A New Mining Consensus Algorithm: A Binary Matrix Representation Based

Abdelkader et al. recently proposed a new data representation method designed to enable efficient storage and management of diverse data types on the blockchain, guarantee scalability, cost-effectiveness, and network efficiency. They transformed a binary matrix $M$ of dimensions $m \times n$ bits into two vectors $H$ and $V$ with sizes $m'$ and $n'$, respectively. The compression rate given by $\frac{(m' + n' + \mid Hash(M) \mid) \times 100}{(m \times n)}$ expands exponentially, i.e., $2^{\lambda}$ with $\lambda$ depends on $m$ and $n$), making their technique highly effective for data size reduction. For instance, with a matrix $M$ of size $512 \times 512$ bits, they achieved a reduction rate of~$96.42\%$. The conversion from $M$ to $(H, V)$ is both fast and simple. The presented paper uses these parameters to create a new consensus algorithm based on solving the challenge of recovering the original data using $H$, $V$, and $Hash(M)$ in order to determine the next miner.