Ethereum mining difficulty graph
This is a mismatch and has interested me for some time. Recently, returning to the problem and after learning they are represented best by a Poisson Point Process I have a theory you can use this fact to build a different, simpler, algorithm that also better fits the probability distribution. Hopefully this means better responsiveness and less unnecessary adjustments. I am unsure, but I am at the point where I could use help simulating different cases. Anyone interested in helping me out on this?
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- What Is Ethereum's "Difficulty Bomb"?
- Ethereum Classic Charts
- What is the Ethereum Difficulty Bomb (Ice Age)?
- Ethereum Difficulty historical chart
- Bitcoin Mining Difficulty Has Made A New All-Time High
- Bitcoin Cash Difficulty Graph
- Bitcoin Difficulty
- Another upgrade to the Ethereum network just went live. Here’s what to know
- Ethereum Classic
What Is Ethereum's "Difficulty Bomb"?
This is a mismatch and has interested me for some time. Recently, returning to the problem and after learning they are represented best by a Poisson Point Process I have a theory you can use this fact to build a different, simpler, algorithm that also better fits the probability distribution. Hopefully this means better responsiveness and less unnecessary adjustments. I am unsure, but I am at the point where I could use help simulating different cases. Anyone interested in helping me out on this?
A deeper explanation of the discovery and possible solutions below. Previously at the Status Hackathon before Devcon last year, Jay Rush and I researched the effects of the time bomb on the up and coming fork. It followed some kind of exponential distribution but not exactly.
I view it as each miner is a racehorse, but the horse only runs after he hears the starting pistol. Mining is Poisson Point Process because each blocktime is completely independent from the previous block time. This leads to a Poisson Distribution which wikipedia has a better explanation than I can write. This is the Distribution of just under blocks spanning from Sept 7th to Sept 8th Thank you Jay Rush for this!
I still have the data from when we worked on the Time-bomb together. It plus the charts below are available on the Google Sheet I used to prepare for this post. You can see after 3 seconds there is some kind of exponential curve. The 1 in this changes for every bucket of A great stackexchange post that goes into this further. Now lets look at the distribution of blocks within each of these buckets.
Here I also add an exponential line of best fit. It is easier to see this side by side. I want to understand it fully and then publish my findings. That is all. And, perhaps write an EIP for the experience of writing one.
That being said, this is where I have gotten so far. In the case of block times it would be the average number of blocks per some unit of time. What is nice about this distribution is you can calculate the probability of occurrences in a given time period.
In our collected data above block time was an average Some example calculations from this number. Within seconds what is the probability we would see n blocks. Now given this information we can also ask this in reverse. Or in Ethereum Terms given the number of blocks within a fixed time period what is the probability the average blocktime is An illustration of a marked point process, where the unmarked point process is defined on the positive real line, which often represents time.
The random marks take on values in the state space known as the mark space. Any such marked point process can be interpreted as an unmarked point process on the space. The marking theorem says that if the original unmarked point process is a Poisson point process and the marks are stochastically independent, then the marked point process is also a Poisson point process on.
If the Poisson point process is homogeneous, then the gaps in the diagram are drawn from an exponential distribution. The graph above is similar to plotting blocks over time. The following is a chart of the blocks over constant time seconds starting with the block found on Sep PM.
In the graph above three sections are conveniently segmented. Not particularly useful, as a 6. In practical terms asserting that the current block difficulty should be changed. But, If in case you use a range like the before mentioned between 10 and 16 blocks there is a Stated inversely, if there is less than 10 or greater than 16 blocks, there is a This means when adjusting the difficulty outside of these ranges you are, more often then not, correct to do so.
This and as well as more rigorous maths narrowing testing ranges for:. A more specific example. In the case greater than 17 is selected as the upper adjustment threshold. The scalar can be defined to increase in magnitude proportional to the following equation.
The difference of the scalar between 18 and 20 would be nearly a 2x increase. This would much more closely resemble the exponential distribution in observed blocktimes. Using this method I hope to document a practical alternative to targeting a blocktime for a PoW chain. One that is simple to calculate as well as follows more closely the actual distribution found in blocktimes. Please any feedback from mathematicians, statisticians, computer scientists, or interested parties would be appreciated.
As well as anyone willing to look at testing and simulation implementations. I also have no idea if this bares anything on the beacon chain found in Serenity. Which if it does, I would love to know. I anticipated as much. Improvements in areas with greatest impact is more than understandable. Especially for Eth 1. Thanks for taking the time to check it out. It is nice to hear feedback it is at least in a good direction.
I am not sure I want to go through the process of writing an EIP for it given how very unlikely it is to be implemented, but it feels good to have thought it through and written it out this far. Worked with Hawkes Processes and Poisson Point Processes in the past, have been thinking along a Beta distribution however to capture second order statistics so as to have an estimator on conditional variance.
Not only does this make more sense, but it allows for iterative market-clearing price formation. A reference on some of the information economics: Grossman and Stiglitz - On the Impossibility of Informationally Efficient Markets slides. X on the new fee structure. I was the one that had the question about targeting Uncle Rates. If it comes to a point where that is revisited this mechanism may be a good way to do just that.
Summarized as follows:. Also, it would reward network optimizations immediately that can be done off-chain because the BlockTime can adjust to along the way. The chain operating as fast as is healthy. In physics, it is quite common to approximate functions using Taylor series. I expect that a mathematically exact solution to the difficulty adjustment problem can be reduced to a linear approximation. That would show that the current system is a good approximation assuming the variation in mean block time is low.
