Table of Links Abstract and 1. Introduction Abstract and 1. Introduction Related Work


Preliminaries
3.1 TFMs: Desirable Properties
3.2 Groves’ Redistribution Mechanism (RM)


IDEAL-TFRM: Impossibility of Achieving Strictly Positive Redistribution Index


Transaction Fee Redistribution Mechanism (TFRM)


R-TFRM: A TFRM Robust to Miner Manipulation
6.1 R-TFRM: Analyzing Impact of Miner Manipulation on Rebate and Miner Revenue


R2-TFRM: Robust and Rational TFRM


Conclusion and References Related Work Related Work Related Work Preliminaries
3.1 TFMs: Desirable Properties
3.2 Groves’ Redistribution Mechanism (RM) Preliminaries Preliminaries 3.1 TFMs: Desirable Properties 3.1 TFMs: Desirable Properties 3.2 Groves’ Redistribution Mechanism (RM) 3.2 Groves’ Redistribution Mechanism (RM) IDEAL-TFRM: Impossibility of Achieving Strictly Positive Redistribution Index IDEAL-TFRM: Impossibility of Achieving Strictly Positive Redistribution Index IDEAL-TFRM: Impossibility of Achieving Strictly Positive Redistribution Index Transaction Fee Redistribution Mechanism (TFRM) Transaction Fee Redistribution Mechanism (TFRM) Transaction Fee Redistribution Mechanism (TFRM) R-TFRM: A TFRM Robust to Miner Manipulation
6.1 R-TFRM: Analyzing Impact of Miner Manipulation on Rebate and Miner Revenue R-TFRM: A TFRM Robust to Miner Manipulation R-TFRM: A TFRM Robust to Miner Manipulation 6.1 R-TFRM: Analyzing Impact of Miner Manipulation on Rebate and Miner Revenue 6.1 R-TFRM: Analyzing Impact of Miner Manipulation on Rebate and Miner Revenue R2-TFRM: Robust and Rational TFRM R2-TFRM: Robust and Rational TFRM R2-TFRM: Robust and Rational TFRM Conclusion and References Conclusion and References Conclusion and References A. Proofs for Results from Section 4 and 5 A. Proofs for Results from Section 4 and 5 B. Proofs for Results from Section 6 B. Proofs for Results from Section 6 C. Proofs for Results from Section 7 C. Proofs for Results from Section 7 R2-TFRM: ROBUST AND RATIONAL TFRM R2 -TFRM: On-chain Randomness. As stated, each transaction receives a rebate with a probability 𝛼. Similar to other TFMs [8], we employ trusted on-chain randomness for this randomization. Researchers have proposed such trusted randomized protocols using various cryptographic primitives [3, 10]. Significantly, the miner of the block cannot exert any influence on this randomization. R2 -TFRM: On-chain Randomness. Proof Sketch. We divide the proof into two parts. R2 -TFRM: Analyzing Miner Manipulation. Like R-TFRM, R2 - TFRM also ensures strictly positive RRI even with miner manipulation as formally stated in Theorem 7. R2 -TFRM: Analyzing Miner Manipulation. Proof Sketch. The result follows from the similar result in Theorem 5 for R-TFRM and the fact that the miner has no control over the randomization in R2 -TFRM. Discussion on TFRMs. Given that the current TFM literature assumes that users and miners are myopic, we believe that redistributing the surplus is more effective in reducing the net payments paid by the users. Another desirable property in TFMs is that of predictable transaction fees, i.e., reducing the volatility of the fees paid by the users. For instance, EIP-1559 [5] uses a deterministic function based on the previous block consumption to calculate a network-determined minimum threshold fee (called base fee) paid by each user. The users can also pay a priority fee over the base fee to incentivize the miners to include their transactions. The base fee aims to reduce the fee volatility and aims to arrive at a market clearing price. Crucially, this minimum threshold fee is burned – transferred to an unspendable address – implying that the miner does not receive this fee as revenue. We see that burning some fraction of the fee is necessary to guarantee such properties. In such mechanisms, the priority fee calculated post-burning can be further reduced by employing TFRMs. Discussion on TFRMs. base priority burned 8 CONCLUSION In this paper, we argued the importance of minimizing user costs in a TFM. Our key idea is to employ a redistribution mechanism-based approach for determining the transaction fees, which we call the Transaction Fee Redistribution Mechanism (TFRM). Due to strategic miner manipulation, we first show that guaranteeing a strictly positive rebate in a TFRM and other desirable properties is impossible. Hence, we propose R-TFRM, which ensures strictly positive rebates even in the worst case but compromises on miner’s IR. However, we show that in R-TFRM, a strategic miner will never incur negative utility while still guaranteeing strictly positive rebates to the users. We also propose R2 -TFRM which uses blockchain’s inherent randomness to guarantee a strictly positive rebate to the users while also respecting the miner’s IR. Future Work. Future directions can explore TFRMs with randomized rebate functions, which may likely satisfy stronger notions of IC and IR. 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(1) Sankarshan Damle, IIIT, Hyderabad, Hyderbad, India (sankarshan.damle@research.iiit.ac.in);
(2) Manisha Padala, IISc, Bangalore, Bangalore, India (manishap@iisc.ac.in);
(3) Sujit Gujar, IIIT, Hyderabad, Hyderbad, India (sujit.gujar@iiit.ac.in). Authors: Authors: (1) Sankarshan Damle, IIIT, Hyderabad, Hyderbad, India (sankarshan.damle@research.iiit.ac.in); (2) Manisha Padala, IISc, Bangalore, Bangalore, India (manishap@iisc.ac.in); (3) Sujit Gujar, IIIT, Hyderabad, Hyderbad, India (sujit.gujar@iiit.ac.in). This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv

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Reducing Blockchain Fees with R2-TFRM and On-Chain Randomness

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