Scalability

The core Bitcoin network can scale to much higher transaction rates than are seen today, assuming that nodes in the network are primarily running on high end servers rather than desktops. Bitcoin was designed to support lightweight clients that only process small parts of the block chain (see simplified payment verification below for more details on this). A configuration in which the vast majority of users sync lightweight clients to more powerful backbone nodes is capable of scaling to millions of users and tens of thousands of transactions per second.

Scalability targets

VISA handles on average around 2,000 transactions per second (tps), so call it a daily peak rate of 4,000 tps. They have burst capacity for over 10,000 tps which they need to handle the busiest points of the holiday period (~8,500 tps). [1]

PayPal, in contrast, handles around 4 million transactions per day for an average of 46 tps or a probably peak rate of 100 tps.

Let's take 4,000 tps as starting goal. Obviously if we want Bitcoin to scale to all economic transactions worldwide, including cash, it'd be a lot higher than that, perhaps more in the region of a few hundred thousand tps. And the need to be able to withstand DoS attacks (which VISA does not have to deal with) implies we would want to scale far beyond the standard peak rates. Still, picking a target let us do some basic calculations even if it's a little arbitrary.

Current bottlenecks

Today the Bitcoin network is restricted to a sustained rate of 7 tps by some artificial limits. These were put in place to stop people from ballooning the size of the block chain before the network and community was ready for it. Once those limits are lifted, the maximum transaction rate will go up significantly.

CPU

The protocol has two parts. Nodes send "inv" messages to other nodes telling them they have a new transaction. If the receiving node doesn't have that transaction it requests it with a getdata.

The big cost is the crypto and block chain lookups involved with verifying the transaction. Verifying a transaction means some hashing and an ECDSA signature verification. RIPEMD-160 runs at 106 megabytes/sec (call it 100 for simplicity) and SHA256 is about the same. So hashing 1 megabyte should take around 10 milliseconds and hashing 1 kilobyte would take 0.01 milliseconds - fast enough that we can ignore it.

Bitcoin is currently able (with a couple of simple optimizations that are prototyped but not merged yet) to perform around 8000 signature verifications per second on an quad core Intel Core i7-2670QM 2.2Ghz processor. However the average number of inputs per transaction is around 2, so we must halve the rate. This means 4000 tps is easily achievable CPU-wise with a single fairly mainstream CPU.

As we can see, this means as long as Bitcoin nodes are allowed to max out at least 4 cores of the machines they run on, we will not run out of CPU capacity unless Bitcoin is handling 100 times as much traffic as PayPal. As of late 2012 the network is handling 0.5 transactions/second, so even assuming enormous growth in popularity we will not reach this level for a long time.

Network

Let's assume an average rate of 2000tps, so just VISA. Transactions vary in size from about 0.2 kilobytes to over 1 kilobyte, but it's averaging half a kilobyte today.

That means that you need to keep up with around 8 megabits/second of transaction data (2000tps * 512 bytes) / 1024 bytes in a kilobyte / 1024 kilobytes in a megabyte = 0.97 megabytes per second * 8 = 7.8 megabits/second.

This sort of bandwidth is already common for even residential connections today, and is certainly at the low end of what colocation providers would expect to provide you with.

When blocks are solved, the current protocol will send the transactions again, even if a peer has already seen it at broadcast time. Fixing this to make blocks just list of hashes would resolve the issue and make the bandwidth needed for block broadcast negligable. So whilst this optimization isn't fully implemented today, we do not consider block transmission bandwidth here.

Storage

At very high transaction rates each block can be over half a gigabyte in size.

It is not required for most fully validating nodes to store the entire chain. In Satoshis paper he describes "pruning", a way to delete unnecessary data about transactions that are fully spent. This reduces the amount of data that is needed for a fully validating node to be only the size of the current unspent output size, plus some additional data that is needed to handle re-orgs. As of October 2012 (block 203258) there have been 7,979,231 transactions, however the size of the unspent output set is less than 100MiB, which is small enough to easily fit in RAM for even quite old computers.

Only a small number of archival nodes need to store the full chain going back to the genesis block. These nodes can be used to bootstrap new fully validating nodes from scratch but are otherwise unnecessary.

The primary limiting factor in Bitcoins performance is disk seeks once the unspent transaction output set stops fitting in memory. It is quite possible that the set will always fit in memory on dedicated server class machines, if hardware advances faster than Bitcoin usage does.

Optimizations

The description above applies to the current software with only minor optimizations assumed (the type that can and have been done by one man in a few weeks).

However there is potential for even greater optimizations to be made in future, at the cost of some additional complexity.

CPU

Newly developed digital signature algorithms, like ed25519 have extremely efficient software implementations that can reach speeds of nearly 80,000 verifications per second, even on an old Westmere CPU. That is a 10x improvement over secp256k1, and most likely is even higher on more modern CPUs. Supporting this in Bitcoin would mean a "soft fork" like the one done recently for pay-to-script-hash support.

Algorithms exist to accelerate batch verification over elliptic curve signatures. This means if there are several inputs that are signing with the same key, it's possible to check their signatures simultaneously for another 9x speedup. This is a somewhat more complex implementation, however, it can work with existing signatures (clients don't need upgrading).

Assuming no upgrades to lightweight/SPV clients, so just batch verification, we can reach 40,000 transactions per second which is far beyond the traffic levels of the entire credit card system. And with ed25519 we could go up to nearly half a million transactions per second - with todays hardware!

Simplified payment verification

It's possible to build a Bitcoin implementation that does not verify everything, but instead relies on either connecting to a trusted node, or puts its faith in high difficulty as a proxy for proof of validity. BitCoinJ is an implementation of this mode.

In Simplified Payment Verification (SPV) mode, named after the section of Satoshi's paper that describes it, clients connect to an arbitrary full node and download only the block headers. They verify the chain headers connect together correctly and that the difficulty is high enough. They then request transactions matching particular patterns from the remote node (ie, payments to your addresses), which provides copies of those transactions along with a Merkle branch linking them to the block in which they appeared. This exploits the Merkle tree structure to allow proof of inclusion without needing the full contents of the block.

As a further optimization, block headers that are buried sufficiently deep can be thrown away after some time (eg, you only really need to store say 1000 blocks).

The level of difficulty required to obtain confidence the remote node is not feeding you fictional transactions depends on your threat model. If you are connecting to a node that is known to be reliable, the difficulty doesn't matter. If you want to pick a random node, the cost for an attacker to mine a block sequence containing a bogus transaction should be higher than the value to be obtained by defrauding you. By changing how deeply buried the block must be, you can trade off confirmation time vs cost of an attack.

Programs implementing this approach can have fixed storage/network overhead in the null case of no usage, and resource usage proportional to received/sent transactions.

See also: Thin Client Security.