Connecting AI Learning and Blockchain Mining in 6G Systems
This addresses resource inefficiency in 6G systems by repurposing blockchain mining waste for AI training, though it is incremental as it modifies an existing consensus mechanism.
The paper tackles the problem of wasted computing power in Proof-of-Work blockchains and limited resources for AI training in 6G systems by proposing an Evolved-Proof-of-Work consensus that integrates AI matrix computations into mining, salvaging up to 80% of computing power for parallel AI training.
The sixth generation (6G) systems are generally recognized to be established on ubiquitous Artificial Intelligence (AI) and distributed ledger such as blockchain. However, the AI training demands tremendous computing resource, which is limited in most 6G devices. Meanwhile, miners in Proof-of-Work (PoW) based blockchains devote massive computing power to block mining, and are widely criticized for the waste of computation. To address this dilemma, we propose an Evolved-Proof-of-Work (E-PoW) consensus that can integrate the matrix computations, which are widely existed in AI training, into the process of brute-force searches in the block mining. Consequently, E-PoW can connect AI learning and block mining via the multiply used common computing resource. Experimental results show that E-PoW can salvage by up to 80 percent computing power from pure block mining for parallel AI training in 6G systems.