Average fee per block btc

Some desire fast confirmation; some are content with waiting a while. Some use wallets with excellent dynamic fee estimation; some do not. In addition, demand varies according to certain patterns, with perhaps the most recognizable being the weekly cycle where fees increase during weekdays and decrease on the weekend: Another less recognizable cycle is the intra-day cycle where fees wax and wane during the day: These variations in supply and demand create a market for block space that allows users to make a trade-off between confirmation time and cost.

Users with high time requirements may pay a higher than average transaction fee to be confirmed quickly, while users under less time pressure can save money by being prepared to wait longer for either a natural but unpredictable increase in supply or a somewhat predictable decrease in demand. It is envisioned that over time the cumulative effect of collecting transaction fees will allow those creating new blocks to "earn" more bitcoins than will be mined from new bitcoins created by the new block itself.

This is also an incentive to keep trying to create new blocks as the creation of new bitcoins from the mining activity goes towards zero in the future. This section describes why feerates are important and how to calculate a transaction's feerate. Bitcoin transactions vary in size for a variety of reasons.

We can easily visualize that by drawing four transactions side-by-side based on their size length with each of our examples larger than the previous one: This method of illustrating length makes it easy to also visualize an example maximum block size limit that constrains how much transaction data a miner can add to an individual block: Since Bitcoin only allows whole transactions to be added to a particular block, at least one of the transactions in the example above can't be added to the next block.

So how does a miner select which transactions to include? There's no required selection method called policy and no known way to make any particular policy required, but one strategy popular among miners is for each individual miner to attempt to maximize the amount of fee income they can collect from the transactions they include in their blocks. We can add a visualization of available fees to our previous illustration by keeping the length of each transaction the same but making the area of the transaction equal to its fee.

This makes the height of each transaction equal to the fee divided by the size, which is called the feerate: Although long wide transactions may contain more total fees, the high-feerate tall transactions are the most profitable to mine because their area is greatest compared to the amount of space length they take up in a block. For example, compare transaction B to transaction D in the illustration above.

This means that miners attempting to maximize fee income can get good results by simply sorting by fee rate and including as many transactions as possible in a block: Because only complete transactions can be added to a block, sometimes as in the example above the inability to include the incomplete transaction near the end of the block frees up space for one or smaller and lower-feerate transactions, so when a block gets near full, a profit-maximizing miner will often ignore all remaining transactions that are too large to fit and include the smaller transactions that do fit still in highest-feerate order : Excluding some rare and rarely-significant edge cases, the feerate sorting described above maximizes miner revenue for any given block size as long as none of the transactions depend on any of the other transactions being included in the same block see the next section, feerates for dependent transactions, for more information about that.

To calculate the feerate for your transaction, take the fee the transaction pays and divide that by the size of the transaction currently based on weight units or vbytes but no longer based on bytes. For example, if a transaction pays a fee of 2, nanobitcoins and is vbytes in size, its feerate is 2, divided by , which is 10 nanobitcoins per vbyte this happens to be the minimum fee Bitcoin Core Wallet will pay by default. When comparing to the feerate between several transactions, ensure that the units used for all of the measurements are the same.

For example, some tools calculate size in weight units and others use vbytes; some tools also display fees in a variety of denominations. Feerates for dependent transactions child-pays-for-parent Bitcoin transactions can depend on the inclusion of other transactions in the same block, which complicates the feerate-based transaction selection described above. This section describes the rules of that dependency system, how miners can maximize revenue while managing those dependencies, and how bitcoin spenders can use the dependency system to effectively increase the feerate of unconfirmed transactions.

Each transaction in a block has a sequential order, one transaction after another. Each block in the block chain also has a sequential order, one block after another. This means that there's a single sequential order to every transaction in the best block chain. One of Bitcoin's consensus rules is that the transaction where you receive bitcoins must appear earlier in this sequence than the transaction where you spend those bitcoins.

For example, if Alice pays Bob in transaction A and Bob uses those same bitcoins to pay Charlie in transaction B, transaction A must appear earlier in the sequence of transactions than transaction B. Often this is easy to accomplish because transaction A appears in an earlier block than transaction B: But if transaction A and B both appear in the same block, the rule still applies: transaction A must appear earlier in the block than transaction B.

