IEC Type 3: Android cloud native applications on Arm servers in edge for Integrated Edge Cloud (IEC) Blueprint Family

Use Case Details:

Attributes	Description	Informational
Type	New
Industry Sector	Telco, Cloud
Business driver	Edge cloud requires initiatives for cloud gaming on Android platform 5G + edge bring low latency and high-throughput for cloud gaming, which improves user experience More and more Android applications will migrate into edge compute platform. Building an android platform is necessary, and it's rigid demand.
Business use cases	Android Cloud Gaming AR/VR Android Application
Business Cost - Initial Build Cost Target Objective	Using virtualization technology instead of mobile chip board on ARM server will reduce the cost of android platform. ARM server board also let android platform more flexible and more agile. In order to support cloud gaming and AR/VR, ARM server need have GPU inside. 2 ARM Nodes Kubernetes v 1.17 for ARM Android 10.0 GPU (AMD, NVIDIA) Android virtualization layer: Anbox, docker.
Business Cost – Target Operational Objective	It more like a cloud platform, but it's specific for android application. It needs Helm and Ansible for the automation and management tools to keep operational cost lower It needs to monitor the status of android system status and application status. Maintain a mixed edge platform including x86 and ARM. It's more complex Kubernetes v1.17 for ARM Android 10.0 GPU (AMD, NVIDIA) Host OS kernel optimization; Android virtualization layer: Anbox, docker. GPU (AMD, NVIDIA) Both ARM and X86 can support it.
Security need	Security is very important in this use case, especially for containerized android system.
Regulations	N/A
Other restrictions	N/A
Additional details	N/A

Case Attributes	Description	Informational
Type	New
Blueprint Family - Proposed Name	Integrated Edge Cloud (IEC)
Use Case	Cloud Gaming and AR/VR
Blueprint proposed Name	IEC Type 3: Android cloud native applications on Arm servers in edge
Initial POD Cost (capex)	2 ARM bare metal machines, 1 10G switch, 1 AMD GPU, 1 NIVIDA GPU
Scale & Type	For the smallest deployment, this requires 2 ARM bare metal machines. For large deployments, this could span to large number of bare metal machines.
Applications	Android application, such as cloud gaming, VR/AR.
Power Restrictions	N/A
Infrastructure orchestration	Host: Orchestrator: Kubernetes Bare Metal Provisioning：Ansible Kubernetes Provisioning：KuD OS: Ubuntu GPU Driver: AMD,NVIDIA: Network: OVS Android virtualization layer: Anbox, docker. Host OS kernel optimization Guest OS Andriod: GPU Driver (AMD, NVIDIA)
SDN	N/A
Workload Type	Android applications
Additional Details	N/A

Committer	Committer Company	Committer Contact Info	Committer Bio	Committer Picture	Self Nominate for PTL (Y/N)
JiaXuan	China Mobile	jiaxuan@chinamobile.com
Yongsu Zhang	ByteDance	zhangyongsu@bytedance.com
Kairui She	ByteDance	shekairui@bytedance.com
Shi Lei	China Mobile	shileiyj@chinamobile.com
Trevor Tao (Deactivated)	Arm	trevor.tao@arm.com
Jingzhao Ni (Arm Technology China) (Deactivated)	Arm	jingzhao.ni@arm.com
Jianlin Lv (Arm Technology China) (Deactivated)	Arm	jianlin.lv@arm.com
Hanyu Ding	China Mobile	dinghanyu@chinamobile.com
Wang WeiXun	Mobile Intelligence Cloud

Mobile Intelligence Cloud（www.higgsgod.net） provide the Lab for integration and validation:

	TS2280v1	TS2280v2
CPU	2x 32 core 2.4 GHz Hi1616 Processors	2x 32 core 2.6 GHz Hi1620 Processors
RAM	8x 16GB RDIMM-Tx2	8x 16GB DDR4-DIMM
Storage	2x 1TB SSD	2x 1TB SSD
Networking	2x 1/10Gbe BASE-T (1 connected) 1x IPMI Lights-out Management	2x 1/10Gbe SFP+ (connected) 1x IPMI / Lights-out Management
GPU	1 AMD GPU ,1 NVidia GPU

Servers and Switches

Server Name	IPMI Address	Public Network Address	Switch Port(s)	OS Installed
93	10.x	10.x	gigabyte-edgecore2: left 40Bbe Port 1, right 40Gbe Port 2, left 10Gbe Port 7 Breakout 1, right 10Gbe Port 7 Breakout 2	Ubuntu 18.04
174	10.x	10.x	gigabyte-edgecore2: left 40Bbe Port 3, right 40Gbe Port 4, left 10Gbe Port 7 Breakout 3, right 10Gbe Port 7 Breakout 4	Ubuntu 18.04

BP: