Incentive and Playful Strategy for a Participative Model of Learning and Experimenting Blockchain
| Autor: | Samuel Ouya, Ahmath Bamba Mbacke, Gervais Mendy, Fatou Ndiaye Mbodji |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Blockchain
Emerging technologies Computer science business.industry Perspective (graphical) 020206 networking & telecommunications 02 engineering and technology Incentive Feature (computer vision) Scalability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software engineering business |
| Zdroj: | 2021 23rd International Conference on Advanced Communication Technology (ICACT). |
| Popis: | In this paper, we are interested in the scalability of simulator models of new technologies, such as the blockchain, which present many technical and consensual constraints and challenges. Thus our proposal focuses on an important feature of meta-models of such simulators, namely the management of the incentive to participate in the proposal to make them evolve continuously. This is done through the election of a king based on his significant contributions to the evolution of the model. The introduction of an evolution can be an optimization of the model's performance or the integration of a recent advance in technology. To better illustrate our proposal, we do an implementation of a blockchain simulator with a perspective of optimizing its upgradability and trying to move towards a single simulation platform based on our model that aggregates the learning and experiment of the blockchain while managing the low and high level details. |
| Databáze: | OpenAIRE |
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