Title: Transaction sampling algorithms for real-time crypto block dependability

Authors: Abhilash Kancharla; Hyeyoung Kim; Nohpill Park

Addresses: Computer Science Department, Oklahoma State University, Stillwater, OK, 74078, USA ' School of Games, Hongik University, South Korea ' Computer Science Department, Oklahoma State University, Stillwater, OK, 74078, USA

Abstract: This paper presents various transaction sampling algorithms for the proposed real-time crypto computing, and analytical model to assure their dependability under stringent real-time requirement. Efficacy of the algorithms is assessed in terms of the block dependability that expresses the probability for the pending transactions to be posted within the current or the target block delay. Algorithms on prioritising and sampling transactions from pool, to facilitate execution of those transactions within their deadline requirements, such as normal, random, sorted, and stratified, are proposed and simulated. Performance variables such as the number of pending transactions, average speed, gas fees, deadlines, number of miners, are identified and taken into the block dependability in order to reveal the influence of those variables. Extensive parametric simulation results are presented and discussed in the cases of the random and sorted transaction sampling algorithms along with a prototype built based on the Ethereum open source.

Keywords: blockchain; Ethereum; real-time; dependability; crypto computing.

DOI: 10.1504/IJBDI.2020.109671

International Journal of Big Data Intelligence, 2020 Vol.7 No.3, pp.127 - 136

Received: 31 Mar 2020
Accepted: 28 May 2020

Published online: 10 Sep 2020 *

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