Enabling Cost-Effective Blockchain Applications via Workload-Adaptive Transaction Execution_2

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Enabling Cost-Eective Blockchain Applications via

Workload-Adaptive Transaction Execution

A Case Study on Saving Fees for Write-intensive Accounts

Yibo Wang

Syracuse University

Syracuse, New York, USA

ywang349@syr.edu

Yuzhe Tang

Syracuse University

Syracuse, New York, USA

ytang100@syr.edu

Abstract

As transaction fees skyrocket today, blockchains become

increasingly expensive, hurting their adoption in broader

applications.

This work tackles the saving of transaction fees for eco-

nomic blockchain applications. The key insight is that other

than the existing “default” mode to execute application logic

fully on-chain, i.e., in smart contracts, and in ne granular-

ity, i.e., user request per transaction, there are alternative

execution modes with advantages in cost-eectiveness.

On Ethereum, we propose a holistic middleware platform

supporting exible and secure transaction executions, in-

cluding o-chain states and batching of user requests. Fur-

thermore, we propose control-plane schemes to adapt the

execution mode to the current workload for optimal runtime

cost.

We present a case study on the institutional accounts

(e.g., coinbase.com) intensively sending Ether on Ethereum

blockchains. By collecting real-life transactions, we con-

struct workload benchmarks and show that our work saves

18%

∼

47% per invocation than the default baseline while

introducing 1.81 ∼16.59 blocks delay.

Keywords: Blockchains, cost eectiveness

1 Introduction

Ethereum [

] is a blockchain platform that supports smart

contracts. Ethereum charges a very high fee for transaction

execution. One cause of the high fee is that data storage and

processing are replicated to all nodes across a large network.

Another cause is due to the basic principle of economy –

raising user demand in transactions under the limited supply

of block space (i.e., causing more users to bid for a single

block slot). As a result, the Ether price has increased 27 times

in the last two years (as of Mar. 2022). The high fees have

real-world consequence: Ethereum clients are scared away

and are forced to switch to other blockchains.

There are several cost saving schemes on blockchain that

have been studied in the existing literature. iBatch [

] sup-

ports batching multiple smart-contract invocations into one

transaction so that the base fee is amortized. GRuB [

] stores

data o-chain in data-feed workloads and dynamically repli-

cates the data on the blockchain. Layer-two protocols [

–

]

are built on top of the blockchain as extensions. They process

the application logic o-chain to increase throughput and

reduce gas fee. iBatch supports the invocations between any

kinds of accounts, while is limited as it doesn’t support Ether

transferring. GRuB is designed only for data-feed workloads

and doesn’t support Ether transfer as well. Layer-two proto-

cols support Ether transferring with the payment network. It

saves Gas cost only for the transactions between institutional

accounts.

While iBatch is under smart contract workloads and GRuB

is under data feed workloads, it remains an open research

problem: Can one optimize the cost of institutional client

transferring Ether by leveraging batch and o-chain states?

We tackle this problem by presenting OCIA, a blockchain

ptimization s

heme for

nstitutional

ccounts via selec-

tively placing states o the blockchain. OCIA is a control-

plane scheme that maps the upper-layer transaction work-

loads (Ether transfers) to the underlying data plane that ex-

tends blockchains with batch transactions (i.e., iBatch) and

o-chain states (i.e., GRuB). This work extends the workload

to new, more common workloads, that is, Ether transfers

from institutional accounts to average accounts.

We propose an (oine) dynamic optimization algorithm

that decides when to upload the o-chain states to the on-

chain storage (i.e., to convert an o-chain account to on-

chain one) in order to maximize the batch size and minimize

the cost.

We discover the institutional accounts who send the most

transactions in one day Ethereum transaction history. We

then analyzed the transaction history related with 3insti-

tutional accounts as case study workloads including Coin-

base, Ethermine, Crypto.com. The dynamic optimization

algorithm makes one transaction contain more Ether trans-

ferring to amortize the cost while introducing a delay. We

analyze the cost under the workload of write-intensive ac-

counts with the dynamic optimization algorithm. The result

shows OCIA saves 18%

∼

47% per invocation than baseline

while has 1.81 ∼16.59 blocks delay.

arXiv:2210.04644v1 [cs.CR] 7 Oct 2022

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摘要：

EnablingCost-EffectiveBlockchainApplicationsviaWorkload-AdaptiveTransactionExecutionACaseStudyonSavingFeesforWrite-intensiveAccountsYiboWangSyracuseUniversitySyracuse,NewYork,USAywang349@syr.eduYuzheTangSyracuseUniversitySyracuse,NewYork,USAytang100@syr.eduAbstractAstransactionfeesskyrockettoday,blo...

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Enabling Cost-Effective Blockchain Applications via Workload-Adaptive Transaction Execution_2

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