Abstract: Addressing security threats from unknown attacks exploiting software and system vulnerabilities in power grid devices often overlooks potential issues within operating systems and communication protocols at the programming languarg level. This paper proposes a finegrained scheduling algorithm that quantifies the similarity of execution components and incorporates parameters such as attack timing and frequency to assess historical trust deficit. By combining similarity and historical trust deficit, a quantitative algorithm for redundant execution body heterogeneity is introduced. Simulation experiments demonstrate that this algorithm significantly outperforms other methods in distinguishing execution body similarity, effectively reducing the risk of exploiting similar vulnerabilities or defects, and minimizing redundant wastage from similar execution bodies. The failure rate remains consistently below 0.55, indicating superior practical performance compared to commonly used algorithms.