#6
Tokenizing assets on
Hyperledger Fabric

Tokenizing assets on Hyperledger Fabric

Problems:-

The Chinese cross-border e-commerce trading is booming exponentially but the majority of the shopping malls are still not able to participate in this sector. Furthermore, most of them only actively operates online duty-free, which means it is almost impossible or small businesses to land.

There is also a lack of customer-service and follow up management

Lack of convenience for Chinese tourists in terms of Online reservations/payments.

Necessity of integrated app to minimize inconveniences in using coupons of each duty free shop

There is no integrated single app for Chinese tourist groups which leads to inconvenience in using discount coupons across different duty-free shops

Also, the current Hyperledger based permissioned networks do not have the utility of a token to act as a payment mechanism.

Solution:-

ELAMACHAIN plans to develop cross-border AI platform which breaks down the borders with permissioned blockchain technology and AI chatbot technology, and provide cross-border e- commerce along with cross-border tourism services

Provisions of directions through associated services ( GPS-on foot, by car, by public transportation)

Associated franchises through associated services ( friends or tour guide locators)

Call a taxi through an associated service

General payment methods

Integrated points exchange (combined associates and own company’s points, matching private authentication key)

A technology to commercialise “hyperledger fabric-based transaction system”, is developed for the first time in the world by adding the company’s own coin layers to a permissioned blockchain (hyperledger fabric)

What we have developed:-

This project was comprised of 7 sub-projects -

Developing a Reactjs app for wallet UI - App contains admin and user sections where admin can mint tokens, transfer tokens,check balance and transaction history of users and users can login in to specific organisation, check their balance , transaction history and transfer tokens to other users

Chaincode Analysis - In this part a complete analysis of chaincode was done, which comprised of understanding every line of code using manual reverse engineering to define the architecture of chaincode

Chaincode Manual and Unit Testing - In this part manual and unit testing of chaincode was done. Manual testing was done by making manual transaction from docker-cli interface and comparing the results between expected and actual result. Unit tests were written using chaincode mock shim interface and some third party golang packages

Chaincode performance analysis using hyperledger caliper - In this part chaincode performance is calculated using hyperledger caliper. Chaincode was executed in multiple network configuration as given in caliper sampl

Chaincode performance analysis using hyperledger caliper after integrating accelerator - In this part chaincode performance is improved by integrating accelerator which is done by making the code compatible with accelerator by adding batchUtil chaincode

Testing the chanicodes in various testing environments - in this part production network like Kafka, Orderer and Kubernetes deployment were set up for the chain codes to benchmark the performance

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