Bitcoin

What Happens When You Pay to Speed Up a Crypto Transaction?

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Summary / Zusammenfassung

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Chapter 1: Introduction

Introduction

1.1 Overview of the thesis contributions

1.2 Overview of the thesis

Chapter 2: Context

2.1 Blongschains and intelligent contracts

2.2 Transactions prioritization standards

2.3 Transparency of prioritization and compression of transactions

2.4 Decentralized governance

2.5 Blockchain scalability with layer 2.0 solutions

Chapter 3. Standards of hierarchy of transactions

Transactions hierarchy standards

3.1 Methodology

3.2 Analyze standards membership

3.3 Investigation of standards violations

3.4 Fresh black transactions

3.5 Final remarks

Chapter 4. Transparency of prioritization of transactions and compression

Transparency of prioritization and compression of transactions

4.1 Methodology

4.2 On the transparency of affirmations

4.3 On the transparency of hierarchy

4.4 Final remarks

Chapter 5. Decentralized governance

Decentralized governance

5.1 Methodology

5.2 Governance attacks

5.3 Governance of the compound

5.4 Final remarks

Chapter 6. Related work

6.1 Transactions prioritization standards

6.2 Transparency of hierarchy and compression of transactions

6.3 Decentralized governance

Chapter 7. Discussion, limitations and future work

7.1 Transaction control

7.2 Transparency of transactions

7.3 Distribution of voting power to modify intelligent contracts

Conclusion

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Annexes

Annex A: Additional analysis of hierarchy standards

Annex B: additional analysis of transactions prioritization and transparency of affirmations

Annex C: Additional analysis of the distribution of voting power

Bibliography

Annex B: additional analysis of transactions prioritization and transparency of affirmations

B.1 Ethereum private transaction experience

We have conducted 4 active experiences where we issued 8 Ethereum transactions; Half has published publicly and the other half in private through a network of private channels known as Taichi Network (Sparkpool, 2021). Table B.1 sums up transactions in our experience. Spark Pool and Babel Pool included all private transactions (2 transactions each) sent directly to these minors via Taichi Network.

B.2 Liquidation with ChainLink Oracle Updates

In Aave, out of 1,154 bundles, 994 (86.14%) include an Oracle Chainlink update followed by a liquidation. There are 52 (4.51%) with two Oracle updates followed by liquidations. Out of 1301, Oracle updates grouped with liquidations, 282 (21.68%) are USDC-ETH, 203 (15.60%) are USDT-ETH, 1699%) are DAI -TH, 70 (5.38%) are above and 60 (4.61%) are links. In compound, of 641 bundles, 548 (85.49%) contain an oracle update of the chain, followed by a liquidation, while 39 (6.08%) include two Oracle updates followed by liquidation. Out of 751, the Oracle updates grouped with liquidations, 311 (41.41%) are ETH-USD, 128 (17.04%) are BTC-USD and 53 (7.06%) are uni-USD.

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Table B.1: We have conducted 4 active experiences in Ethereum by simultaneously accelerating private transactions and publicly via the Taichi network. Private transactions were only included by Spark Pool and Babel Pool. If we classify these mining swimming pools according to their chopping rate, they represent 27.72% of the chopping rate of Total Ethereum.

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Figure B.1: Mensual Bitcoin hash rate over the period of 3 years.

B.3 hash lines of mining pools

According to Figure B.1, the hash rates of Bitcoin extraction pools such as BTC.com, F2pool and Antpool alone represented almost half of the total hash rate of the network around May 2018, and approximately a year later, that is to say from March 2019, as well as the pool, the four mining pools represent more than 50% total. At the end of 2020, the new MPOs, for example, Lubian.com and Binance Pool, began to exploit Bitcoin, which contributes to improving the decentralization of Bitcoin. However, BTC.com, F2Pool, Antpool and Poolin still represent almost half of the hash rates showing that some mining pools control a considerable part of the Bitcoin hash.

