TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Modeling of Distributed Ledgers: Challenges and Future Perspectives

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoIEEE 22nd Conference on Business Informatics (CBI)
KustantajaIEEE
Sivut162-171
Sivumäärä10
ISBN (painettu)9781728199269
DOI - pysyväislinkit
TilaJulkaistu - 22 kesäkuuta 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE Conference on Business Informatics (CBI) -
Kesto: 22 kesäkuuta 202024 kesäkuuta 2020

Julkaisusarja

NimiIEEE Conference on Business Informatics (CBI)
ISSN (elektroninen)2378-1971

Conference

ConferenceIEEE Conference on Business Informatics (CBI)
Ajanjakso22/06/2024/06/20

Tiivistelmä

Interest in applications based on distributed ledger technology (DLT) is on the rise, with corporations worldwide shifting from simply exploring DLT's potential to creating productive business cases. However, despite the existence of numerous DLT applications, developers are still lacking proper tools and instruments for evaluating system behavior (e.g., performance) of their applications on different distributed ledgers before deployment. Since the behavior of such applications is highly dependent on the characteristics of the distributed ledger they are built upon and changing the distributed ledger after deployment of an application is difficult, selecting the wrong ledger can have severe negative consequences. To address the issue, we conducted an extensive literature review to identify and synthesize published modeling and simulation approaches for distributed ledgers. Based on the results, this paper also presents a research agenda to improve modeling of the system behavior of distributed ledgers and to support the development of distributed ledgers and viable DLT applications. In doing so, we facilitate informed decision-making for suitable modeling or simulation approach, which helps application developers to identify a suitable distributed ledger before implementing an application. In addition, our work contributes to science, as we provide a comprehensive overview and analysis of extant simulation and modeling approaches in DLT that accumulates the current state-of-the-art in the rapidly growing DLT field.

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