Discussions of Bitcoin's blockchain possibly forking shortly has caused some people to consider changing the digital currency's Proof-of-Work.
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Wallet software is expected to retransmit such transactions or reconstruct them with higher fees if they are not successfully executed within a reasonable amount of time. You can see this block in the blockchain using the Bitcoin Core client command-line interface, as shown in Example The first transaction added to the block is a special transaction, called a generation transaction or coinbase transaction. Unlike regular transactions, the generation transaction does not consume spend UTXO as inputs.
Instead, it has only one input, called the coinbase , which creates bitcoin from nothing. The output of the generation transaction sends the value of The fees are calculated as:.
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The reward is calculated based on the block height, starting at 50 bitcoins per block and reduced by half every , blocks. Because this block is at height ,, the correct reward is 25 bitcoins. The initial subsidy is calculated in satoshis by multiplying 50 with the COIN constant ,, satoshis.
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This sets the initial reward nSubsidy at 5 billion satoshis. Next, the function calculates the number of halvings that have occurred by dividing the current block height by the halving interval SubsidyHalvingInterval. In the case of block ,, with a halving interval every , blocks, the result is 1 halving. The maximum number of halvings allowed is 64, so the code imposes a zero reward return only the fees if the 64 halvings is exceeded. Next, the function uses the binary-right-shift operator to divide the reward nSubsidy by two for each round of halving.
In the case of block ,, this would binary-right-shift the reward of 5 billion satoshis once one halving and result in 2. The binary-right-shift operator is used because it is more efficient for division by two than integer or floating-point division. Finally, the coinbase reward nSubsidy is added to the transaction fees nFees , and the sum is returned. As you can see in Example , the generation transaction has a special format.
We examined transaction inputs in Table In a generation transaction, the first two fields are set to values that do not represent a UTXO reference. Generation transactions do not have an unlocking script a. Instead, this field is replaced by coinbase data, which must be between 2 and bytes.
Except for the first few bytes, the rest of the coinbase data can be used by miners in any way they want; it is arbitrary data. Currently, miners use the coinbase data to include extra nonce values and strings identifying the mining pool, as we will see in the following sections. The first few bytes of the coinbase used to be arbitrary, but that is no longer the case. The first byte, 03 , instructs the script execution engine to push the next three bytes onto the script stack see Table A The next three bytes, 0xb04 , are the block height encoded in little-endian format backward, least significant byte first.
Reverse the order of the bytes and the result is 0xb44 , which is , in decimal. The next few hexadecimal digits are used to encode an extra nonce see The Extra Nonce Solution , or random value, used to find a suitable proof of work solution. Note that the libbitcoin library contains a static copy of the genesis block, so the example code can retrieve the genesis block directly from the library.
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To construct the block header, the mining node needs to fill in six fields, as listed in Table At the time that block , was mined, the version number describing the block structure is version 2, which is encoded in little-endian format in 4 bytes as 0x The block header hash for block , is:. The next step is to summarize all the transactions with a merkle tree, in order to add the merkle root to the block header.
The generation transaction is listed as the first transaction in the block. Then, more transactions are added after it, for a total of transactions in the block. The node then fills in the difficulty target, which defines the required proof-of-work difficulty to make this a valid block. The encoding has a 1-byte exponent, followed by a 3-byte mantissa coefficient. In block ,, for example, the difficulty bits value is 0xa30c. The first part 0x19 is a hexadecimal exponent, while the next part, 0x03a30c , is the coefficient. The final field is the nonce, which is initialized to zero.
With all the other fields filled, the block header is now complete and the process of mining can begin. The goal is now to find a value for the nonce that results in a block header hash that is less than the difficulty target. The mining node will need to test billions or trillions of nonce values before a nonce is found that satisfies the requirement.
Throughout this book we have studied cryptographic hash functions as used in various aspects of the bitcoin system. In the simplest terms, mining is the process of hashing the block header repeatedly, changing one parameter, until the resulting hash matches a specific target. This feature of hash functions means that the only way to produce a hash result matching a specific target is to try again and again, randomly modifying the input until the desired hash result appears by chance. A hash algorithm takes an arbitrary-length data input and produces a fixed-length deterministic result, a digital fingerprint of the input.
