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Themis-code

Source Code for hotstuff with Themis

How do I Reproduce Your Key Result in the Paper?

Local Environment

We assume you have the latest Terraform and Ansible installed on your work computer (a work computer is your laptop/home computer).

we had the folder libhotstuff for data of original LibHotstuff. The code is the same as libhotstuff. Another folder Aequitas-hotstuff/libhotstuff is the one integrated Themis.

On your work computer, you have cloned the latest Themis-code repo. Finally, you have already built the repo so binaries hotstuff-keygen and hotstuff-tls-keygen in the two version of libhotstuff are available in their root directory. (See the instructions here )

Now let's move to reproduce the results. Take a look at the guide of libhotstuff first to get an idea, our process is nearlly the same.

We use Terraform to launch a bunch of ec2 instance to get the corresponding replicas.txt and client.txt in scripts/deploy. You can skip this step if you want to generate it manually.

How to launch a bunch of ec2 instances

You can skip this step if you want to generate your own replicas.txt and client.txt manually.

In the folder Terraform, we have two subfolders. One is for one datacenter (e.g. Ohio), the other is for geo-distributed datacenters.

To use Terraform, you need

  • AWS account;
  • AWS Identify and Access Management (IAM) credentials and programmatic access. The IAM credentials that you need for EC2 can be found here;
  • setting up AWS credentials locally with aws configure in the AWS Command Line Interface (CLI). You can find further details here, remember to add permission AdministratorAccess;
  • a VPC configured for EC2. You can find a CloudFormation template to do that here;
  1. Enter the correspondidng folder you want to (one-region-ohio or geo-distributed), open resources.tf, assign access_key and secret_key to your access key ID and secret access key from your IAM credentials.
  2. Change the region to the datacenter's name.
  3. In the block resource, change the count to the number of servers you need, which equals to #replicas + 2, here 2 is for client, and actually we will use one server as 8 clients, you can reduce the client number by removing some lines in clients.txt. Also assign ami to the coresponding VPC configuration for EC2, also private_key and public_key to yours that used to log in to the EC2 instance.
  4. Run terraform init, then ./terra_to_txt.sh.
  5. Paste the generated replicas.txt and clients.txt to Aequitas-hotstuff/libhotstuff/scripts/deploy or libhotstuff/scripts/deploy, depending on which one you want to test.

Before Running the experiments

  • You need running following commands in your terminal

      > sudo chmod 600 path/to/your/id_rsa 
      > eval `ssh-agent -s`
      > ssh-add path/to/your/id_rsa
    
  • Now move to scripts/deploy of coresponding folder.

  • Generate node.ini and hotstuff.gen.*.conf by running ./gen_all.sh.

  • Build libhotstuff on all remote machines by ./run.sh setup.

For Benchmark Results

In the one datacenter setting, when I set the block-size to 400, client number to 16, replica number to 10. I got the following results:

[308385, 302775, 304241, 303517, 304156, 301061, 307310, 303565, 302551, 304807, 115632]
lat = 9.157 ms
lat = 9.143 ms

Where the first line is the throughput, the second line is the mean end-to-end latency, the third line is the mean end-to-end latency after removing outliers.

For Themis Results

  • Change the block-size in hotstuff.gen.conf.
  • Change the #define max_num_all_txn to block-size + 5 in consensus.h and hotstuff.cpp.
  • Then follow the third step in the guide of libhotstuff to reproduce the results.

In the five geo-distributed datacenters' setting, when I set the block-size to 400, client number to 12, replica number to 100. I got the following results:

[3183, 2817, 3196, 2804, 2800, 3200, 2800, 2800, 3200, 2800, 3168, 2832, 2800, 3200, 1600]
lat = 707.553 ms
lat = 681.231 ms

Stop all the launched servers

There is no simple way to stop the server by using Terraform. Therefore we use the UI. In the AWS console, select the servers with the filter "running", then change the instance status to "suspended".

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