I spent more time with $DUSK’s consensus docs last night, and I think I was looking at decentralization from the wrong angle.
The obvious metric is the number of provisioners. But Dusk’s design makes the distribution of consensus influence more interesting than the raw count. Provisioners need at least 1,000 DUSK to participate, while DuskDS uses deterministic sortition to select provisioners for proposal and committee duties.
That matters because a network could have plenty of eligible provisioners while a smaller group still gets disproportionate consensus exposure.
I also found the risk controls interesting. Dusk uses soft penalties for failed participation and hard penalties for provably invalid behavior, including conflicting votes or proposals.
So I’m less interested in simply asking, “How many provisioners are there?”
I want to know: how evenly is consensus power actually distributed, and how sensitive is that distribution to the eligibility parameters?
That’s the $DUSK metric I’ll be watching next.
#dusk @Dusk $DUSK
The obvious metric is the number of provisioners. But Dusk’s design makes the distribution of consensus influence more interesting than the raw count. Provisioners need at least 1,000 DUSK to participate, while DuskDS uses deterministic sortition to select provisioners for proposal and committee duties.
That matters because a network could have plenty of eligible provisioners while a smaller group still gets disproportionate consensus exposure.
I also found the risk controls interesting. Dusk uses soft penalties for failed participation and hard penalties for provably invalid behavior, including conflicting votes or proposals.
So I’m less interested in simply asking, “How many provisioners are there?”
I want to know: how evenly is consensus power actually distributed, and how sensitive is that distribution to the eligibility parameters?
That’s the $DUSK metric I’ll be watching next.
#dusk @Dusk $DUSK