For any specific input, the resulting hash will always be the same and can be easily calculated and verified by anyone implementing the same hash algorithm. The key characteristic of a cryptographic hash algorithm is that it is virtually impossible to find two different inputs that produce the same fingerprint. As a corollary, it is also virtually impossible to select an input in such a way as to produce a desired fingerprint, other than trying random inputs.
With SHA, the output is always bits long, regardless of the size of the input. Example shows the result of calculating the hash of "I am Satoshi Nakamoto" : 5d7c7ba21cbbcd75dbd5be5bd27cbcca6be. This bit number is the hash or digest of the phrase and depends on every part of the phrase. Adding a single letter, punctuation mark, or any other character will produce a different hash.
Now, if we change the phrase, we should expect to see completely different hashes. Running this will produce the hashes of several phrases, made different by adding a number at the end of the text. By incrementing the number, we can get different hashes, as shown in Example Each phrase produces a completely different hash result. They seem completely random, but you can reproduce the exact results in this example on any computer with Python and see the same exact hashes. The number used as a variable in such a scenario is called a nonce. The nonce is used to vary the output of a cryptographic function, in this case to vary the SHA fingerprint of the phrase.
It took 13 attempts to find it. In terms of probabilities, if the output of the hash function is evenly distributed we would expect to find a result with a 0 as the hexadecimal prefix once every 16 hashes one out of 16 hexadecimal digits 0 through F. In numerical terms, that means finding a hash value that is less than 0x We call this threshold the target and the goal is to find a hash that is numerically less than the target.
If we decrease the target, the task of finding a hash that is less than the target becomes more and more difficult. To give a simple analogy, imagine a game where players throw a pair of dice repeatedly, trying to throw less than a specified target. In the first round, the target is Unless you throw double-six, you win.
In the next round the target is Players must throw 10 or less to win, again an easy task. Now, more than half the dice throws will add up to more than 5 and therefore be invalid. It takes exponentially more dice throws to win, the lower the target gets. The successful result is also proof of work, because it proves we did the work to find that nonce.
While it only takes one hash computation to verify, it took us 13 hash computations to find a nonce that worked. If we had a lower target higher difficulty it would take many more hash computations to find a suitable nonce, but only one hash computation for anyone to verify. Furthermore, by knowing the target, anyone can estimate the difficulty using statistics and therefore know how much work was needed to find such a nonce.
The miner constructs a candidate block filled with transactions. If the hash is not less than the target, the miner will modify the nonce usually just incrementing it by one and try again. At the current difficulty in the bitcoin network, miners have to try quadrillions of times before finding a nonce that results in a low enough block header hash. A very simplified proof-of-work algorithm is implemented in Python in Example Running this code, you can set the desired difficulty in bits, how many of the leading bits must be zero and see how long it takes for your computer to find a solution.
In Example , you can see how it works on an average laptop. As you can see, increasing the difficulty by 1 bit causes an exponential increase in the time it takes to find a solution. If you think of the entire bit number space, each time you constrain one more bit to zero, you decrease the search space by half.
In Example , it takes 84 million hash attempts to find a nonce that produces a hash with 26 leading bits as zero. Even at a speed of more than , hashes per second, it still requires 10 minutes on a consumer laptop to find this solution.
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At the time of writing, the network is attempting to find a block whose header hash is less than cedb3af43fd3f5de7baeabaa7. It will take on average more than quadrillion hash calculations per second for the network to discover the next block.
In this block, therefore, the exponent is 0x19 and the coefficient is 0x03a30c. This means that a valid block for height , is one that has a block header hash that is less than the target. In binary that number would have more than the first 60 bits set to zero. As we saw, the target determines the difficulty and therefore affects how long it takes to find a solution to the proof-of-work algorithm.
This leads to the obvious questions: Why is the difficulty adjustable, who adjusts it, and how? It has to remain constant not just over the short term, but over a period of many decades. Over this time, it is expected that computer power will continue to increase at a rapid pace. Furthermore, the number of participants in mining and the computers they use will also constantly change. To keep the block generation time at 10 minutes, the difficulty of mining must be adjusted to account for these changes.
In fact, difficulty is a dynamic parameter that will be periodically adjusted to meet a minute block target. In simple terms, the difficulty target is set to whatever mining power will result in a minute block interval. How, then, is such an adjustment made in a completely decentralized network? Difficulty retargeting occurs automatically and on every full node independently.
Every 2, blocks, all nodes retarget the proof-of-work difficulty.