This complicates the task of maximizing fee revenue for miners. Normally, miners would prefer to simply sort transactions by feerate as described in the feerate section above. But if both transaction A and B are unconfirmed, the miner cannot include B earlier in the block than A even if B pays a higher feerate. This can make sorting by feerate alone less profitable than expected, so a more complex algorithm is needed.

Happily, it's only slightly more complex. For example, consider the following four transactions that are similar to those analyzed in the preceding feerate section: To maximize revenue, miners need a way to compare groups of related transactions to each other as well as to individual transactions that have no unconfirmed dependencies. To do that, every transaction available for inclusion in the next block has its feerate calculated for it and all of its unconfirmed ancestors.

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. Proof-Of-Work Algorithm 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. 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. Example 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 Simplified proof-of-work implementation! In Example , you can see how it works on an average laptop.

Success with nonce 9 Hash is 1c1ce65bfa8f93ddf3dabbbccecb3c1 Elapsed Time: 0. Success with nonce 25 Hash is 0f7becfd3bcd1a82ecadd89e7caede46f94e7e11bce Elapsed Time: 0. Success with nonce 36 Hash is ae6eaadcbbab1cf0b94cba8bac1d47e Elapsed Time: 0. Success with nonce Hash is bb8f0efb8edae85fb3cd2bdfe8bab6cefc3 Elapsed Time: Success with nonce Hash is cf12dbd20fcbaaedc6ffa9f74f5df4df0a3 Elapsed Time: Success with nonce Hash is c3d6bfccdd1b7cb4abd68b2acce8b95 Elapsed Time: Success with nonce Hash is f0ea21eb6dde5adb9da9f2bab2fcbca22b1e21a Elapsed Time: 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. 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.

In binary that number would have more than the first 60 bits set to zero. Difficulty Target and Retargeting 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. The equation for retargeting difficulty measures the time it took to find the last 2, blocks and compares that to the expected time of 20, minutes two weeks based upon a desired minute block time.

The ratio between the actual timespan and desired timespan is calculated and a corresponding adjustment up or down is made to the difficulty. In simple terms: If the network is finding blocks faster than every 10 minutes, the difficulty increases. If block discovery is slower than expected, the difficulty decreases.

Retargeting the proof-of-work difficulty—GetNextWorkRequired in pow. ProofOfWorkLimit ; Note While the difficulty calibration happens every 2, blocks, because of an off-by-one error in the original Bitcoin Core client it is based on the total time of the previous 2, blocks not 2, as it should be , resulting in a retargeting bias towards higher difficulty by 0.

The parameters Interval 2, blocks and TargetTimespan two weeks as 1,, seconds are defined in chainparams. To avoid extreme volatility in the difficulty, the retargeting adjustment must be less than a factor of four 4 per cycle.

If the required difficulty adjustment is greater than a factor of four, it will be adjusted by the maximum and not more. Any further adjustment will be accomplished in the next retargeting period because the imbalance will persist through the next 2, blocks. Therefore, large discrepancies between hashing power and difficulty might take several 2, block cycles to balance out.

Tip The difficulty of finding a bitcoin block is approximately 10 minutes of processing for the entire network, based on the time it took to find the previous 2, blocks, adjusted every 2, blocks. Note that the target difficulty is independent of the number of transactions or the value of transactions. This means that the amount of hashing power and therefore electricity expended to secure bitcoin is also entirely independent of the number of transactions.

The increase in hashing power represents market forces as new miners enter the market to compete for the reward. The target difficulty is closely related to the cost of electricity and the exchange rate of bitcoin vis-a-vis the currency used to pay for electricity.

High-performance mining systems are about as efficient as possible with the current generation of silicon fabrication, converting electricity into hashing computation at the highest rate possible. The primary influence on the mining market is the price of one kilowatt-hour in bitcoin, because that determines the profitability of mining and therefore the incentives to enter or exit the mining market.

Jing has several hardware mining rigs with application-specific integrated circuits, where hundreds of thousands of integrated circuits run the SHA algorithm in parallel at incredible speeds. These specialized machines are connected to his mining node over USB. Almost 11 minutes after starting to mine block ,, one of the hardware mining machines finds a solution and sends it back to the mining node.

