Imagine if your smart devices

could contribute to

cancer research

Sharing idle computing resources and data on the blockchain

My Story

Being a computer scientist, experiments and data are the two most important parts of my life. Often, I need to spend months to collect data and run thousands of experiments with those data on a couple of computers.

 

Once, I sent a message to a WhatsApp group offering my exclusive recipe for dumplings in exchange for using their computers.

That night 67 computers were offered to me and I got the experiment results I wanted in just one night. Not one month, one night.

ASTONE (CHENYU) Shi

  • Ph.D of computer science at the University of Groningen in the Netherlands

  • Computer scientist and AI specialist in Distributed System, Blockchain, Machine Learning, Pattern Recognition and Big Data

Problems

  • Most of people do not use their TV Box and Wifi Box during the day time. 85% of people do not power off their computers when they are off duty and 98% of people only use 5% - 20%  computing power of their smart devices.

 

  • Researchers and developers spend a lot of cost to buy computing resources and data. Young researchers and students do not even have enough budget to buy.
Current ​Situation ​Cost
Buy or build a computer cluster  ​$ 5,000,000
Purchase super computers ​$ 50,000 / Each
​Subscribe solutions provided by large enterprises (Google, Amazon, IBM etc.) ​$ 0.32 - 0.54 / Hour / Node
Use facilities from universities or companies Limited resources
Cooperate with other companies on big projects Chance barely existing

Solution

  • A secure, transparent and decentralised platform​ where users can share, rent, lease and auction idle computing resources and their data to:

SAVE MONEY

when using computing resources

MAKE MONEY

when sharing idle computing power or data

INVEST FUTURE

by supporting R&D  projects

Example

  • R&Ders need to process big data for a cancer research.

  • Not paying expensive cloud services or supercomputers.

  • Simply log onto TuDoLink to get cheap or free computing power.

 

  • Providers are helping to advance cancer treatment research.

  • They may get a free cancer check or health tips from researchers.

Business Model

  • Provide technical services and charge service fee.

      - Online Machine Learning and Big Data Services.

      - Cloud Services ( Cloud Computing )

      - Speed up with Content Delivery Network

      - Data Transfer

      - Program or Coding Education

      - Applications on Demand

 

  • Other business models could be developed in the future.

 

Competitors and Comparison

TuDoLink Gridcoin Golem Sonm
Computing power shared
Open to individual  suppliers
Open to individual R&Ders X
Tasks distribution
X X X

 
X X X

 
X X X
​√ X X ​X
Codes inspection based on machine learning technique ​√ X X ​X
Technical support and consulting ​√ X X ​X
 Cloud services ​√ X X ​X
Data Trading ​√ X X ​X

Transparency: Codes of tasks traceable on blockchain

Social: ​Free communication between R&Ders and suppliers

Secure: ​Program Guarantee

Easy: In-browser implementation

Your computing power can contribute to cancer research!

 

 

Would you like to invest this project?

SWOT Analysis

Strengths

- Commercial innovation in task distribution mode
- Solid connection and support from academy
- Superior technical architecture
- Solid partnership with R&Ders in the field of computer science
- Solid background in distributed computing
- Ability to enter  the East Asian market
Weaknesses

- Start up
- Limited experiences in financial market
- Lack of funding
- Currently mainly volunteers
 
Opportunities

- The market for idle computing resources is still on the stage of Blue Ocean

- Increasing idle computing resources
- Increasing demand in resource-consuming analysis and model training
- Sharing economy utilising blockchain is the clear trend for the future

- The  European and Chinese markets are opening
 
Threats

- Competitions projects also utilising idle computing resources such as Golem, Gridcoin and Sonm are major competitors
- Malicious users

 

Technical Solution of MVP

  • The MVP will allow users to share their computing resources by merely one click of a button on their browser. See example on the next slide.

Each Block

Codes of tasks

Deal information

Smart Contract

Other

TDL Transaction speed on Blockchain

Bitcoin      :           7 transactions per seconds

Ethereum :         20 transactions pre seconds

Litecoin     :         56 transactions pre seconds

TuDoLink  :  10,000 transactions pre seconds

 

We can complete one transaction in just 2 seconds on the blockchain.

