PDF
Abstract
The Internet of Things (IoT) has gained substantial attention in both academic research and real-world applications. The proliferation of interconnected devices across various domains promises to deliver intelligent and advanced services. However, this rapid expansion also heightens the vulnerability of the IoT ecosystem to security threats. Consequently, innovative solutions capable of effectively mitigating risks while accommodating the unique constraints of IoT environments are urgently needed. Recently, the convergence of Blockchain technology and IoT has introduced a decentralized and robust framework for securing data and interactions, commonly referred to as the Internet of Blockchained Things (IoBT). Extensive research efforts have been devoted to adapting Blockchain technology to meet the specific requirements of IoT deployments. Within this context, consensus algorithms play a critical role in assessing the feasibility of integrating Blockchain into IoT ecosystems. The adoption of efficient and lightweight consensus mechanisms for block validation has become increasingly essential. This paper presents a comprehensive examination of lightweight, constraint-aware consensus algorithms tailored for IoBT. The study categorizes these consensus mechanisms based on their core operations, the security of the block validation process, the incorporation of AI techniques, and the specific applications they are designed to support.
Keywords
Blockchain
/
Internet of Things
/
Lightweight consensus
Cite this article
Download citation ▾
Somia Sahraoui, Abdelmalik Bachir.
Lightweight consensus mechanisms in the Internet of Blockchained Things: Thorough analysis and research directions✩.
, 2025, 11(4): 1246-1261 DOI:10.1016/j.dcan.2024.12.007
| [1] |
H.-N. Dai, Z. Zheng, Y. Zhang, Blockchain for internet of things: a survey, IEEE Internet Things J. 6 (5) (2019) 8076-8094.
|
| [2] |
A. Hameed, A. Alomary, Security issues in iot: a survey, in: 2019 International Conference on Innovation and Intelligence for Informatics, Computing, and Tech-nologies, 3ICT, IEEE, 2019, pp. 1-5.
|
| [3] |
R. Rudman, R. Bruwer, Defining web 3.0: opportunities and challenges, Electron. Libr. 34 (1) (2016) 132-154.
|
| [4] |
B. Rababah, T. Alam, R. Eskicioglu, The next generation internet of things archi-tecture towards distributed intelligence: reviews, applications, and research chal-lenges, J. Telecommun. Electron.comput. Eng. 12 (2) (2020).
|
| [5] |
M. Di Pierro, What is the blockchain?, Comput. Sci. Eng. 19 (5) (2017) 92-95.
|
| [6] |
Q. He, N. Guan, M. Lv, W. Yi, On the consensus mechanisms of blockchain/dlt for internet of things, in: 2018 IEEE 13th International Symposium on Industrial Embedded Systems, SIES, IEEE, 2018, pp. 1-10.
|
| [7] |
M. Salimitari,M. Chatterjee, A survey on consensus protocols in blockchain for iot networks, arXiv preprint, arXiv:1809.05613.
|
| [8] |
L. Lao, Z. Li, S. Hou, B. Xiao, S. Guo, Y. Yang, A survey of iot applications in blockchain systems: architecture, consensus, and traffic modeling, ACM Comput. Surv. 53 (1) (2020) 1-32.
|
| [9] |
A.M. de Morais, F.A.A. Lins, N.S. Rosa, Survey on integration of consensus mecha-nisms in iot-based blockchains, J. Univers. Comput. Sci. 29 (10) (2023) 1139.
|
| [10] |
M. Nofer, P. Gomber, O. Hinz, D. Schiereck, Blockchain, Bus. Inf. Syst. Eng. 59 (2017) 183-187.
|
| [11] |
M. Wohrer, U. Zdun, Smart contracts: security patterns in the ethereum ecosystem and solidity, in: 2018 International Workshop on Blockchain Oriented Software Engineering, IWBOSE, IEEE, 2018, pp. 2-8.
|
| [12] |
S. Tikhomirov, Ethereum: state of knowledge and research perspectives,in: Foun-dations and Practice of Security: 10th International Symposium, FPS 2017, Nancy, France, October 23-25, 2017, in: Revised Selected Papers, vol. 10, Springer, 2018, pp. 206-221.
|
| [13] |
A. Arooj, M.S. Farooq, T. Umer, Unfolding the blockchain era: timeline, evolution types and real-world applications, J. Netw. Comput. Appl. 207 (2022) 103511.