If we take a long enough time period T, the amount of blocks in that time period N T will be equal to the expected amount of blocks for the current E[N T ]. The relation is not direct, there might be unexpected game theoretical consequences when the difficulty changes. For example, some miners might not be profitable and turn off after a certain difficulty.
However, for small changes the effect will be linear; the expected number of events in a time period changes inversely with the difficulty. For larger fixed values of T, the difficulty will change slowly and the number of blocks will be close to the expected value. In other words, we obtain the negative linear relationship. A slightly different derivation to prevent this inverts it and swaps the negative sign:.
He came about it by a more lengthy thinking process. This 1-block delay causes bad oscillations unless N is large I think it needs to be over ThomasdenH Your first paragraph was exactly correct. You have. The N ts is how long it took to observe N blocks.
So you attach a ratio at the end to make the correction. For large N the correction is not noticed. The more precise answer is that it follows an inverse gamma distribution which is not the same as an inverse of the gamma distribution otherwise I think your last paragraph would have been correct.
Rolling averages need a much smaller correction their long term average is not as accurate for small N if hashrate is constant, but otherwise they are a lot more accurate.
The correct rolling average equations are. This is not usually a problem because most coins do difficulty in terms of target instead of difficulty. Mark Lundeberg suggested an algorithm that I recognized as solving a long-standing problem in that none of them give perfect avg solvetime when their parameter is made fast.
For example, a simple moving avg based on just the previous block is way off. In the above, the EMA loses accuracy at small N. Namely, the observed solvetime, mapped to the exponential distribution, is the numerator, and the expected solvetime for the target is the denominator. The N factor being a power function is the result of the target being recursively multiplied.
Jacob eliosoff investigated this in but did not pursue it because simplified ema gives almost the same result without the exponentials or power function.
Ethereum Classic Charts
The flip side of any proof-of-work cryptocurrency system is the impact of mining difficulty on the network as a whole. Miners provide an essential service to any cryptocurrency that needs hash power to provide, keeping the network stable. The more people are employed in mining, the higher the security of the ecosystem. In exchange for the provided hashpower, miners receive appropriate rewards.
What is the Ethereum Difficulty Bomb (Ice Age)?
T-Rex is a versatile cryptocurrency mining software. It supports a variety of algorithms and we, as developers, are trying to do our best to make it as fast and as convenient to use as possible. To start T-Rex with config file config. If a parameter is set in the config file and also via cmd line, the latter takes precedence, for example: t-rex -c config. Watchdog is intended to observe miner state and restart T-Rex if it crashes or hangs for any reason. Also, watchdog can optionally perform auto updates if a newer version is available. If you do need to disable the watchdog, you can do so using --no-watchdog parameter. In order to protect the miner from reverse engineering attacks, the binaries are packed using a third-party software which mangles the original machine code. As a result, some antivirus engines may detect certain signatures within the executable that are similar to those that real viruses protected by the same packer have.
Ethereum Difficulty historical chart
A nimbler Bitcoin Cash Difficulty adjustment algorithm :. Come November 13, Bitcoin Cash. If a group of people know they control an overwhelming economic majority of activity blockchain, they have the ability to do whatever they want within their economic group. Bitcoin difficulty vs price chart - Discussion Anyone have a forward projection on the increase in difficulty vs the increase in the btc price? An easy to use crypto-currency finance utility used to calculate a Bitcoin miner's potential profits in ETH and multiple fiat A projected future profit chart is created dynamically and displayed instantly.
Bitcoin Mining Difficulty Has Made A New All-Time High
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Bitcoin Cash Difficulty Graph
Statistics server is temporarily offline. This doesn't affect the mining process. Mining works fine. Ethereum Difficulty Real time and historical statistics on Ethereum network difficulty. The ETH difficulty is adjusted periodically as a function of an average block finding time.
Bitcoin Difficulty
Ethereum is a public blockchain platform that allows developers to build and deploy decentralized applications. Ethereum runs smart contracts, which allow a higher level of protection from downtime, censorship, fraud or third party interference. Ether is a tradeable cryptocurrency, used by application developers to fuel the Ethereum network.
Another upgrade to the Ethereum network just went live. Here’s what to know
RELATED VIDEO: Polygon Не Работает? Майнинг Ethereum на Ethermine 2022 и Решение Возможных ПроблемHelp us translate the latest version. Page last updated : January 30, This introductory paper was originally published in by Vitalik Buterin, the founder of Ethereum , before the project's launch in It's worth noting that Ethereum, like many community-driven, open-source software projects, has evolved since its initial inception. While several years old, we maintain this paper because it continues to serve as a useful reference and an accurate representation of Ethereum and its vision. To learn about the latest developments of Ethereum, and how changes to the protocol are made, we recommend this guide.
Ethereum Classic
Check the Hardware. But consider the amount of stress and heat you're putting on your computer. The GPU is the chip that enables graphics cards often called GPUs for brevity in mining circles to perform millions of repetitive calculations at the same time so that games can be rendered in real time. Gpu Mining Select your graphics card GPU and calculate its power and power consumption for mining on different algorithms. GPU mining ensured a much higher hash rate at a much lower rate of energy consumption. Your GPU or mining rig is calculating thousands, millions of sol solutions per second.
First thing you need it to get proper data. Here is the link where you can download csv data. Go to ribbon Insert tab and choose Insert 2D line chart.
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