | Committer Picture | PTL |
Hanyu Ding | China Mobile |
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| Aug 4, 2022 to Aug 4, 2023 Approved at TSC 2022-08-04 (Thursday) 7:00 am Pacific - Akraino - Akraino Confluence | |
Kevin Wang | Huawei |
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Yanjun Chen | China Mobile |
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Lei Shi | China Mobile |
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Pengxiang Chen | China Mobile |
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Fanqin Zhou | BUPT |
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Baohong Ma | MIGU | mabaohong@migu.cn |
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Guangming Wang | MIGU | wangguangming@migu.cn |
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Zhonghu Xu | Huawei |
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Jianpeng He |
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Mengxuan Li | 4Paradigm |
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Contributor | Contributor Company | Contributor Contact Info | Contributor Bio | Contributor Picture |
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