|
| [14] |
H. Vranken, Sustainability of bitcoin and blockchains, Curr. Opin. Environ. Sustain. 28 (2017) 1-9.
|
| [15] |
S. Ferretti, G. D’Angelo, On the ethereum blockchain structure: a complex networks theory perspective, Concurr.comput. 32 (12) (2020) e5493.
|
| [16] |
S. Pongnumkul, C. Siripanpornchana, S. Thajchayapong, Performance analysis of private blockchain platforms in varying workloads, in: 2017 26th Interna-tional Conference on Computer Communication and Networks, ICCCN, IEEE, 2017, pp. 1-6.
|
| [17] |
O. Dib, K.-L. Brousmiche, A. Durand, E. Thea, E.B. Hamida, Consortium blockchains: overview, applications and challenges, Int. J. Adv. Telecommun. 11 (1) (2018) 51-64.
|
| [18] |
A. Alkhateeb, C. Catal, G. Kar, A. Mishra, Hybrid blockchain platforms for the in-ternet of things (iot): a systematic literature review, Sensors 22 (4) (2022) 1304.
|
| [19] |
M. Alshaikhli, T. Elfouly, O. Elharrouss, A. Mohamed, N. Ottakath, Evolution of internet of things from blockchain to iota: a survey, IEEE Access 10 (2021) 844-866.
|
| [20] |
A.A. Khan, A.A. Laghari, Z.A. Shaikh, Z. Dacko-Pikiewicz, S. Kot, Internet of things (iot) security with blockchain technology: a state-of-the-art review, IEEE Access ( 2022).
|
| [21] |
C. Liang, B. Shanmugam, S. Azam, A. Karim, A. Islam, M. Zamani, S. Kavianpour, N.B. Idris, Intrusion detection system for the internet of things based on blockchain and multi-agent systems, Electronics 9 (7) (2020) 1120.
|
| [22] |
H.B. Patel, D.C. Jinwala, 6mid: mircochain based intrusion detection for 6lowpan based iot networks, Proc.comput. Sci. 184 ( 2021) 929-934.
|
| [23] |
S. Mishra, A.K. Tyagi, Intrusion detection in internet of things (iots) based ap-plications using blockchain technology, in: 2019 Third International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC, IEEE, 2019, pp. 123-128.
|
| [24] |
S.S. Mathew, K. Hayawi, N.A. Dawit, I. Taleb, Z. Trabelsi, Integration of blockchain and collaborative intrusion detection for secure data transactions in industrial iot: a survey, Clust.comput. 25 (6) (2022) 4129-4149.
|
| [25] |
R.F. Mansour, Blockchain assisted clustering with intrusion detection system for industrial internet of things environment, Expert Syst. Appl. 207 (2022) 117995.
|
| [26] |
S. He, W. Ren, T. Zhu, K.-K.R. Choo, Bosmos: a blockchain-based status monitoring system for defending against unauthorized software updating in industrial internet of things, IEEE Internet Things J. 7 (2) (2019) 948-959.
|
| [27] |
S. Mishra, Blockchain-based security in smart grid network, Int. J. Commun. Netw. Distrib. Syst. 28 (4) (2022) 365-388.
|
| [28] |
B. Hu, C. Zhou, Y.-C. Tian, Y. Qin, X. Junping, A collaborative intrusion detec-tion approach using blockchain for multimicrogrid systems, IEEE Trans. Syst. Man Cybern. Syst. 49 (8) (2019) 1720-1730.
|
| [29] |
A.M. Alkhiari, S. Mishra, M. AlShehri, Blockchain-based sqkd and ids in edge en-abled smart grid network, Comput. Mater. Continua 70 (2) (2022).
|
| [30] |
A.Z. Ourad, B. Belgacem, K. Salah, Using blockchain for iot access control and au-thentication management, in: Internet of Things—ICIOT 2018: Third International Conference, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25-30, 2018, in:Proceedings, vol. 3, Springer, 2018, pp. 150-164.
|
| [31] |
D. Li, W. Peng, W. Deng, F. Gai, A blockchain-based authentication and security mechanism for iot, in: 2018 27th International Conference on Computer Commu-nication and Networks, ICCCN, IEEE, 2018, pp. 1-6.
