Advances, Systems and Applications
From: CG-PBFT: an efficient PBFT algorithm based on credit grouping
Node type | First-level evaluation indicators | Symbolic representation | Weight | Second-level evaluation indicators | Symbolic representation | Weight | Third-level evaluation indicators | Symbolic representation | Weight |
---|---|---|---|---|---|---|---|---|---|
Good nodes | Direct credit value | C_diri | λ + μ | Consensus credit | C_coni | λ | Number of successful consensus completions | Num_ci | - |
Total number of consensus participation rounds | TNum_ci | - | |||||||
Voting credit | C_voti | ÎĽ | Number of successful voting completions | Num_vi | - | ||||
Total number of voting participation rounds | TNum_vi | - | |||||||
Indirect credit value | C_idiri | α + β | Active credit | C_acti | α | Number of times the node exists in the master-node group | Num_GMi | \(\gamma\) | |
Number of times the node exists in the consensus-node group | Num_GCi | 1-\(\gamma\) | |||||||
Total number of consensus participation rounds | TNum_ci | - | |||||||
Incentive credit | C_inci | β | Credit ranking | C_ranki | - | ||||
Number of nodes | n | - | |||||||
Historical credit value | C_hisi | \(\eta\) | - | - | - | - | - | - | |
Malicious nodes | Historical credit value | C_hisi | 1/2 | - | - | - | - | - | - |