They receive, validate, and then propagate the new block. As the block ripples out across the network, each node adds it to its own copy of the blockchain, extending it to a new height of , blocks. As mining nodes receive and validate the block, they abandon their efforts to find a block at the same height and immediately start computing the next block in the chain. As the newly solved block moves across the network, each node performs a series of tests to validate it before propagating it to its peers.

This ensures that only valid blocks are propagated on the network. The independent validation also ensures that miners who act honestly get their blocks incorporated in the blockchain, thus earning the reward. Those miners who act dishonestly have their blocks rejected and not only lose the reward, but also waste the effort expended to find a proof-of-work solution, thus incurring the cost of electricity without compensation.

When a node receives a new block, it will validate the block by checking it against a long list of criteria that must all be met; otherwise, the block is rejected. In previous sections we saw how the miners get to write a transaction that awards them the new bitcoins created within the block and claim the transaction fees. Because every node validates blocks according to the same rules. An invalid coinbase transaction would make the entire block invalid, which would result in the block being rejected and, therefore, that transaction would never become part of the ledger.

The miners have to construct a perfect block, based on the shared rules that all nodes follow, and mine it with a correct solution to the proof of work. To do so, they expend a lot of electricity in mining, and if they cheat, all the electricity and effort is wasted. This is why independent validation is a key component of decentralized consensus.

Once a node has validated a new block, it will then attempt to assemble a chain by connecting the block to the existing blockchain. Nodes maintain three sets of blocks: those connected to the main blockchain, those that form branches off the main blockchain secondary chains , and finally, blocks that do not have a known parent in the known chains orphans. Invalid blocks are rejected as soon as any one of the validation criteria fails and are therefore not included in any chain.

Under most circumstances this is also the chain with the most blocks in it, unless there are two equal-length chains and one has more proof of work. These blocks are valid but not part of the main chain. They are kept for future reference, in case one of those chains is extended to exceed the main chain in difficulty. In the next section Blockchain Forks , we will see how secondary chains occur as a result of an almost simultaneous mining of blocks at the same height.

When a new block is received, a node will try to slot it into the existing blockchain. Then, the node will attempt to find that parent in the existing blockchain. For example, the new block , has a reference to the hash of its parent block , Most nodes that receive , will already have block , as the tip of their main chain and will therefore link the new block and extend that chain. Sometimes, as we will see in Blockchain Forks , the new block extends a chain that is not the main chain.

In that case, the node will attach the new block to the secondary chain it extends and then compare the difficulty of the secondary chain to the main chain. If the secondary chain has more cumulative difficulty than the main chain, the node will reconverge on the secondary chain, meaning it will select the secondary chain as its new main chain, making the old main chain a secondary chain.

If the node is a miner, it will now construct a block extending this new, longer, chain. Once the parent is received and linked into the existing chains, the orphan can be pulled out of the orphan pool and linked to the parent, making it part of a chain. Orphan blocks usually occur when two blocks that were mined within a short time of each other are received in reverse order child before parent.

By selecting the greatest-difficulty chain, all nodes eventually achieve network-wide consensus. Temporary discrepancies between chains are resolved eventually as more proof of work is added, extending one of the possible chains. When they mine a new block and extend the chain, the new block itself represents their vote. In the next section we will look at how discrepancies between competing chains forks are resolved by the independent selection of the longest difficulty chain.

Blockchain Forks Because the blockchain is a decentralized data structure, different copies of it are not always consistent. Blocks might arrive at different nodes at different times, causing the nodes to have different perspectives of the blockchain. To resolve this, each node always selects and attempts to extend the chain of blocks that represents the most proof of work, also known as the longest chain or greatest cumulative difficulty chain. By summing the difficulty recorded in each block in a chain, a node can calculate the total amount of proof of work that has been expended to create that chain.

As long as all nodes select the longest cumulative difficulty chain, the global bitcoin network eventually converges to a consistent state. Forks occur as temporary inconsistencies between versions of the blockchain, which are resolved by eventual reconvergence as more blocks are added to one of the forks. The diagram is a simplified representation of bitcoin as a global network. Rather, it forms a mesh network of interconnected nodes, which might be located very far from each other geographically.

The representation of a geographic topology is a simplification used for the purposes of illustrating a fork. For illustration purposes, different blocks are shown as different colors, spreading across the network and coloring the connections they traverse. In the first diagram Figure , the network has a unified perspective of the blockchain, with the blue block as the tip of the main chain.

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