DiPETrans: A framework for distributed parallel execution of transactions of blocks in blockchains

Abstract

Contemporary blockchain such as Bitcoin and Ethereum execute transactions serially by miners and validators and determine the Proof-of-Work (PoW). Such serial execution is unable to exploit modern multi-core resources efficiently, hence limiting the system throughput and increasing the transaction acceptance latency. The objective of this work is to increase the transaction throughput by introducing parallel transaction execution using a static analysis over the transaction dependencies. We propose the DiPETrans framework for distributed execution of transactions in a block. Here, peers in the blockchain network form a community of trusted nodes to execute the transactions and find the PoW in-parallel, using a leader-follower approach. During mining, the leader statically analyzes the transactions, creates different groups (shards) of independent transactions, and distributes them to followers to execute concurrently. After execution, the community's compute power is utilized to solve the PoW concurrently. When a block is successfully created, the leader broadcasts the proposed block to other peers in the network for validation. On receiving a block, the validators re-execute the block transactions and accept the block if they reach the same state as shared by the miner. Validation can also be done in parallel, following the same leader-follower approach as mining. We report experiments using over 5 million real transactions from the Ethereum blockchain and execute them using our DiPETrans framework to empirically validate the benefits of our techniques over a traditional sequential execution. We achieve a maximum speedup of 2.2× and 2.0× and an average speedup of 1.6× and 1.5× for the miner and the validator, respectively, with 100-500 transactions per block when using 6 machines in the community. Further, we achieve a peak of 5× end-to-end block creation speedup using a parallel miner over a serial miner.

FSC: A Fast Smart Contract Transaction Execution Approach via Read-Write Static Analysis

“…Under the existing parallel transaction execution solutions 25,26,27,28,29 which perform static analysis on contracts, if several transactions call the deposit() function in Listing 1, we will find that all these transactions need to be executed serially. The main reason why parallel execution cannot be performed is that the read-write set of each transaction contains writes to the three state variables: currentAmount, goalReached, and isClosed, as shown in Figure 1.…”

“…A promising solution for parallel transaction execution is to perform static analysis, then improve the parallelism according to the analysis results. There are two ways of static analysis, one is to perform static analysis on transaction payload 27 , and another is to perform read-write static analysis on contract source code or bytecode. The grouping granularity of the former is coarse, and it can only be grouped according to the accounts and contracts involved in the transaction.…”

“…However, the dynamic execution scheme may cause most transactions to need to be rolled back and re-executed or transaction failures with high transaction conflict rate 23,24 , resulting in worse performance. A promising method is to perform static analysis on contracts 25,26,27,28,29 . Before transactions are executed in smart contract virtual machine, all transactions in the same block are grouped according to the static analysis results, and transaction groups are dispatched to different computing nodes or threads for execution.…”

Execução Paralela de Transações Baseada em Análise Dinâmica e Auto-Verificável de Conflitos

“…As soluc ¸ões vistas até aqui utilizam paralelismo dentro dos peers através da utilizac ¸ão de arquiteturas multi-cores. Seguindo outra abordagem, Baheti et al [Baheti et al 2022] propuseram uma soluc ¸ão baseada em líder-seguidores que formam um comitê de peers. O líder analisa estaticamente as transac ¸ões, criando diferentes grupos (shards) de transac ¸ões independentes e as distribui aos seguidores para execuc ¸ão concorrente.…”

Fuzzy Logic-Based Mining Strategy for Transaction Congestion Management in Blockchain Networks

“…Another method called DiPETrans (Distributed Parallel Execution of Transactions) was introduced by Baheti et al (11) , which identified the transactions of blocks using the statistical analysis of shards. The mechanism, ever connected to the Blockchain server, enables the leader to perform the tasks of both segmenting blocks and the followers in handling the mining activities.…”