Analysis and Comparison

What?

Side-by-side analysis of the Monero and Aeon blockchains.

By performing these analysis, I hope to further cement Aeon's position as Monero's "little brother." After all, who doesn't want an increased sample size for their studies?

Why?

Aeon is an ideal candidate for comparison with Monero due to similiar release dates, implementation, and involved communities.

How much?

I do not want to set a target amount for this proposal, and would like this proposal to be closed in about a month's time. Any amount donated will be greatly appreciated.

I can typically produce plots in under four or five hours. However, learning background information and gathering data can takes weeks or months of my time.

Milestones

Please consider your donation directed toward what I have already created and my future education.

Past projects

• Transactions per Block By counting the number of transactions in each block and throwing them onto a scatterplot, we can add a piece of reasoning to a larger argument concerning either an increase or decrease in usage. I will not comment on either trend, but it does seem that the number of transfers per block suddenly increased for Monero sometime in November while Aeon did not experience a similiar trend. The entire blockchain: Image 1, and the last year: Image 2.
• Nonce Distributions Nonce distributions suggest the presence of ASICs and FPGAs when compared to network difficulty. Please see my reddit post for a more in depth explaination and additional references. Interestingly, when we compare Aeon with Monero, we can see the ASICS transition from the Monero network to Aeon when Aeon lagged behind the PoW change that was made to Monero on February 11, 2018. Image 1. When we zoom in to see just the last year, we see a concerning change to Monero's nonce distribution and difficutly over the last couple months: Image 2.
• Price Comparison Many users believe that Aeon should be worth around 1% of Monero's value. The linked image shows the ratio of Aeon to Monero over the last few years: Image.
• Blocktimes Blocktimes are expected to fall on along a Gaussian distribution. However, since miners submit blocks with their own timestamps, we see significant deviations from the normal distribution: Image.

Outcomes?

I love working with datasets and will continue to do so in my spare time. However, if the community shows that they value my efforts, I will approach this hobby with serious intent.

Why you?

I have a two years of experience working as a research assistent as an undergraduate. During this time, I created visualizations of datsets, performed image analysis, and wrote a few small simulations for discrete time stochastic processes.

I've been active in the community since July of last year. My username on Reddit is /u/kim-whan and BMO-noire in the community chat.