Introduction

IEC  Akraino Edge Stack supports AR/VR  applications. It could support AR/VR Algorithms that with GPU Modeling (i.e. modeling describes the process of forming the shape of an object) Compositing (e.g. Environmental Mapping, Tone Mapping) Rendering and Illumination Models Visualization of Large Volume 3D Models (e.g. Global Network Operations Center monitoring) Registration (e.g. Stitching data from distributed sources) Segmentation (e.g. Segmentation and detection for security monitoring). This IEC Type 4 AR/VR platform utilizes Tars for remote direct memory access control. In this document, we use Virtual Classroom  as demo for IEC Type4.   Virtual Classroom is an online learning environment that allows teachers and students to communicate and interact with each other in real time. We use WebGL, Three.js and JavaScript to develop Virtual Classroom application.  

License

Apache License - V2

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K8STARS is a convenient solution to run TARS services in Kubernetes, and it has the following characteristics:
- Maintain the native development capability of TARS;
- Automatic registration and configuration deletion of name service for TARS;
- Support smooth migration of original TARS services to K8S and other container platforms;
- Non intrusive design, no coupling relationship with operating environment.

How K8STARS works?

1. Three interfaces are added in the tarsregistry, which are used for automatic registration, heartbeat reporting and node offline. For details, please refer to interface definition。

2. A 'tarscli' command-line tool is provided to allocate ports, generate configuration, report heartbeat and node offline.

Deployment

1. Deployment tars basic service

curl https://raw.githubusercontent.com/TarsCloud/K8STARS/master/baseserver/install_all.sh | sh
Deployment service example

2. Deploy sample simpleserver

cd examples/simple && kubectl apply -f simpleserver.yaml

Example description:

• The image is created by the examples/simple/dockerfile file, and the basic image is created by cmd/tarscli/dockerfile
• start.sh: tarscli genconf in is used to generate the tars service startup configuration
• server_ meta.yaml The file is used to configure the metadata of the service. For field information, please refer to app/genconf/config.go structure ServerConf . Endpoint defaults to tcp -h ${local_ip} -p ${random_port} , supports automatic filling of IP and random ports. -ased on Golang HelloWorld program TestApp.HelloGo See examples/README.md

3. Verify the deployment Login db_tars , then execute select * from t_server_conf\G The node information of simpleserver has been registered automatically.

• Install Virtual Classroom BackEnd

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Virtual Classroom demo includes two parts: (1) server side and (2) client side. The technologies used to develop these applications includes WebGL, Three.js and JavaScript.

The code could be find at:

git clone https://github.com/OpenVidu/openvidu-vr.git

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sed -i 's/demos.openvidu.io/${Local_IP_Address}/g' app.js

To execute:

docker run --rm --name openvidu_server -d -p 4443:4443 -e openvidu.secret=MY_SECRET -e openvidu.publicurl=https://${Local_IP_Address}:4443/ openvidu/openvidu-server-kms

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