Title: Efficient variant transaction injection protocols and adaptive policy optimisation for decentralised ledger systems

Authors: Bruno Andriamanalimanana; Chen-Fu Chiang; Jorge Novillo; Sam Sengupta; Ali Tekeoglu

Addresses: Department of Computer and Information Science, State University of New York Polytechnic Institute, Utica, NY 13502, USA ' Department of Computer and Information Science, State University of New York Polytechnic Institute, Utica, NY 13502, USA ' Department of Computer and Information Science, State University of New York Polytechnic Institute, Utica, NY 13502, USA ' Department of Computer and Information Science, State University of New York Polytechnic Institute, Utica, NY 13502, USA ' Department of Computer Science, University of New Brunswick & Canadian Institute for Cybersecurity, Fredericton, NB E3A 9P3, Canada

Abstract: For decentralised cryptocurrency systems, it is important to provide users an efficient network. One performance bottleneck is the latency issue. To address this issue, we provide four protocols to utilise the resources based on the traffic in the network to alleviate the latency in the network. To facilitate the verification process, we discuss three variant injection protocols: Periodic Injection of Transaction via Evaluation Corridor (PITEC), Probabilistic Injection of Transactions (PIT) and Adaptive Semi-synchronous Transaction Inject (ASTI). The injection protocols are variants based on the given assumptions of the network. The goal is to provide dynamic injection of unverified transactions to enhance the performance of the network. The Adaptive Policy Optimisation (APO) protocols aim at optimising a cryptocurrency system's own house policy. The house policy optimisation is translated into a 0/1 knapsack problem. The APO protocol is a fully polynomial time approximation scheme for the decentralised ledger system.

Keywords: blockchain; optimisation; decentralised ledger system architecture.

DOI: 10.1504/IJGUC.2020.110910

International Journal of Grid and Utility Computing, 2020 Vol.11 No.6, pp.847 - 856

Received: 09 Apr 2019
Accepted: 12 Oct 2019
Published online: 01 Nov 2020 *

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