Distributed consensus

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Distributed consensus ( distributed-consensus )

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134 7.4. HYBRID EPOCH ALLOCATION p1 a1 a2 a3 p2 e:0 e:0 propose(0,A) accept(0,A) QA : {a1} accept(0,A) QA:{a1,a2} epro:0 eacc:0 vacc :A epro:0 eacc :0 vacc :A epro:0 eacc:0 vacc :A propose(0,A) accept(0,A) QA : {a3} accept(0,A) QA:{a2,a3} Figure 7.5: Example run of epochs by recovery with two concurrent proposers proposing the same proposal (0, A). 7.4 Hybrid epoch allocation Pre-allocation Y Y Y, to proposers Voting Y Y N Epoch allocation approach Epochs unique to values Epochs unique to proposers Epoch assignment required Allocator Value-based Recovery Y Y & N12 Y N N N N Y, to values N Table 7.2: Approaches to epoch allocation Thus far, we have described five mechanisms for handling the allocation of epochs: static allocation, phase one voting, dynamic allocation by an allocator (§7.1), valued-based (§7.2) or recovery-based allocation (§7.3). These mechanisms are summarised in Table 7.213. However, algorithms for distributed consensus need not utilise only one of these mechanisms but may use them in combination by allocating epochs to particular methods. The ability for proposers to use any epoch is most powerful with the epoch emin, since proposers using emin can skip phase one. Therefore a logical hybrid algorithm would consist of combining either an allocator, value-based or recovery-based approach for emin (fast 12Epochs are only unique to proposers when an allocator is used if the proposal is not reallocated. 13Proposal copying (§3.10) can also be combined with each of these mechanisms.

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