The volume of data has experienced explosive growth which poses high requirements for computing power. The traditional centralized computing power scheduling model has many drawbacks, including low resource utilization, single-point failures, and lack of trust. Cross-domain collaborative computing power scheduling is applied between the supply and demand of computing power. This paper aims to combine the blockchain technology with federated learning for cross-domain collaborative computing power scheduling. Blockchain technology builds a trusted trading environment while federated learning helps the optimal resource allocation of the entire cross-domain computing power scheduling system. The experiment shows the design has high accuracy in task assignment. It also provides fast verification times and security protection.

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A Trusted Computing Power Network Scheduling Algorithm Based on Federated Learning

  • Sijia Zhao,
  • Zhanjun Si

摘要

The volume of data has experienced explosive growth which poses high requirements for computing power. The traditional centralized computing power scheduling model has many drawbacks, including low resource utilization, single-point failures, and lack of trust. Cross-domain collaborative computing power scheduling is applied between the supply and demand of computing power. This paper aims to combine the blockchain technology with federated learning for cross-domain collaborative computing power scheduling. Blockchain technology builds a trusted trading environment while federated learning helps the optimal resource allocation of the entire cross-domain computing power scheduling system. The experiment shows the design has high accuracy in task assignment. It also provides fast verification times and security protection.