TangleSim: An Agent-based, Modular Simulator for DAG-based Distributed Ledger Technologies

DAG-based DLTs allow for parallel, asynchronous writing access to a ledger. Consequently, the perception of the most recent blocks may differ considerably between nodes, and the underlying network properties of the P2P layer have a direct impact on the performance of the protocol. Moreover, the stronger inter-dependencies of several core components demand a more complex and complete approach to studying such DLTs. This paper presents an agent-based, open-sourced simulator for large-scale networks that implement the leaderless Tangle 2.0 consensus protocol. Its scope includes modelling the underlying peer-to-peer communication with network topology, package loss, heterogeneous latency, the gossip protocol with reliable broadcast qualities, the underlying DAG-based data structure, and the consensus protocol. The simulator allows us to explore the performance of the protocol in different network environments, as well as different attack scenarios.

[1]  Santiago Ruano Rincón,et al.  Stability of local tip pool sizes , 2023, ArXiv.

[2]  A. Penzkofer,et al.  Robustness of the Tangle 2.0 Consensus , 2022, VALUETOOLS.

[3]  G. Dini,et al.  SegWit Extension and Improvement of the BlockSim Bitcoin Simulator , 2022, 2022 IEEE International Conference on Blockchain (Blockchain).

[4]  E. Solaiman,et al.  Investigating the Requirements for Building a Blockchain Simulator for IoT Applications , 2022, ArXiv.

[5]  E. Solaiman,et al.  Blockchain Simulators: A Systematic Mapping Study , 2022, 2022 IEEE International Conference on Services Computing (SCC).

[6]  A. Penzkofer,et al.  Tangle 2.0 Leaderless Nakamoto Consensus on the Heaviest DAG , 2022, IEEE Access.

[7]  K. Wolter,et al.  CBlockSim: A Modular High-Performance Blockchain Simulator , 2022, 2022 IEEE International Conference on Blockchain and Cryptocurrency (ICBC).

[8]  Olivia Saa,et al.  Impact of delay classes on the data structure in IOTA , 2021, DPM/CBT@ESORICS.

[9]  Ernestas Filatovas,et al.  An Overview and Current Status of Blockchain Simulators , 2021, 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC).

[10]  Aleksandr Ometov,et al.  Blockchain Evaluation Approaches: State-of-the-Art and Future Perspective , 2020, Sensors.

[11]  Qingyi Zhu,et al.  Applications of Distributed Ledger Technologies to the Internet of Things , 2019, ACM Comput. Surv..

[12]  Guy Pujolle,et al.  A Vademecum on Blockchain Technologies: When, Which, and How , 2019, IEEE Communications Surveys & Tutorials.

[13]  Ning Zhang,et al.  A Survey of Distributed Consensus Protocols for Blockchain Networks , 2019, IEEE Communications Surveys & Tutorials.

[14]  Pietro Ferraro,et al.  Distributed Ledger Technology for Smart Mobility: Variable Delay Models , 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

[15]  A. Moorsel,et al.  BlockSim: A Simulation Framework for Blockchain Systems , 2019, SIGMETRICS Perform. Evaluation Rev..

[16]  D. Harz,et al.  DAGsim: Simulation of DAG-based distributed ledger protocols , 2019, IACR Cryptol. ePrint Arch..

[17]  Hans-Arno Jacobsen,et al.  CIDDS: A Configurable and Distributed DAG-based Distributed Ledger Simulation Framework , 2018, Middleware.

[18]  Ghassan O. Karame,et al.  Evaluating User Privacy in Bitcoin , 2013, Financial Cryptography.

[19]  S. Kubler,et al.  BlockPerf: A Hybrid Blockchain Emulator/Simulator Framework , 2021, IEEE Access.

[20]  R. Paulavičius,et al.  A Systematic Review and Empirical Analysis of Blockchain Simulators , 2021, IEEE Access.

[21]  S. Popov The Tangle , 2015 .