A Raspberry Pi Cloud Testbed
Raspberry Pi as a Service (RPiaaS) is a low-cost and energy-efficient cloud testbed built using Raspberry Pi's. The testbed consists of multiple worker nodes, which can be aggregated in small clusters. Every node in the cluster is interconnected, and there is a master node managing the whole testbed. This master node can be a Raspberry Pi or any device running a Linux distribution.
RPiaaS provides an easy-to-use cloud environment for experimentation and validation of resource management experiments, and is initially designed to facilitate the step from simulations towards experimental evaluations on larger cloud testbeds. The developed software however is easy to extend and/or customize, for example to use it for managing a classroom environment or to build a multimedia streaming cluster.
An in-depth overview of the testbed can be found here
We just received permission to publish the code, and are now cleaning up the source code and finishing all documentation. All code and documentation will be released very soon, so please come back to this page in a few weeks.
RPiaaS is developed using a microservice architecture, and consists of 5 different Docker containers:
- rpiaas-cas: container running the client agent service (CAS)
- rpiaas-cms: container running the cluster master service (CMS)
- rpiaas-mongo: container running a mongodb instance, for storing all historical usage data, used by the rpiaas-cms container
- rpiaas-dnsmasq: container running an dnsmasq instance, and is used for providing DNS, DHCP and TFTP towards all worker nodes in the cluster(s)
- rpiaas-nfs: container running a nfs-kernel-server instance, providing the NFS root file system towards all worker nodes
On the master node (= the node managing the cluster(s)), all containers should be deployed. On the worker nodes (= all other nodes), only the rpiaas-cas container should be deployed.
All source code can be found inside the src/ folder. The agent/ and master/ subfolders contain the source code of the client agent service (CAS) and cluster master service (CMS) respectively, and the docker/ subfolder contains the Docker-compose files and the docker files for the different containers.
To facilitate the installation, two bash scripts are provided:
- buildandrun_agent.sh should be executed on the worker nodes, this script launches the rpiaas-cas container
- buildandrun_master.sh should be executed on the master node, this script launches all containers
The configuration files required for the different containers are automatically generated during startup.
Important: Before deploying the services, a config.json needs to be created inside the config/ folder. In this file, the interface of the master node used for communication with the cluster(s), and an overview of the different cluster nodes have to be added. The config.example.json file inside this folder can be used as a template for creating this file. In this example, the master node communicates with the cluster nodes on eth0 and their are two clusters defined, each consisting of 2 worker nodes. The config.json file needs to be created before launching the containers, as during startup the configuration files for the services are automatically generated using this configuration file.
RPiaaS is developed at Ghent University - IDLab. We strongly encourage fellow researchers within the field to try out and customize the code for their own research projects. If you use this code for your own projects, please give credit to the original authors, for example by citing one of the following publications:
Pieter-Jan Maenhaut, Bruno Volckaert, Veerle Ongenae, Filip De Turck. Efficient resource management in the cloud: From simulation to experimental validation using a low‐cost Raspberry Pi testbed. Softw: Pract Exper. 2018;1–29. https://doi.org/10.1002/spe.2669
Pieter-Jan Maenhaut, Hendrik Moens, Bruno Volckaert, Veerle Ongenae, Filip De Turck. Resource Allocation in the Cloud: From Simulation to Experimental Validation . In proceedings of the 2017 IEEE 10th International Conference on Cloud Computing (CLOUD 2017), Honolulu, Hawaii, USA, 2017
Copyright 2017-2018 Ghent University - imec - IDLab
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
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