In-browser implementation of Python

Demo

Our Vision

To build a blockchain-based marketplace for people to trade computing resources and data around the world.

As a Chinese saying goes, Water of the TU Brings Spring   (土之水,引春泉 )

It means little help brings much return.

Roadmap

By the end 2018

  • Feasibility validated

  • Market research completed

  • Website development completed
  • R&D and legal teams formed
  • ICO advisory 80% joined
  • Processing business development
  • Aligning with potential investors

Project founder

ASTONE (CHENYU) Shi

  • Ph.D of computer science at the University of Groningen in the Netherlands

  • Computer scientist and AI specialist in Distributed System, Blockchain, Machine Learning, Pattern Recognition and Big Data

  • Founder of CHIWEN B.V.

  • Consultant of IZENE Group

  • Consultant of IBO Technology

Advisory Board

NICOLAI PETKOV

Professor of computer science at the University of Groningen; Head of the system of Intelligent Systems; Member of the University Council; Author of two monographs and coauthor of another book on parallel computing, holds four patents and has authored over 100 scientific papers.

MANUEL ANTONIO LÓPEZ ANTEQUERA

PETER VAN OOIJEN

Associate Professor of Medical Imaging Informatics at UMCG; Discipline Leader Medical Imaging Informatics Board member of the European Society for Medical Imaging Informatics (EuSoMII); Working in Medical Imaging Informatics on advanced visualization and processing of imaging, human machine interaction and 3D planning and printing. Author of over 120 international, peer reviewed, publications and over 20 book chapters.

Advisory Board

ZHI ZHANG

Founder of cloud poly (Beijing) Technology Co., Ltd. The inventor of the core technology of the WPS curve of Chinese characters. He has long been a senior software designer in Microsoft and a technical director of the "Venus program". And lead the development of China Mobile 139 mobile phone mailbox and other star commercial products.

MANUEL ANTONIO LÓPEZ ANTEQUERA

GEORGE AZZOPARDI

Assistant Professor of computer science at the University of Groningen; Senior AI Specialist at Crowdynews; Affiliated with the University of Malta; Award of the Tenure Track project. The founder of the COSFIRE algorithm in the field of pattern recognition and machine vision.

R&D Team

Laura Fernandez Robles

Assistant Professor of computer science at the University of Leon; Ph.D of University of Leon ;Ph.D of University of Groningen; Computer scientist in machine learning, mathematics, artificial intelligence and pattern recognition.

Nicola Strisciuglio

Postdoctoral researcher of computer science at the University of Groningen; Ph.D of University of Salerno. Computer scientist in distributed system, artificial intelligence, pattern recognition, big data and internet of things.

Jiapan Guo

Postdoctoral researcher of computer science at the University Medical Center Groningen; Ph.D of University of Groningen. Computer scientist in machine learning, big data and medical image processing.

R&D Team

Estefania Talavera Martinez

Ph.D of computer science at the University of Groningen; Ph.D of University of Barcelona; Computer scientist in distributed system, lifelogging, deep learning, artificial intelligence, pattern recognition and big data​

Manuel Antonio Lopez Antequera

Ph.D of computer science at the of University of Groningen; Ph.D of University of Málaga; Computer scientist in deep learning, robotics, distributed system, parallel computing, big data and pattern recognition

Ugo Moschini

Ph.D of computer science at the University of Groningen; Computer scientist in distributed system, parallel computing, big data, intelligent system, pattern analysis and remote sensing image processing.

Funding plan

We are looking for investors who:

  • Have a passion for distributed ledger technology in general and believe in our technology in particular
  • Willing to help us grow
  • Willing to invest no less then €1,000,000 for our MVP development, team building and the launch of our ICO

Token plan

                                          Ticker : TDL
                              Total supply  : 2,666,666,666
                           Private Round : 70,000,000 TDL (3%)
               Base Exchange Rates : 1 ETH = 7000 TDL Tokens
 Target Amount Offered (ICO) : 59% TDL

Use of funds

Partnership

One Platform
One Chain

Many Possibilities