Overview

The purpose of this blueprint is an end-to-end technology solution for mobile game deployed across multiple heterogeneous edge nodes using various network access protocols such as mobile and WiFi and others. This blueprint demonstrates how an application leverages a distributed and multi access network edge environment in order to get all the benefits of edge computing.

This is the very first release of this new blueprint as part of the Akraino PCEI family. Current focus for this release is to enable open source Karmada based cloud federation & kubeEdge/EdgeMesh based East-West networking functionality.

Multi-cluster Management

Environmental Information (CentOS8.0 4U8G)

Username & Password: root/Akraino2021

CPU Name	Role	IP	Workload
kubeedge-karamda-001	Karmada Control Plane	159.138.22.176	Karmada controllers, karmada api
kubeedge-karamda-002	Cluster02	182.160.12.59	K8s, docker
kubeedge-karamda-003	Cluster01	159.138.43.243	K8s, docker

Deployment Manual

Karmada control plane deployment

Disable boot firewall

# systemctl disable firewalld

Install Docker

# yum install wget container-selinux -y

# wget https://download.docker.com/linux/centos/7/x86_64/stable/Packages/containerd.io-1.2.6-3.3.el7.x86_64.rpm

# yum erase runc -y

# rpm -ivh containerd.io-1.2.6-3.3.el7.x86_64.rpm

Note: The above steps do not need to be operated in centos7

# update-alternatives --set iptables /usr/sbin/iptables-legacy

# yum install -y yum-utils device-mapper-persistent-data lvm2 && yum-config-manager --add-repo https://download.docker.com/linux/centos/docker-ce.repo && yum makecache

# yum -y install docker-ce

# systemctl enable docker.service && systemctl start docker

Install Kind

# curl –Lo ./kind https://kind.sigs.k8s.io/d1/v0.10.0/kind-linux-amd64

# chmod +x ./kind

# mv ./kind /usr/local/bin/kind

# kind version

Install Go and configure the Golang environment

# wget https://golang.google.cn/dl/go1.17.0.linux-amd64.tar.gz

# tar –zxvf go1.17.0.linux-amd64.tar.gz –C /usr/local

# vi /etc/profile

Add at the end of file:

# golang env

export GOROOT=/usr/local/go

export GOPATH=/data/gopath

export PATH=$PATH:$GOROOT/bin:$GOPATH/bin

# source /etc/profile

# mkdir -p /data/gopath && cd /data/gopath

# mkidr –p src pkg bin

Configure yum source

# cat <<EOF > /etc/yum.repos.d/kubernetes.repo

[kubernetes]

name=Kubernetes

baseurl=https://mirrors.aliyun.com/kubernetes/yum/repos/kubernetes-el7-x86_64

enabled=1

gpgcheck=1

repo_gpgcheck=1

gpgkey=https://mirrors.aliyun.com/kubernetes/yum/doc/yum-key.gpg https://mirrors.aliyun.com/kubernetes/yum/doc/rpm-package-key.gpg

EOF

Install KubeCtl

# yum makecache

# yum instal –y kubectl

Install Karmada control plane components

# git clone https://github.com/karmada-io/karmada

# cd karmada

# hack/local-up-karmada.sh

Edge cluster deployment

Disable boot firewall

# systemctl disable firewalld

Install Docker

# yum install wget container-selinux -y

# wget https://download.docker.com/linux/centos/7/x86_64/stable/Packages/containerd.io-1.2.6-3.3.el7.x86_64.rpm

# yum erase runc -y

# rpm -ivh containerd.io-1.2.6-3.3.el7.x86_64.rpm

Note: The above steps do not need to be operated in centos7

# update-alternatives --set iptables /usr/sbin/iptables-legacy

# yum install -y yum-utils device-mapper-persistent-data lvm2 && yum-config-manager --add-repo https://download.docker.com/linux/centos/docker-ce.repo && yum makecache

# yum -y install docker-ce

# systemctl enable docker.service && systemctl start docker

Configure yum source

[root@kubeEdge-cloud ~]# cat <<EOF > /etc/yum.repos.d/kubernetes.repo

[kubernetes]

name=Kubernetes

baseurl=https://mirrors.aliyun.com/kubernetes/yum/repos/kubernetes-el7-x86_64

enabled=1

gpgcheck=1

repo_gpgcheck=1

gpgkey=https://mirrors.aliyun.com/kubernetes/yum/doc/yum-key.gpg https://mirrors.aliyun.com/kubernetes/yum/doc/rpm-package-key.gpg

EOF

Install KubeAdm, KubeCtl

# yum makecache

# yum install kubelet-1.21.0-0.x86_64 kubeadm-1.21.0-0.x86_64 kubectl-1.21.0-0.x86_64

Configure the kernel parameters

[root@kubeEdge-cloud ~]# cat <<EOF > /etc/sysctl.d/k8s.conf

net.bridge.bridge-nf-call-ip6tables = 1

net.bridge.bridge-nf-call-iptables = 1

vm.swappiness=0

EOF

[root@kubeEdge-cloud ~]# sysctl --system

[root@kubeEdge-cloud ~]# modprobe br_netfilter

[root@kubeEdge-cloud ~]# sysctl -p /etc/sysctl.d/k8s.conf

Load ipvs related kernel modules

If you reboot, you need to reload (it can be written in /etc/rc.local to automatically load at boot)

