开源软件名称：

开源软件地址：

开源编程语言：

开源软件介绍：

Update: see last paragraph for some important status update.

py-swirld

Just fooling around the Swirlds byzantine consensus algorithm by Leemon Baird (whitepaper available) in python. Swirlds is an algorithm constructing a strongly consistent and partition tolerant, peer-to-peer append-only log.

It seems to work as intended to me but don't take it for granted!

Dependencies

• python3 (obviously!)
• pysodium for the crypto
• bokeh for the analysis and interactive visualization

Usage / High-level explainations

I don't think this is any useful to you if you don't plan to understand how the algorithm works so you should read the whitepaper first. After that, the implementation is quite straightforward: the code is divided in the same functions as presented in the paper:

• The main loop (which is a coroutine to enable step by step evaluation and avoid threads).
• sync(<remote-node-id>, <payload-to-embed>) which queries the remote node and updates local data.
• divide_rounds which sets round number and witnessness for the new transactions.
• decide_fame which does the voting stuff.
• find_order which update the final transactions list according to new election results.

Everything is packed into a Node class which is initialized with it's signing keypair and with a dictionary mapping a node ID (it's public key) to some mean to query data from him (the ask_sync method). Note that for simplicity, a node is included in it's own mapping.

You can fiddle directly with that code or try out my nice interactive visualizations to see how the network evolves in real time with:

bokeh serve --show viz.py --args <number of nodes>

This will start locally the specified number of nodes and by pressing the play button it will start choosing one at random every few miliseconds and do a mainloop step. The color indicates the round number (it's just a random color, the only thing is that transactions with the same round have the same color).

Algorithm details

Actually, I didn't implement the algorithm completely straitforward with full graph traversals everywhere and big loops over all nodes. The main specificity I introduced is a mapping I named can_see. It is updated along the round number in divide_rounds and stores for each transaction a dictionnary that maps to each node the id of the latest (highest) transaction from that node this transaction can see (if there is one). It is easily updated by a recurrence relation and enables to quickly seable and strongly seable transactions.

With nn and nt respectively the number of nodes and the number of transactions, this datastructure adds up O(nn*nt) space and enables to compute the set of witnesses a transaction can strongly see in O(nn^2).

IPFS

A variant lives in the ipfs branch. This variant uses IPFS as a backend to store the hashgraph. Indeed a swirlds hashgraph is just the same as an IPFS merkle DAG. This enables global deduplication of the hashgraph (bandwith and computation efficient syncing between members). The syncing process is just about getting the head of the remote member. As the head of a member is stored in an IPNS record, this code is currently very slow, but a lot of work is currently going on on the IPFS side to improve IPNS (cf IPRS).

Work In Progress

• The interactive visualization is still rather crude.
• There is no strong fork detection when syncing.
• There is no real networking (the communication is really just a method call). This should not be complicated to implement, but I will have to bring in threads, locks and stuff like that. I am actually thinking about embedding the hashgraph in IPFS objects as it fits perfectly. This would enable to just drop any crypto and network operation as IPFS already takes care of it well.

Some updates

AKA why swirlds isn't that much interesting

Following this issue, I want to stress some things (also explaining why I stopped to be interested in swirlds).

There are two flaws in this protocol which are somewhat related. The first one is that the protocol cannot scale very well (ie have sublinear complexity in the number of nodes for message handling) and the second one is that it doesn't handle open-membership.

These issues may not be relevant if you want a distributed db in a medium-sized closed organisation having some external centralized auth system. But this is important if you want to make an internet-sized distributed db which has absolutely no owner and no centralized registration service.

I'm gonna start with the second issue. To have a distributed db with open-membership you must have protocol handling open-membership, you can't make some construction with a second distributed db for the current stake repartition with swirlds because there should then be a fixed set of "stake validators". Some solutions proposed on swirlds.com are:

• an invite system where one gives a share of it's stake to people he's inviting, not trivial to do and the one starting the network has full power until he gives some away
• rely on some external mean (associating with a bitcoin wallet etc), that's aweful because this should be something replacing it
• use PoW for the stake, hurray, we just got back to a blockchain

They are all wacky because there is no mean to transform a closed membership protocol into an open one.

