Usually a miner’s reward directly depends on network hashrate, meaning larger nethash results in lower reward portion going to each miner. In other words, if the amount of GPUs in the network grows 1000 times, the average miners reward within given time frame will become 1000 times less. Some cryptocurrencies use non-linear dependencies, but their principle also remains the same, higher the network hashrate, less each miner receives. BitGun uses another approach – as total network hashrate grows, the block reward gradually increases, allowing to keep an average miners reward relatively stable.
This is how it works.
The reward size for each block changes every time at the moment of block generation, depending on the total average nethash recorded for the last 24 blocks.
The reward size for each block changes in accordance with a set of “levels” reflecting the Fibonacci series. There are 15 levels.
Table 1 presents the levels defined by total nethash and the corresponding block reward size .
For the block reward size to change automatically, the total XDNA nethash must overcome the corresponding threshold value from the table.
What are the advantages of using this approach?
Comparing with the conventional block reward calculation methods, BitGun allows us to stabilize the reward amount received by miners in the certain period of time. With a sufficient growth of network hashrate the average reward slightly decreases, remaining, however, much larger than in systems with traditional distribution.
Table 2 shows comparison of an average reward for one Nvidia GTX 1080Ti GPU for 24 hours using classical calculation method and BitGun.
As shown in the table above, at low network hashrate the reward remains almost identical, but as network grows the advantage of BitGun becomes obvious.
Figure 1 presents the comparison of daily reward for a single Nvidia GeForce GTX 1080ti GPU depending on total network hashrate, stated in number of mining GPUs.
Mathematical modelling was performed for levels 1-8. For this simulation, we used the following conditions: a miner gets a reward from each block; hashrate of a single GPU is 1.35 gh/s for Keccak algorithm.
As we see even with a significant increase in network hashrate each given GPU will keep receiving relatively stable reward within one BitGun level, this reward is much larger than a reward, calculated using classic system would be.
These simulation results are valid for Levels 2-14 and can be successfully approximated for any time interval.
The novelty of this approach is primarily in the fact that it changes the very paradigm of pseudolinear inverse relation of miner`s income to the nethash.
BitGun also has another, not so obvious advantage. If ASIC miners for Keccak algo are ever developed, XDNA won’t have to change it’s consensus, algorithm, or to implement a hardfork in order to keep GPU miners happy. Few minor amendments in BitGun parameters should be enough.
Miners from all over the world can now count on decent mining rewards even if the network hashrate suddenly grows 1000 times.
How T.N.T. system works:
In general, all masternode projects have similar rewarding system: «Each SINGLE block only ONE masternode wins the masternode reward» There are many tiered masternode projects with a different coin amount requirement for a different masternode tiers.
But, if you think that different tier masternodes get separate rewards from a block – you are mistaken. Even if a project has 5 MN tiers – each block only 1 masternode gets a reward. If it is tier1 masternode – it gets block reward for tier 1. If tier 5 – for tier 5.
But in XDNA we made a unique part of coin, providing multiple block outputs for MN rewards. In brief, it means: «Each SINGLE block THREE masternodes of different tiers get THREE different masternode rewards» So, If in a common masternode project we have: 30MN T1, 50MN T2, 100 MN T3, 10 MN T4 and 10 MN T5 this is counted as just a bulk of 200 MN in network and only 1 will get this reward.
But, if we are speaking about XDNA T. N. T. system and we got: 50 MN T1 (Light), 10 MN T2 (Medium) and 5 MN T3 (Full) the randomizer process will process 3 different directions: 3% from a block reward between 50 MN T1 (Light), 9% from a block reward between 10 MN T2 (Medium) and 15% from a block reward between ONLY 5 MN T3 (Full).
If we had a common MN reward system, the owners of XDNA Full masternodes would share their chances to get rewards between 65 MN’s , but in our T.N.T. system each type of masternodes has their own prize pool, so they share the chance of getting the reward only between other Full masternode owners.
T. N. T. Description
Relying only on the most advanced aspects of the world leading cryptocurrencies, we propose to use masternodes to ensure network stability.
However, given the experience of creating and using masternodes in different projects, we put harmony between miners and investors’ wishes and possibilities on the first place at XDNA. To make it possible for everyone to set up a masternode, we have developed three types of them. Each type takes a different amount of XDNA and brings a variety of income. This system is called T.N.T. – TripleNodeTechnology.
During POW masternodes will receive the following reward (different for each type) for maintaining network stability and performing additional functions:
During POS the masternode reward proportion will remain but the amounts will be determined by the SeeSaw algorithm.
Despite the main masternodes task being network stability, they are also an excellent means of investment.
Series of calculations have been done to determine the profitability and reward for different types of masternodes.
It should be noted that BitGun levels are directly affecting masternodes profitability – block reward at higher nethash increases, therefore masternodes income increases as well.
Fig. 1 shows the calculation results for the payback of different masternode types at various BitGun levels, depending on masternodes amount in the network.
We have also calculated daily masternode payouts for a set number of 50 masternodes depending on their type and BitGun level functioning in the network (Fig.2) and annual ROI depending on BitGun level for each masternode type when 100 masternodes of each type exist in the network (Fig. 3).