[root@ke-cloud ~]# modprobe ip_vs

[root@ke-cloud ~]# modprobe ip_vs_rr

[root@ke-cloud ~]# modprobe ip_vs_wrr

[root@ke-cloud ~]# modprobe ip_vs_sh

[root@ke-cloud ~]# modprobe nf_conntrack_ipv4

Check whether the loading is successful

[root@ke-cloud ~]# lsmod | grep ip_vs

Pull Mirror

[root@kubeEdge-cloud ~]# kubeadm config images list

[root@kubeEdge-cloud ~]# kubeadm config images pull

Install Kubelet

1）Get docker cgroups

# DOCKER_CGROUPS=$(docker info | grep 'Cgroup Driver' | cut -d' ' -f4)

# echo $DOCKER_CGROUPS

cgroupfs

2）Configure cgroups for kubelet

# cat >/etc/sysconfig/kubelet<<EOF

KUBELET_EXTRA_ARGS="--cgroup-driver=$DOCKER_CGROUPS --pod-infra-container-image=k8s.gcr.io/pause:3.5"

EOF

3）Start kubelet

# systemctl daemon-reload

# systemctl enable kubelet && systemctl start kubelet

Initialize the cluster

# kubeadm init --kubernetes-version=v1.17.9 \

--pod-network-cidr=10.244.0.0/16 \

--apiserver-advertise-address=192.168.0.238 \

--ignore-preflight-errors=Swap

Install network plugin

1）Download the yaml file of flannel plug-in.

# cd ~ && mkdir flannel && cd flannel

# curl -O https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml

2）Startup

# kubectl apply -f ~/flannel/kube-flannel.yml

Log in to the karmada-host node and join the multi-cluster (the karmada.config below refers to the kubeconfig of the existing k8s cluster)

# hack/create-cluster.sh member1 $HOME/.kube/karmada.config
# go get github.com/karmada-io/karmada/cmd/karmadactl

# karmadactl join cluster01--cluster-kubeconfig=$HOME/.kube/karmada.config

Nginx application deployment

Create nginx deployment

Create the nginx propagation policy

East-West Edge-to-Edge Networking

Environmental Information (CentOS8.0 4U8G)

Username & Password: root/Akraino2021

CPU Name	Role	IP	Workload
Kubeedge-akraino-0001	Cloud	159.138.149.190	K8S, docker, cloudcore
Kubeedge-akraino-0002	Edge Node	119.8.35.111	docker, edgecore, edgemesh
Kubeedge-akraino-0003	Edge Node	182.160.10.130	docker, edgecore, edgemesh

Deployment Manual

Deploy cloud nodes (kubeEdge-cloud)

Disable boot firewall

# systemctl disable firewalld

Install Docker

# yum install wget container-selinux -y

# wget https://download.docker.com/linux/centos/7/x86_64/stable/Packages/containerd.io-1.2.6-3.3.el7.x86_64.rpm

# yum erase runc -y

# rpm -ivh containerd.io-1.2.6-3.3.el7.x86_64.rpm

Note: The above steps do not need to be operated in centos7

# update-alternatives --set iptables /usr/sbin/iptables-legacy

# yum install -y yum-utils device-mapper-persistent-data lvm2 && yum-config-manager --add-repo https://download.docker.com/linux/centos/docker-ce.repo && yum makecache

# yum -y install docker-ce

# systemctl enable docker.service && systemctl start docker

Configure yum source

[root@kubeEdge-cloud ~]# cat <<EOF > /etc/yum.repos.d/kubernetes.repo

[kubernetes]

name=Kubernetes

baseurl=https://mirrors.aliyun.com/kubernetes/yum/repos/kubernetes-el7-x86_64

enabled=1

gpgcheck=1

repo_gpgcheck=1

gpgkey=https://mirrors.aliyun.com/kubernetes/yum/doc/yum-key.gpg https://mirrors.aliyun.com/kubernetes/yum/doc/rpm-package-key.gpg

EOF

Install Kubeadm, kubectl

# yum makecache

# yum install kubelet-1.21.0-0.x86_64 kubeadm-1.21.0-0.x86_64 kubectl-1.21.0-0.x86_64

Note: The current KubeEdge version does not match the 1.22 version of K8s, and the latest version cannot be installed.

