Computational Resource Allocation Strategy in a Public Blockchain Supported by Edge Computing

Blockchain, as an emerging distributed data management technology, has attracted extensive attention in recent years. In particular, a public blockchain network can ensure data security by addressing computationally intensive cryptographic tasks. Therefore, for node devices, sufficient computing power is required. However, mobile devices with limited computing power do not meet the conditions required by public blockchain network applications (OZEX, CoininAsia, BitRewards, etc.). To copy with the mentioned problems, nodes can offload computing tasks to edge computing services with low latency. This paper mainly focuses on the trade between edge computing providers (ECP) and nodes. We build a computational resource market model based on auction. Meanwhile, we propose two strategies to deal with two methods of offloading to achieve higher system profit. We also prove that the proposed strategy has individual rationality, authenticity under resource constraints. The simulation results have significance for administrators of a public blockchain network to improve the efficiency of computing resource allocation.

Automated summary

This paper focuses on the trade between edge computing providers (ECP) and nodes in the context of public blockchain networks. A computational resource market model based on auction is established, with two strategies proposed to achieve higher system profit through offloading methods. The proposed strategies are proven to be individually rational and authentic under resource constraints, providing significance for administrators to improve computing resource allocation efficiency in public blockchain networks.