What the Tech? Matrix Verification Masternode May Earnings Report

Matrix AI Network
Jun 8 · 4 min read

Updated Matrix Verification Masternode participation incentive statistics!

Last month, the Matrix AI Network started publishing Verification Masternode participation incentive statistics. As the Matrix AI Network’s participation incentives will continue to adapt, change and normalize over time, the Matrix team plans to release updated statistics on a monthly basis. These reports help highlight the real impact of the numerous network adjustments and upgrades. For basic information about Matrix Masternode participation incentives, please read “An Introduction to the Matrix AI Network.”

Qualifications

  • Two data samples are used:
  1. May 1st 2019 to May 31st 2019
  • Data only considers block rewards. Stake rewards and other incentives such as airdrops are not included in the calculation

Verification Masternode Annual ROI — May 1st 2019 to May 31st 2019

Between May 1st and May 31st, 2019, a total of 180 Verification Masternodes were online for at least 2500 minutes. The number of recorded Verification Masternodes per stake level is as follows:

Verification Masternode Annual ROI — April 13th 2019 to May 31st 2019

Between April 13th and May 31st, 2019, a total of 246 Verification Masternodes were online for at least 2500 minutes. The number of recorded Verification Masternodes per stake level is as follows:

Clarifications

  1. Why are there so many Verification Masternodes included in the data? And why does the number of Verification Masternodes differ between the first sample and the second?
  • The number of active Verification Masternodes will naturally vary on a month to month basis. New Masternodes will join the network, others will become Mining Masternoders, and others still will shut down completely. Additionally, in an effort to have more accurate results, if an individual Masternode added to their stake such that their Masternode entered a new stake level, they were considered as two separate nodes; so long as the Masternode spent more than 2500 minutes online at both stake levels.

2. Why are there large, seemingly random, deviations between stake levels?

  • There are several factors contributing to this including the relatively low minimum uptime requirement for inclusion in this data set (2500 minutes) and the unequal number of nodes at each stake level. Additionally, the dataset includes Masternodes that have been forced to forfeit selection opportunities due to being malicious, malfunctioning or offline (more on this below). This certainly impacts the published ROI — particularly among the smaller Verification Masternodes. Larger Verification Masternodes are fewer in number and have historically experienced fewer technical difficulties. As such, the ROI of these nodes has already stabilized. Raising the sample size to being online for over 5000 minutes or 10,000 minutes illustrates this phenomenon.

Final Thoughts

The Matrix AI Network was updated on May 20th 2019. The primary goal of this update was to increase the stability of the network. Part of this updated included increased penalties to offline, malicious and malfunctioning Verification Masternodes. Any Verification Masternode that failed to perform its duties for the entirety of a selection cycle now forfeits its next 10 selections. The data used in this month’s earnings report is certainly impacted by several Verification Masternodes being removed from circulation for extended periods of time. In future earnings reports, the Matrix Team will consider removed malfunctioning nodes from the data.

If you find that your current performance differs greatly from the data listed above, your node likely isn’t properly deployed. If you are experiencing issues with your Matrix Masternode, please send an email to public@matrix.io or contact a member of the Matrix team on Telegram.


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Matrix AI Network

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Matrix AI Network leverages the latest AI technology to deliver on the promise of blockchain. Website: www.matrix.io Telegram: t.me/matrixainetwork