Empirically Analyzing Ethereum's Gas Mechanism

Abstract

Ethereum's Gas mechanism attempts to set transaction fees in accordance with the computational cost of transaction execution: a cost borne by default by every node on the network to ensure correct smart contract execution. Gas encourages users to author transactions that are efficient to execute and in so doing encourages node diversity, allowing modestly resourced nodes to join and contribute to the security of the network.However, the effectiveness of this scheme relies on Gas costs being correctly aligned with observed computational costs in reality. In this work, we performed the first large scale empirical study to understand to what degree this alignment exists in practice, by collecting and analyzing Tera-bytes worth of nanosecond-precision transaction execution traces. Besides confirming potential denial-of-service vectors, our results also shed light on the role of I/O in transaction costs which remains poorly captured by the current Gas cost model. Finally, our results suggest that under the current Gas cost model, nodes with modest computational resources are disadvantaged compared to their better resourced peers, which we identify as an ongoing threat to node diversity and network decentralization.

Systematic Review of Security Vulnerabilities in Ethereum Blockchain Smart Contract

“…It provides a run-time environment that is isolated from the network to execute the smart contract code. Computation in EVM [28] is essentially bounded by transaction fees. Smart contracts contain ethers (a type of cryptocurrency) as their balance.…”

“…Ethers can be sent to other contracts for executing the smart contract. It is a very crucial task because any type of vulnerability can be the reason for the loss of millions of Ether [28]. A smart contract cannot be changed after the deployment [29] on the blockchain due to the immutable [30] nature of the blockchain.…”

Simulating permissionless blockchains: Distribution fitting, tool support, and a case study

“…In the literature there are some proposals that aim to measure the CPU usage for individual operation codes that reside in the EVM. These proposals include OpBench framework 31,32 as well as the work presented in Chen et al, Perez and Livshits, and Yang et al 33–35 Our measurement approach is different from these approaches found in the literature. We measure the CPU usage for smart contracts at the transaction level, while these proposals focus on measuring the CPU usage at the operation code level.…”

Synthesis of Super-Optimized Smart Contracts Using Max-SMT

“…Again, there is not automation and those patterns are manually identified. There is recent work that experimentally proves that the gas model for some EVM instructions is not correctly aligned with respect to the observed computational costs in real experiments [26], and that these misalignments can lead to gas-related attacks [22]. Our work is parametric on the gas model used, and new adjustments in the gas model of Ethereum are integrated in our optimizer by just updating the cost for the corresponding modified instructions in our implementation.…”