Energy-recycling Blockchain with Proof-of-Deep-Learning
This addresses the energy inefficiency issue in blockchain systems, potentially reducing waste and enabling sustainable applications, though it appears incremental as it adapts existing mechanisms.
The paper tackles the energy waste problem in Proof-of-Work blockchains by proposing a novel design that recycles energy into deep learning computations, using Proof-of-Deep-Learning to generate valid blocks only when a proper deep learning model is produced, with benchmark and simulation results showing feasibility for cryptocurrencies like Bitcoin, Bitcoin Cash, and Litecoin.
An enormous amount of energy is wasted in Proofof-Work (PoW) mechanisms adopted by popular blockchain applications (e.g., PoW-based cryptocurrencies), because miners must conduct a large amount of computation. Owing to this, one serious rising concern is that the energy waste not only dilutes the value of the blockchain but also hinders its further application. In this paper, we propose a novel blockchain design that fully recycles the energy required for facilitating and maintaining it, which is re-invested to the computation of deep learning. We realize this by proposing Proof-of-Deep-Learning (PoDL) such that a valid proof for a new block can be generated if and only if a proper deep learning model is produced. We present a proof-of-concept design of PoDL that is compatible with the majority of the cryptocurrencies that are based on hash-based PoW mechanisms. Our benchmark and simulation results show that the proposed design is feasible for various popular cryptocurrencies such as Bitcoin, Bitcoin Cash, and Litecoin.