A decentralized data structure and consensus algorithm
Achieves consensus over the ordering of events/transactions
Marketed as an alternative to the blockchain (PoS)
Async Byzantine Fault Tolerant
Why is this relevant?
Proof Of Work algorithms are wasteful
Existing DLT technologies are slow
Mining and transaction fees
Contributions
An inventive approach for a consensus algorithm
Building block for DLTs
with no double spending attacks
fast confirmations
no PoW necessary
Solution
Nodes randomly connect to other nodes, and send all known events
Receiving node creates new event and sends it to other nodes
When a supermajority of nodes have exchanged messages, we say a round has ended
First events in new round (witnesses) will make decision regarding consensus in previous round based on local info
Computation is performed offline, based on gossiped information
Solution
Solution
Solution
witness
see
strongly see
round
consensus
Strong Points
Elegant solution for achieving consensus
Correctness is easy to prove
Algorithm is easy to specify and understand
Enhancements may improve the protocol
invite nodes and split up stakes
proximity and trust involved in voting
Weak Points
Claims fairness but underdelivers
Performance metrics are not yet available
Not clear how well it scales
Permissioned system
Incentive to fraud the system?
Unclear how byzantine nodes are handled
Solution: Patented, Closed-Source, Java :(
Fairness
A0 = median(3, 1, 4) = 3
D0 = median(4, 2, 0) = 2
Scalability
for N=50 nodes, clients will use at least 120 kbps bandwidth
It's current permissioned model may be why it achieves a high throughput
Conclusion
Exciting technology with a lot of potential
Paper is clear, concise, well written
Room for improvement
The Hashgraph Consensus Agorithm ID2210 Valentin Goșu gosu@kth.se Link to paper: https://www.swirlds.com/downloads/SWIRLDS-TR-2016-01.pdf Link to slides: https://slides.com/valentingosu/hashgraph