BFT-MVBA

This repo provides a minimal implementation of the various mvba consensus protocol. The codebase has been designed to be small, efficient, and easy to benchmark and modify. It has not been designed to run in production but uses real cryptography (kyber), networking(native), and storage (nutsdb).

Say something about bft-mvba...

Quick Start

lightDAG is written in Golang, but all benchmarking scripts are written in Python and run with Fabric. To deploy and benchmark a testbed of 4 nodes on your local machine, clone the repo and install the python dependencies:

git clone https://github.com/ac-dcz/BFT-MVBA
cd BFT-MVBA/benchmark
pip install -r requirements.txt

You also need to install tmux (which runs all nodes and clients in the background). Finally, run a local benchmark using fabric:

fab local

This command may take a long time the first time you run it (compiling golang code in release mode may be slow) and you can customize a number of benchmark parameters in fabfile.py. When the benchmark terminates, it displays a summary of the execution similarly to the one below.

• CKPS01-MVBA

Setting up testbed...
Running mvba
0 byzantine nodes
tx_size 250 byte, batch_size 500, rate 5000 tx/s
DDOS attack False
Waiting for the nodes to synchronize...
Running benchmark (30 sec)...
Parsing logs...

-----------------------------------------
 SUMMARY:
-----------------------------------------
 + CONFIG:
 Protocol: mvba 
 DDOS attack: False 
 Committee size: 4 nodes
 Input rate: 5,000 tx/s
 Transaction size: 250 B
 Batch size: 500 tx/Batch
 Faults: 0 nodes
 Execution time: 30 s

 + RESULTS:
 Consensus TPS: 4,877 tx/s
 Consensus latency: 94 ms

 End-to-end TPS: 4,874 tx/s
 End-to-end latency: 586 ms
-----------------------------------------

• VABA

Setting up testbed...
Running vaba
0 byzantine nodes
tx_size 250 byte, batch_size 500, rate 5000 tx/s
DDOS attack False
Waiting for the nodes to synchronize...
Running benchmark (30 sec)...
Parsing logs...

-----------------------------------------
 SUMMARY:
-----------------------------------------
 + CONFIG:
 Protocol: vaba 
 DDOS attack: False 
 Committee size: 4 nodes
 Input rate: 5,000 tx/s
 Transaction size: 250 B
 Batch size: 500 tx/Batch
 Faults: 0 nodes
 Execution time: 30 s

 + RESULTS:
 Consensus TPS: 4,962 tx/s
 Consensus latency: 76 ms

 End-to-end TPS: 4,953 tx/s
 End-to-end latency: 119 ms
----------------------------------------

• SMVBA

Starting local benchmark
Setting up testbed...
Running smvba
0 byzantine nodes
tx_size 250 byte, batch_size 500, rate 5000 tx/s
DDOS attack False
Waiting for the nodes to synchronize...
Running benchmark (30 sec)...
Parsing logs...

-----------------------------------------
 SUMMARY:
-----------------------------------------
 + CONFIG:
 Protocol: smvba 
 DDOS attack: False 
 Committee size: 4 nodes
 Input rate: 5,000 tx/s
 Transaction size: 250 B
 Batch size: 500 tx/Batch
 Faults: 0 nodes
 Execution time: 30 s

 + RESULTS:
 Consensus TPS: 5,140 tx/s
 Consensus latency: 70 ms
 
 End-to-end TPS: 5,130 tx/s
 End-to-end latency: 105 ms
-----------------------------------------

• Mercury

Starting local benchmark
Setting up testbed...
Running Mercury
0 byzantine nodes
tx_size 250 byte, batch_size 500, rate 5000 tx/s
DDOS attack False
Waiting for the nodes to synchronize...
Running benchmark (30 sec)...
Parsing logs...

-----------------------------------------
 SUMMARY:
-----------------------------------------
 + CONFIG:
 Protocol: Mercury 
 DDOS attack: False 
 Committee size: 4 nodes
 Input rate: 5,000 tx/s
 Transaction size: 250 B
 Batch size: 500 tx/Batch
 Faults: 0 nodes
 Execution time: 30 s

 + RESULTS:
 Consensus TPS: 15,780 tx/s
 Consensus latency: 121 ms

 End-to-end TPS: 15,748 tx/s
 End-to-end latency: 156 ms
-----------------------------------------

Aliyun Benchmarks

The following steps will explain that how to run benchmarks on Alibaba cloud across multiple data centers (WAN).

1. Set up your Aliyun credentials

Set up your Aliyun credentials to enable programmatic access to your account from your local machine. These credentials will authorize your machine to create, delete, and edit instances on your Aliyun account programmatically. First of all, find your 'access key id' and 'secret access key'. Then, create a file ~/.aliyun/access.json with the following content:

{
    "AccessKey ID": "your accessKey ID",
    "AccessKey Secret": "your accessKey Secret"
}

2. Add your SSH public key to your Aliyun account

You must now add your SSH public key to your Aliyun account. This operation is manual and needs to be repeated for each Aliyun region that you plan to use. Upon importing your key, Aliyun requires you to choose a 'name' for your key; ensure you set the same name on all Aliyun regions. This SSH key will be used by the python scripts to execute commands and upload/download files to your Aliyun instances. If you don't have an SSH key, you can create one using ssh-keygen:

ssh-keygen -f ~/.ssh/Aliyun

3. Configure the testbed

The file settings.json located in BFT-MVBA/benchmark contains all the configuration parameters of the testbed to deploy. Its content looks as follows:

{
    "key": {
        "name": "BFT-MVBA",
        "path": "/root/.ssh/id_rsa",
        "accesskey": "/root/.aliyun/access.json"
    },
    "ports": {
        "consensus": 8000
    },
    "instances": {
        "type": "ecs.g6e.xlarge",
        "regions": [
            "eu-central-1",
            "ap-northeast-2",
            "ap-southeast-1",
            "us-east-1"
        ]
    }
}

The first block (key) contains information regarding your SSH key and Access Key:

"key": {
    "name": "BFT-MVBA",
    "path": "/root/.ssh/id_rsa",
    "accesskey": "/root/.aliyun/access.json"
}

The second block (ports) specifies the TCP ports to use:

"ports": {
    "consensus": 8000
}

The the last block (instances) specifies theAliyun Instance Typeand the Aliyun regions to use:

"instances": {
    "type": "ecs.g6e.xlarge",
    "regions": [
        "eu-central-1",
        "ap-northeast-2",
        "ap-southeast-1",
        "us-east-1"
    ]
}

4. Create a testbed

The Aliyun instances are orchestrated with Fabric from the file fabfile.py (located in BFT-MVBA/benchmark) you can list all possible commands as follows:

The command fab create creates new Aliyun instances; open fabfile.py and locate the create task:

@task
def create(ctx, nodes=2):
    ...

The parameter nodes determines how many instances to create in each Aliyun region. That is, if you specified 4 Aliyun regions as in the example of step 3, setting nodes=2 will creates a total of 8 machines:

$ fab create

Creating 8 instances |██████████████████████████████| 100.0% 
Waiting for all instances to boot...
Successfully created 8 new instances

You can then install goland on the remote instances with fab install:

$ fab install

Installing rust and cloning the repo...
Initialized testbed of 10 nodes

Next,you should upload the executable file

$ fab uploadexec

5. Run a benchmark

$ fab remote