State-Machine Replication For Planet-Scale Systems (Eurosys 2020)

in the CURP paper, that nosotros of late read.) Instead the requirement is that the commands that conflict are to endure ordered the same agency alongside honor to each other satisfying the dependencies at each node.

Ok, what is novel inwards Atlas? Atlas improves on EPaxos inwards several aspects.

1. Atlas makes the maximum number of sites that tin forcefulness out neglect (f) configurable  independently of the overall number of sites (n). In EPaxos f=$\lfloor{n/2}\rfloor$. In Atlas f tin forcefulness out endure less, opening the chance to merchandise higher f, fault-tolerance, alongside higher scalability, every bit nosotros verbalize over next.
2. Atlas uses a pocket-size fast quorum, FQ=$\lfloor{n/2}\rfloor+f$, compared to EPaxos fast quorum of 3n/4. Of class EPaxos tin forcefulness out tolerate f=$\lfloor{n/2}\rfloor$ alongside its larger fast quorum, exactly Atlas considers pocket-size f, e.g.  f=1 or f=2, argument that solely a distich datacenters may endure downward at most, in addition to reaps the do goodness of this past times using smaller FQ. 
3. Atlas shows how nosotros tin forcefulness out apply the flexible quorums result to fast Paxos identify unit of measurement of protocols. It shows that thank y'all to flexible quorums, the tiresome quorum tin forcefulness out endure made besides real small, SQ=$f+1$, provided that nosotros brand the recovery quorums RQ=$n-f$. This is a reasonable tradeoff, because recovery quorum is exercised rarely, solely when faults happen.
4. Atlas processes a high pct of accesses inwards a unmarried circular trip, fifty-fifty when these conflict. But this requires advance explanation in addition to optimization, in addition to then nosotros volition come upwards dorsum to this below. 
5. Atlas provides a simpler recovery round. Recovery is nonetheless hard, hear you, exactly it is an improvement over EPaxos recovery, which should caution y'all close the trickiness of recovery inwards opportunistic/any leader protocols. 

Side remark. Here is the paper's declaration close using pocket-size f: 

Running a typical protocol over thirteen information centers would tolerate half-dozen of them failing. However, natural disasters leading to the loss of a information centre are rare, in addition to planned downtime tin forcefulness out endure handled past times reconfiguring the unavailable site out of the organization [15, 31]. Furthermore, temporary information centre outages (e.g., due to connectivity issues) typically accept a brusk duration [20], and, every bit nosotros confirm experimentally inwards §5, rarely hap concurrently. For this reason, manufacture practitioners assume that the number of concurrent site failures inwards a geo-distributed organization is low, e.g. 1 or 2.

Here is the video of presentation of this newspaper inwards our dynamic sharding inwards WPaxos, industrial plant improve to solve the problem. This is due to the next reasons.

1. The scalability of EPaxos similar approaches is express due to firstly due to conflicts (throughput plummets chop-chop when conflict charge per unit of measurement increases), in addition to secondly because every consensus event is communicated to every node at to the lowest degree for commit in addition to execution. 
2. Even the fast path of $\lfloor{n/2}\rfloor+f$ spans one-half the globe inwards a world-wide deployment. Due to this, the do goodness y'all larn from proposing the ascendency from any-leader some y'all is non much. Sharded deployments, afterwards brunting the toll of initial communication to the corresponding leader tin forcefulness out perform phase-2 from nearby datacenters (not using the one-half the globe). Moreover sharded many-leader Paxos protocols tin forcefulness out solve the initial toll to going to the leader past times adopting to the traffic past times repositioning the leader, which is done much chop-chop using a dynamic many-leader sharding solution similar WPaxos. The evaluation compares alongside FPaxos, exactly it is a single-leader solution, where the unmarried leader becomes a bottleneck both inwards damage of distance in addition to throughput. With many-leader sharding solutions both problems are addressed in addition to fifty-fifty alongside a totally random access designing in addition to no locality-adaptation, they could outperform opportunistic/any-leader approaches, thank y'all to their nearby consensus quorums. And they are much easier to implement.  

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