Configure the kernel parameters

[root@kubeEdge-cloud ~]# cat <<EOF > /etc/sysctl.d/k8s.conf

net.bridge.bridge-nf-call-ip6tables = 1

net.bridge.bridge-nf-call-iptables = 1

vm.swappiness=0

EOF

[root@kubeEdge-cloud ~]# sysctl --system

[root@kubeEdge-cloud ~]# modprobe br_netfilter

[root@kubeEdge-cloud ~]# sysctl -p /etc/sysctl.d/k8s.conf

Load ipvs related kernel modules

If you reboot, you need to reload (it can be written in /etc/rc.local to automatically load at boot)

[root@ke-cloud ~]# modprobe ip_vs

[root@ke-cloud ~]# modprobe ip_vs_rr

[root@ke-cloud ~]# modprobe ip_vs_wrr

[root@ke-cloud ~]# modprobe ip_vs_sh

[root@ke-cloud ~]# modprobe nf_conntrack_ipv4

Check whether loading is successful

[root@ke-cloud ~]# lsmod | grep ip_vs

Pull Mirror

[root@kubeEdge-cloud ~]# kubeadm config images list

[root@kubeEdge-cloud ~]# kubeadm config images pull

Initialize the cluster

[root@ke-cloud ~]# kubeadm init --kubernetes-version=v1.17.9 \

--pod-network-cidr=10.244.0.0/16 \

--apiserver-advertise-address=192.168.0.238 \

--ignore-preflight-errors=Swap

Deploy Cloudcore

Prerequisites: install golang

[root@kudeEdge-cloud ~]# git clone https://github.com/kubeedge/kubeedge $GOPATH/src/github.com/kubeedge/kubeedge

[root@kudeEdge-cloud ~]# cd $GOPATH/src/github.com/kubeedge/kubeedge

[root@kudeEdge-cloud ~]# make all WHAT=keadm

[root@kudeEdge-cloud ~]# keadm init --advertise-address="192.168.0.238"

Deploy edge nodes (edgemesh version is release1.7)

Install docker same as before
Obtain the token on the cloud node

[root@kudeEdge-cloud ~]# keadm gettoken

Install edgecore and mqtt

[root@kudeEdge-cloud ~]# keadm join --cloudcore-ipport=192.168.1.66:10000 --token=“上一步骤获取的token”

--token="token obtained in the previous step"

Modify the edgecore configuration

[root@kudeEdge-cloud ~]# vim /etc/kubeedge/config/edgecore.yaml

modules:

..

edgeMesh:

enable: false

metaManager:

metaServer:

enable: true

..

Restart edgecore

[root@kudeEdge-cloud ~]# systemctl restart edgecore

Modify cloudcore configuration and restart cloudcore

[root@kudeEdge-cloud ~]# vim /etc/kubeedge/config/cloudcore.yaml

modules:

..

dynamicController:

enable: true

..

Pull EdgeMesh code and build EdgeMesh image

[root@kudeEdge-cloud ~]# docker build -t edgemesh:0.1 -f build/Dockerfile .

Deploy EdgeMesh

Modify the following configuration file, modify service-cluster-ip-range.

[root@kudeEdge-cloud ~]# kubectl apply -f build/kubernetes/edgemesh/03-configmap.yaml

[root@kudeEdge-cloud ~]# kubectl apply -f build/kubernetes/edgemesh/04-daemonset.yaml

Deploy ROS application

Create ros-deployment-master.yaml and deploy

Create ros-deployment-slave.yaml and deploy

Create ros-master-service.yaml and deploy

ros application master node operation
- Open the master node page, http://182.160.10.130:80
- Refer to the operation of https://hub.docker.com/r/njh1195/ros-vnc:
  - Open the terminal page and execute "roscore" to start roscore
  - Open the second terminal page and execute "roslaunch turtlebot3_gazebo multi_turtlebot3.launch”
  - multi_turtlebot3.launch" to start three simulation robots
  - Open the third terminal page and execute "ROS_NAMESPACE=tb3_0 roslaunch
  - turtlebot3_slam turtlebot3_gmapping.launch set_base_frame:=tb3_0/base_footprint set_odom_frame:=tb3_0/odom set_map_frame:=tb3_0/map”, set_map_frame:=tb3_0/map" to start the first robot scan on the master node.
  - Open the fourth terminal page and execute "roslaunch turtlebot3_gazebo
  - multi_map_merge.launch" to open the merge program.
  - Generate a point source map and execute "rosrun rviz rviz -d `rospack find
  - turtlebot3_gazebo`/rviz/multi_turtlebot3_slam.rviz”

ros application master node operation
- Open the slave node page, http://159.138.49.1:80
- Refer to the operation of https://hub.docker.com/r/njh1195/ros-vnc:
  - Open the terminal page and configure ros-master's access service. The file is in /root/.bashrc.

Add the following configuration at the end of the file to configure the master access address and slave address:

- - Open the second terminal page and execute "ROS_NAMESPACE=tb3_1 roslaunch
  - turtlebot3_slam turtlebot3_gmapping.launch

set_base_frame:=tb3_1/base_footprint set_odom_frame:=tb3_1/odom

set_map_frame:=tb3_1/map", open the graphic scan of another room.

- - Check whether the point source graph is Merged in the master node.

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