Inspired by Stefan Hajnoczi's excellent blog post, I recently set about constructing an environment for rapid testing of Linux kernel changes, particularly focused on the LIO iSCSI target. This soft fork could also place limits on how big an OP_CHECKSIG-using transaction could be. Such a change will take a while: there are other things which would be nice to change for OP_CHECKSIG2, such as new sighash flags for the Lightning Network, and removing the silly DER encoding of signatures. Since I was creating large blocks (41662 transactions), I added a little code to time how long they take once received (on my laptop, which is only an i3). I did some digging.A  Just invalidating and revalidating the 8MB block only took 1 second, so something about receiving a fresh block makes it worse.
So I did some IBLT research (as posted to bitcoin-dev ) and I lazily used SHA256 to create both the temporary 48-bit txids, and from them to create a 16-bit index offset.A  Each node has to produce these for every bitcoin transaction ID it knows about (ie. Only connect to a single well-connected peer (-maxconnections=1), and hope they propagate your block.
Join a large pool.A  This is what happens in practice, but raises a significant centralization problem.
We need bitcoind to be smarter about ratelimiting in these situations, and stream serially.A  Done correctly (which is hard), it could also help bufferbloat which makes running a full node at home so painful when it propagates blocks. The bad news is that even if fees hit (say) 25c and that prevents all the sub-$1 transactions, we only double our capacity, giving us perhaps another 18 months. I used bitcoin-iterate and gnumeric to render the current bitcoin blocksizes, and here are the results.
So, not time to panic just yet, though we’re clearly growing, and in unpredictable bursts. Countries which had best bandwidth grew about 17% a year, so I think that’s the best model for future growth patterns (China is now where the US was 7 years ago, for example). These graphs are my first look; in blue is the number of txs in the block, and in purple stacked on top is the number of txs which were left in the mempool after we took those away.
Note that the scheme requires some solution to malleability to allow chains of transactions to be built (this is a common theme, so likely to be mitigated in a future soft fork), but Gregory Maxwell points out that it also wants selective malleability, so transactions can be replaced without invalidating the HTLCs which are spending their outputs.A  Thus it proposes new signature flags, which will require active debate, analysis and another soft fork.
There is much more to discover in the paper itself: recommendations for lightning network routing, the node charging model, a risk summary, the specifics of the softfork changes, and more.
A new peer-to-peer protocol needs to be designed for the lightning network, including routing. Wallets need to learn to use this, with UI handling of things like timeouts and fallbacks to the bitcoin network (sorry, your transaction failed, you’ll get your money back in N days). You need to be online every 40 days to check that an old HTLC hasn’t leaked, which will require some alternate solution for occasional users (shut down channel, have some third party, etc).
This is the third part of my series of posts explaining the bitcoin Lightning Networks 0.5 draft paper. In Part I I described how a Poon-Dryja channel uses a single in-blockchain transaction to create off-blockchain transactions which can be safely updated by either party (as long as both agree), with fallback to publishing the latest versions to the blockchain if something goes wrong. In Part II I described how Hashed Timelocked Contracts allow you to safely make one payment conditional upon another, so payments can be routed across untrusted parties using a series of transactions with decrementing timeout values. Half a channel: we will invalidate transaction 1 (in favour of a new transaction 2) to send funds. Note that you supply another separate signature (sig3) for this output, so you can reveal that private key later without giving away any other output. We modify our previous HTLC design so you revealing the sig3 would allow me to steal this output. My next post will be a TL;DR summary, and some more references to the implementation details and possibilities provided by the paper. What if we could bond these transactions together somehow, so that when you spend the output from the MtBox transaction, that automatically allows MtBox to spend the output from my transaction?
If you can produce to MtBox an unknown 20-byte random input data R from a known H, within two days, then MtBox will settle the contract by paying you 1c.
If two days have elapsed, then the above clause is null and void and the clearing process is invalidated. Either party may (and should) pay out according to the terms of this contract in any method of the participants choosing and close out this contract early so long as both participants in this contract agree.


The hashing and timelock properties of the transactions are what allow them to be chained across a network, hence the term Hashed Timelock Contracts. There are several techniques which are used in the paper, so I plan to concentrate on one per post and wrap up at the end. Then a minute later, I send you a signed transaction which spends that same opening transaction output, and has a $9.98 output for me, and a 2c output for you. A Each transaction I send spends the same output; so only one of them can ever be included in the blockchain. Now, if you sign and publish that transaction, I can spend my $9.99 straight away, and you can publish that timelocked transaction tomorrow and get your 1c.
Updating the payment in a lightning-style channel: you sent me your private key for sig2, so I could spend both outputs of Transaction 1 if you were to publish it. So the effect is that the old transaction is revoked: if you were to ever sign and release it, I could steal all the money.A  Neat trick, right? Now we have a generalized transaction channel, which can spend the opening transaction in any way we both agree on, without trust or requiring on-blockchain updates (unless things break down). So first we added debug statements to the open() and close() calls to see when the fd was opened and closed.
We found out that the code responsible for this created a pipe() to communitcate with the child and then forked. Whether a business wants to mirror information between two data high-powered data centers or a school district is looking to consolidate individual school data to a central office, replication technology is the key.
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