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A performance evaluation of C4M consensus algorithm

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Abstract

Blockchain designed for Mobile Ad hoc Networks (MANETs) and mesh networks is an emerging research topic that has to cope with the network partition problem. However, existing consensus algorithms used in blockchain have been designed to work in a fully connected network with reliable communication. As this assumption does not hold anymore in mobile wireless networks, we describe in this paper the problem of network partitions and their impact on blockchain. Then, we propose a new consensus algorithm called Consensus for Mesh (C4M) which is inspired by RAFT as a solution to this problem. The C4M consensus algorithm is integrated with Blockgraph, a blockchain solution for MANET and mesh networks. We implemented our solution in NS-3 to analyze its performances through simulations. The simulation results gave the first characterization of our algorithm, its performance, and its limits, especially in case of topology changes.

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  1. YOI device — Green Communications: https://www.green-communications.fr/

References

  1. Jiazi Y (2008) A survey on the applications of MANET. Polytech’Nantes, February, 721–726

  2. Alriyami QM, Asimakopoulou, E Bessis, N (2014) A survey of intrusion detection systems for mobile ad hoc networks. In: 2014 International conference on intelligent networking and collaborative systems. pp. 427–432. https://doi.org/10.1109/INCoS.2014.27

  3. Al-Megren S, Alsalamah S, Altoaimy L, Alsalamah H, Soltanisehat L, Almutairi E ‘Sandy’ Pentland A (2018) Blockchain use cases in digital sectors: A review of the literature. In: 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). pp. 1417–1424. https://doi.org/10.1109/Cybermatics_2018.2018.00242

  4. Cordova D, Laube A, Nguyen T-M-T, Pujolle G (2020) Blockgraph: A Blockchain for Mobile Ad hoc Networks. In: 2020 4th cyber security in networking conference (CSNet). pp. 1–8. https://doi.org/10.1109/CSNet50428.2020.9265532

  5. Cordova D, Velloso PB, Laube A, Nguyen T-M-T, Pujolle G (2021) C4M: A partition-robust consensus algorithm for blockgraph in mesh network. In: 2021 5th cyber security in networking conference (CSNet). pp. 82–89. https://doi.org/10.1109/CSNet52717.2021.9614651

  6. Ongaro D, Ousterhout J (2014) In search of an understandable consensus Algorithm. In: 2014 USENIX annual technical conference (Usenix ATC 14). pp 305–319

  7. Fischer MJ (1983) The consensus problem in unreliable distributed systems (a Brief Survey). In: Karpinski M (ed) Foundations of computation theory. Springer, Berlin, pp. 127–140. https://doi.org/10.1007/3-540-12689-9_99

  8. Lamport L (2001) Paxos Made Simple. ACM SIGACT News (Distributed Computing Column) 32, 4 (Whole Number 121, December 2001), 51–58

  9. Castro M, Liskov B (1999) Practical Byzantine fault tolerance. OsDI 99:173–186

    Google Scholar 

  10. Nakamoto S (2008) Bitcoin: A peer-to-peer electronic cash system. Decentralized Bus Rev:21260

  11. Nguyen CT, Hoang DT, Nguyen DN, Niyato D, Nguyen HT, Dutkiewicz E (2019) Proof-of-stake consensus mechanisms for future blockchain networks: Fundamentals, applications and opportunities. IEEE Access 7:85727–85745. https://doi.org/10.1109/ACCESS.2019.2925010

    Article  Google Scholar 

  12. Chen L, Xu L, Shah N, Gao Z, Lu Y, Shi W (2017) On security analysis of proof-of-elapsed-time (PoET). In: Spirakis P, Tsigas P (eds) Stabilization, safety, and security of distributed systems. Springer, Cham, pp 282–297. https://doi.org/10.1007/978-3-319-69084-1_19

  13. Alekeish K, Ezhilchelvan P (2011) Consensus in sparse, mobile ad hoc networks. IEEE Trans Parallel Distrib Syst 23(3):467–474

    Article  Google Scholar 

  14. Liu G, Dong H, Yan Z, Zhou X, Shimizu S (2022) B4SDC: A blockchain system for security data collection in MANETs. IEEE Trans Big Data 8(3):739–752. https://doi.org/10.1109/TBDATA.2020.2981438

    Article  Google Scholar 

  15. Peiris PPC, Rajapakse C, Jayawardena B (2020) Blockchain-based distributed reputation model for ensuring trust in mobile adhoc networks. In: 2020 international research conference on smart computing and systems engineering (SCSE). p 51–56. https://doi.org/10.1109/SCSE49731.2020.9312998

  16. Singh M, Kim S (2018) Branch based blockchain technology in intelligent vehicle. Comput Netw 145:219–231. https://doi.org/10.1016/j.comnet.2018.08.016

