Energy Network is the result of a Master's tehesis reasearch on blockchain use in clean energy trading and generation validation. Our model considers energy sellers, buyers, sensors, utility companies and payment companies. We work with PATCHED versions of Hyperledger Fabric, Hyperledger Fabric SDK for Java and Hyperledger Fabric Gateway for Java.
The Energy Network was deployed locally in Ubuntu 20.04 and Windows 10. Also, our scripts allow a fully configurable deploy in AWS and can be easily adapted to other Cloud infrastructures. The following dependencies are required:
GitBash for windows
Docker 20.10.5
docker-compose version 1.28.5, build c4eb3a1f
Python 3.8.2
python3 regex
python3 matplotlib
shyaml 0.6.2 --> to parse YAMLs in Bash scripts
Java OpenJDK 13
Apache Maven 3.6.3
dos2unix
go version go1.16
git version 2.28.0.windows.1
curl 7.72.0 (x86_64-pc-win32)
Patched Hyperledger Fabric tag/v2.3.0
AWS Cli - aws-cli/2.1.32 Python/3.8.8 Windows/10 exe/AMD64 prompt/off
After following the tutorial on Hyperldeger Fabric Pre-requisites, the scripts/install-dependencies.sh script will clone, patch and install MODIFIED:
Hyperledger Fabric gRPC Service Definitions
./scripts/install-dependencies.shTo deal with the energy-applications, scripts/install-java-dependencies.sh will install the patched versions of:
Hyperledger Fabric SDK for Java
./scripts/install-java-dependencies.shFirst edit the file CONFIG-ME-FIRST.yaml to set the organizations:
organizations:
- name: ufsc
admin-quantity: 1
client-quantity: 0
peer-quantity: 1
orderer-quantity: 1
buyer-quantity: 0
seller-quantity: 1
sensor-quantity: 1
msptype: x509
applications-quantity: 1The configurations above will cause the creation of x509 or Idemix credentials for each admin, peer, orderer, buyer, seller, and sensor.
All credentials are available in the hyperledger/ folder.
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Start docker
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Run the network creation script and follow the instructions:
./scripts/automated-creation-factored-energy.sh- CONTINUES
Our network already has scripts to deploy and experiment on the AWS cloud infrastructure.
We support ARM and x86 AMI generations with all dependencies to run our applications, orderers, peers, and experiments. Since AWS ARM instances are more efficient than x86, we opted to perform our experiments with them. The AMI includes our patched Hyperledger Fabric and Fabric SDK Java.
./scripts-aws/create-ami-arm.sh
After the AMI creation, the network can be deployed by executing the AWS creation script. The flags "-o", "-p", and "-a" indicate the instance type of orderers, peers and applications, respectively.
./scripts-aws/automated-aws-creation.sh -o t4g.micro -p t4g.micro -a t4g.micro
The experiments are configured in the **test-configuration.yaml** file. It is possible to set the number of simulated sensors, buyers, and sellers per application instance. The SmartData unit is set in the sensors' configuration (Read more in [Smart Data docs](https://epos.lisha.ufsc.br/IoT+Platform#SmartData)). Each entity (sensor, buyer or seller) publishes the total of **publishquantity** during the experiment. ** publishinterval** milliseconds space the transactions. At the end of the file, the auction period **auctioninterval** in milliseconds can be set, and the interval between two consecutive network auctions.
#quantity per cli-application
sensors:
quantity: 50
unit: 3834792229
#Interval in ms
publishinterval: 5000
publishquantity: 20
msp: UFSC
sellers:
quantity: 50
#Interval in ms
publishinterval: 5000
publishquantity: 5
msp: UFSC
buyers:
quantity: 1
#Interval in ms
publishinterval: 5000
publishquantity: 1
msp: IDEMIXORG
#Interval in ms
auctioninterval: 30000