Transaction sampling algorithms for real-time crypto block dependability
by Abhilash Kancharla; Hyeyoung Kim; Nohpill Park
International Journal of Big Data Intelligence (IJBDI), Vol. 7, No. 3, 2020

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.

Online publication date: Fri, 18-Sep-2020

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