\ Hash rate of Ethereum operating pools, unlike Bitcoin, do not show a high variance (see Figure B.2). We also observed that Spark Pool, the second largest operating pool in Ethereum, suspended its extraction services on September 30, 2021, due to regulatory requirements in response to the Chinese authorities (Helen Partz, 2021).

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Figure B.2: Weekly rate of Hight Ethereum from September 8, 2021 to June 30, 2022.

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Table B.2: We carry out 10 transaction acceleration experiences in Bitcoin. If we classify minors whose transactions included according to their daily hatching power as (D) and the weekly hash rate power as (W), together, these mining pools correspond to a hash rate power (D: 55.2%; W: 56%).

B.4 Experience of acceleration of the Bitcoin transaction

We have organized an active Bitcoin transaction acceleration experience where we paid EUR 205 in ViabTC (ViabTC, 2022) to accelerate 10 transactions from 10 different snapshots from our Mempool. To select these transactions, we have verified whether the mempool was congestioned (that is to say, having more transactions awaiting inclusion than the following block could include), its size being at least 8 MB. Then we considered only the transactions with low tariff rates – less than or equal to 2 SAT per bytes – to guarantee that these transactions would be very uncomfortable in a subsequent block. Then, we sorted the remaining transactions per size to limit the cost of experience as acceleration service costs increase proportional to the size of transactions. Finally, we select the transaction with the smallest size in bytes for our active experience.

Most of these 10 accelerated transactions were included almost in the following block, demonstrating acceleration efficiency. In addition, these transactions were wrongly positioned in the block: they appeared, for example, at the top of the block, that is to say

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Figure B.3: Active experience vs others: Bitcoin exploitation pools in active experience (that is to say, mining pools that included transactions accelerated by ourselves) increased their hash levels in 2020. Together, they represented more than 55% of the overall hash. The intrigue shows the average weekly percentage of the mining swimming pool over 3 years.

\ That non -accelerated transactions, showing that minors have priority (see Table 4.3). In addition, we have observed that although we only accelerated transactions via ViabTC, other upper mining pools were also involved in the confirmation of accelerated transactions.

\ Table B.2 shows the transactions used in our experiences. At the time we conducted our experience, if we rank the miners whose included these transactions based on their daily hash-rate power as (d) and weekly hash-rate power as (w), we would have Have Huobi (D: 8.1%; W: 9.3%), Binance (D: D: 9.6%; W: 10.3%), f2pool (D: 19.9%; W: 18.7%), Antpool (D: 12.5%; W: 10.6%), viabtc (D: 5.1%; W: 7.1%). Together, these mining pools correspond to a hash rate power (D: 55.2%; W: 56%). Figures B.3 and B.4 show the chopping rate of mining pools in active experience and considering passive experience (deduced to be accelerated by API BTC.com), respectively.

\ In addition, BTC.com (btc.com, 2022), one of the main Bitcoin extraction pools, provides transaction acceleration services and allows users to check whether the transactions have been accelerated via their platform or partner services. From our data set, we have selected those with a SPPE greater than or equal to 1% (12,983,282 transactions in total) and verified if they were considered to be accelerated by the btc.com API. Of these transactions, 14,104 have been accelerated. Our results also show that transactions acceleration services become fairly common among Bitcoin extraction pools (as shown in Figure B.5). Between 2018 and April 2019, only BTC.com and F2Pool alone represented most accelerated transactions. However, in December 2020, we note that BTC.com represents a very small fraction of accelerated transactions, Antpool, Huobi and F2Pool counting most accelerated transactions.

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Figure B.4: Passive + Active Vs other experiences: Bitcoin Mining Pools in active experience (i.e. the operating pools which included transactions accelerated by ourselves) and passive experience (mining pools which included transactions deducted to be accelerated using the BTC.com API) increased their hash rate in the course of 3 years.

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Figure B.5: The graph shows the average monthly percentage of accelerated inclusion of Bitcoin transactions by each mining pool over 3 years. Transactions acceleration services or simply forward as services (FRAA) become popular in all mining pools.