    Article  Google Scholar 

  17. Yin B, Mei L, Jiang Z, Wang K (2019) Joint cloud collaboration mechanism between vehicle clouds based on blockchain. In: 2019 IEEE international conference on service-oriented system engineering (SOSE). pp 227–2275 https://doi.org/10.1109/SOSE.2019.00039

  18. Liu H, Lin C-W, Kang E, Shiraishi S, Blough DM (2019) A byzantine-tolerant distributed consensus algorithm for connected vehicles using proof-of-eligibility. In: Proceedings of the 22nd International ACM conference on modeling, analysis and simulation of wireless and mobile systems. Association for Computing Machinery, New York, pp 225–234. https://doi.org/10.1145/3345768.3355910

  19. Javed MU, Rehman M, Javaid N, Aldegheishem A, Alrajeh N, Tahir M (2020) Blockchain-based secure data storage for distributed vehicular networks. Appl Sci 10(6). https://doi.org/10.3390/app10062011

  20. Dong S, Yang H, Yuan J, Jiao L, Yu A, Zhang J (2020) Blockchain-based cross-domain authentication strategy for trusted access to mobile devices in the IoT. In: 2020 international wireless communications and mobile computing (IWCMC). pp 1610–1612. https://doi.org/10.1109/IWCMC48107.2020.9148358

  21. Alvarez Aldana JA, Maag S, Zaidi F (2021) A formal consensus-based distributed monitoring approach for mobile IoT networks. Internet Things 13:100352. https://doi.org/10.1016/j.iot.2020.100352

    Article  Google Scholar 

  22. Jahanian M, Ramakrishnan KK (2022) CoNICE: Consensus in intermittently-connected environments by exploiting naming with application to emergency response, pp 1–14. https://doi.org/10.1109/TNET.2022.3156101

  23. Benchi A, Launay P, Guidec F (2015) Solving consensus in opportunistic networks. In: Proceedings of the 2015 international conference on distributed computing and networking. ICDCN ’15. Association for Computing Machinery, New York. https://doi.org/10.1145/2684464.2684479

  24. Howard H, Schwarzkopf M, Madhavapeddy A, Crowcroft J (2015) Raft Refloated: Do We Have Consensus? SIGOPS Oper Syst Rev 49(1):12–21. https://doi.org/10.1145/2723872.2723876

    Article  Google Scholar 

  25. Howard H, Mortier R (2020) Paxos vs Raft: Have We reached consensus on distributed consensus? PaPoC ’20. Association for Computing Machinery, New York. https://doi.org/10.1145/3380787.3393681

  26. Sakic E, Kellerer W (2018) Response time and availability study of RAFT consensus in distributed SDN control plane. IEEE Trans Netw Serv Manag 15(1):304–318. https://doi.org/10.1109/TNSM.2017.2775061

    Article  Google Scholar 

  27. Fazlali M, Eftekhar SM, Dehshibi MM, Malazi HT, Nosrati M (2019) Raft consensus Algorithm: An effective substitute for paxos in high throughput P2P-based systems. arXiv:1911.01231

  28. Huang D, Ma X, Zhang S (2020) Performance analysis of the raft consensus algorithm for private blockchains. IEEE Trans Syst Man Cybernet Syst 50(1):172–181. https://doi.org/10.1109/TSMC.2019.2895471

    Article  Google Scholar 

  29. Deyerl C, Distler T (2019) In search of a scalable raft-based replication architecture. PaPoC ’19 Association for Computing Machinery, New York. https://doi.org/10.1145/3301419.3323968

  30. Castiglia T, Goldberg C, Patterson S (2020) A hierarchical model for fast distributed consensus in dynamic networks, 1189–1190. https://doi.org/10.1109/ICDCS47774.2020.00137

  31. Morales DC, Velloso P, Guerre A, Nguyen T-M-T, Pujolle G, Alagha K, Dua G (2021) Blockgraph proof-of-concept. In: Proceedings of the SIGCOMM ’21 Poster and Demo Sessions. SIGCOMM ’21. Association for Computing Machinery, New York, pp 82–84. https://doi.org/10.1145/3472716.3472866

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Funding

This work was funded by the French government and is part of the “Blockchain for MESH networks” project with the convention number: 192906025.

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Authors and Affiliations

  1. LIP6 (Laboratoire d’Informatique de Paris 6), Sorbonne Université - CNRS, Paris, 75005, France

    David Cordova Morales, Pedro B. Velloso, Alexandre Laubé & Thi-Mai-Trang Nguyen

  2. Green Communications, Montrouge, 92120, France

    Guy Pujolle

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  1. David Cordova Morales
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  2. Pedro B. Velloso
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  3. Alexandre Laubé
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  4. Thi-Mai-Trang Nguyen
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  5. Guy Pujolle
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Correspondence to David Cordova Morales.

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Morales, D.C., Velloso, P.B., Laubé, A. et al. A performance evaluation of C4M consensus algorithm. Ann. Telecommun. 78, 169–182 (2023). https://doi.org/10.1007/s12243-022-00931-w

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