A Kubernetes-based Resource Augmentation Framework for Edge Devices

K-RAF assists edge devices to overcome their limited capabilities by provisioning virtualized computation and storage resources in a Kubernetes environment.

K-RAF consists of three modules (Execution Migration Module, Monitoring Module, and Storage Module):

1. Execution Migration Module:

   • Utilizes migration features of K-RAF.
   • Receives IoT device's app execution environment info from the database.
   • Performs migration on the edge server by creating application pods on a Kubernetes cluster.
   • User input for GPU usage guides GPU allocation during migration.
   • Kubernetes' Custom Resource Definition partitions GPU VRAM for GPU-reliant applications.

2. Monitoring Module:

   • Consists of Prometheus, Grafana, and Node-exporter.
   • Node-exporter deployed as a pod on each node of the edge server to collect data.
   • Prometheus stores collected data in a database.
   • Grafana visualizes data from Prometheus via a dashboard.
   • Users can query Prometheus to retrieve specific data.

3. Storage Module:

   • Comprises K-RAF's volume-related functions and rook-ceph.
   • rook-ceph builds a storage pool using HDDs and SSDs in the edge server cluster.
   • SSDs classified as cache and HDDs as backing storage for cache-tiering.
   • Kubernetes creates a PV using storage from the pool.
   • K-RAF uses WebDAV Server pods to mount PV to IoT devices for virtual storage.

Kubernetes-based Resource Augmentation Framework

• [Kubernetes v1.22.9]
• [Docker v20.10.16]
• [rook-ceph v1.9.10]
• [davfs2 v1.6.1]

Edge Server Cluster

• [Intel i7-11700]
• [RAM 64 GB]
• [SSD 500 GB]
• [HDD 1 TB]
• [Ubuntu 19.04]

Edge Device

• [Raspberry Pi 4]
  • Installed davfs2 as WebDAV client