The first issue gives a hint why it is probably not interesting to use any hack or external mean to turn swirlds into an open-membership protocol: just try to think of an efficient algorithm for the voting part (divide_rounds, decide_fame, ...), you must in one way or another iterate through all members (and probably also through some part of their respective transaction history) so each transaction takes a time at least linear in the number of nodes. Sure you can sync only with a few people, maybe O(log n) or even O(1) using a carefully choosen De Bruijn graph but you will still need to maintain the full hashgraph and iterate through witness transactions (and there is one for each node), there's no escaping from the O(n) time and space lower bound and linear complexity is bad(tm). Any decent distributed database that wants internet scale should be having time and space bounds at most Omega(log n) for incoming events processing.

So bottom line: don't star this repo, this algorithm is bad ;).

Conclusion

Why do you actually need strong consensus? (tldr: you don't)

1. Probably you want to create a new cryptocurrency, but crypto-currencies are mostly shitty in the sense that the 2 groups interested in them are (1) speculators which are people how's job is to scam other people (yep, their job is mostly to buy things lower than what people think it's worth and resell it higher, having no interaction at all with the underlying physical object of their transactions), they only care about how much money will be in their pocket at the end. I don't think it has any sense to design an economic system where you can get money without creating anything, physical or intellectual) (2) right-libertarian who love capitalism: nope guys, the market isn't automagically stabilizing, it strives to make rich people richer and poor people poorer, which is quite the oposite of convergence. So at the end, i have nothing special against crypto-currencies per se, it's just that it has attracted quite a lot of attention from uninteresting people that have uninteresting and very conservative ideas.

2. Maybe you're writing this awesome service that is fully distributed (p2p) and you need some structure to handle shared mutable data. You should think twice about what real guarantees you need, because high chance are that you can overcome weak consensus. There are loads of distributed datastructures that take advantage of providing lower guarantees but still be on point for a particular use.

   • DHT will be great for a cache and if you're adventurous you can go read some papers about distributed skip-lists and skip-graph.
   • A lot of abstract datastructures (mostly sets and counters) have CRDT implementations which you can use. You can then plug an anti-entropy (or epidemic) protocol to synchronize the states in an eventually consistent fashion.
   • Networking is hard, if you need something like decentralized pub/sub, you should take a look at the Matrix protocol. It's highly unstable and I have some criticism on their protocol, but they're trying to solve this problem.

3. Oh so you do need strong consensus with open membership because you want to create a replacement protocol for naming things on the internet? Somewhat a mix between DNS and SSL-PKI? and distributed keybase? Sure, that's a good goal, but at first, you shouldn't rely on unique global identifiers that are not self-authentifying (so you shouldn't need strong consistency for that part). That said, strong consistency might be useful in this case. You should probably take a look at SCP (stellar consensus protocol), this one should be good.

Post-Scriptum

Please don't ever use or mention blockchain protocols. If you encounter someone who does, please repeat him the following (or just go away from him, chances are he falls into one of the two categories of first conclusion bullet and he will be much harder to deal with).

Blockchains are ledgers, not generic databases. Sure you can build a generic database on top of a ledger, but i'm not sure we would like a world where every database would be a dictionary mapping unique IDs to integers.

PoW blockchain's security claims rely on:

• The protocol's own inefficiency. The only slow part is block creation and making it fast would render the protocol trivially insecure.
• The fact that users rational. Maybe we are maybe not, the problem is that is just a fancy way of saying they assume users want to maximise the number of currency-tokens they have which is not a valid assumption: adversaries will surely not behave in a manner that maximises their tokens, they only want to crash your system. Instead you should target a byzantine-fault tolerant protocol.