|
| [32] |
U. Khalid, M. Asim, T. Baker, P.C. Hung, M.A. Tariq, L. Rafferty, A decentral-ized lightweight blockchain-based authentication mechanism for iot systems, Clust.comput. 23 (3) (2020) 2067-2087.
|
| [33] |
B. Yu, J.K. Liu, A. Sakzad, S. Nepal, R. Steinfeld, P. Rimba, M.H. Au, Platform-independent secure blockchain-based voting system, in: Information Security: 21st International Conference, ISC 2018, Guildford, UK, September 9-12, 2018, in: Pro-ceedings, vol. 21, Springer, 2018, pp. 369-386.
|
| [34] |
J. Lin, Z. Shen, C. Miao,Using blockchain technology to build trust in sharing lorawan iot, in:Proceedings of the 2nd International Conference on Crowd Science and Engineering, 2017, pp. 38-43.
|
| [35] |
S. Malik, V. Dedeoglu, S.S. Kanhere, R. Jurdak, Trustchain: trust management in blockchain and iot supported supply chains, in: 2019 IEEE International Conference on Blockchain, Blockchain, IEEE, 2019, pp. 184-193.
|
| [36] |
J. Pan, J. McElhannon, Future edge cloud and edge computing for internet of things applications, IEEE Internet Things J. 5 (1) (2017) 439-449.
|
| [37] |
O.I. Khalaf, G.M. Abdulsahib, Optimized dynamic storage of data (odsd) in iot based on blockchain for wireless sensor networks, Peer-to-Peer Netw. Appl. 14 (2021) 2858-2873.
|
| [38] |
G. Wang, Z. Shi, M. Nixon, S. Han, Chainsplitter: towards blockchain-based indus-trial iot architecture for supporting hierarchical storage, in: 2019 IEEE International Conference on Blockchain, Blockchain, IEEE, 2019, pp. 166-175.
|
| [39] |
C. Li, J. Zhang, X. Yang, L. Youlong, Lightweight blockchain consensus mechanism and storage optimization for resource-constrained iot devices, Inf. Process. Manag. 58 (4) (2021) 102602.
|
| [40] |
T. Kim, J. Noh, S. Cho, Scc: storage compression consensus for blockchain in lightweight iot network, in: 2019 IEEE International Conference on Consumer Elec-tronics, ICCE, IEEE, 2019, pp. 1-4.
|
| [41] |
D. Li, Y. Hu, M. Lan, Iot device location information storage system based on blockchain, Future Gener. Comput. Syst. 109 (2020) 95-102.
|
| [42] |
Y. Li, J. Wang, H. Zhang, A survey of state-of-the-art sharding blockchains: models, components, and attack surfaces, J. Netw. Comput. Appl. (2023) 103686.
|
| [43] |
H. Chai, S. Leng, Y. Chen, K. Zhang, A hierarchical blockchain-enabled federated learning algorithm for knowledge sharing in internet of vehicles, IEEE Trans. Intell. Transp. Syst. 22 (7) (2020) 3975-3986.
|
| [44] |
A. Gervais, G.O. Karame, K. Wüst, V. Glykantzis, H. Ritzdorf, S. Capkun,On the security and performance of proof of work blockchains, in:Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, 2016, pp. 3-16.
|
| [45] |
A. Dorri, S.S. Kanhere, R. Jurdak, P. Gauravaram, Lsb: a lightweight scalable blockchain for iot security and anonymity, J. Parallel Distrib. Comput. 134 (2019) 180-197.
|
| [46] |
N. Lasla, L. Al-Sahan, M. Abdallah, M. Younis, Green-pow: an energy-efficient blockchain proof-of-work consensus algorithm, Comput. Netw. 214 (2022) 109118.
|
| [47] |
G. Kumar, R. Saha, M.K. Rai, R. Thomas, T.-H. Kim, Proof-of-work consensus ap-proach in blockchain technology for cloud and fog computing using maximization-factorization statistics, IEEE Internet Things J. 6 (4) (2019) 6835-6842.
|
| [48] |
C.P. Jayabal, P.R. Sathia Bhama, Performance analysis on diversity mining-based proof of work in bifolded consortium blockchain for internet of things consensus, Concurr.comput. 33 (16) (2021) e6285.
|
| [49] |
Q. Qu, R. Xu, Y. Chen, E. Blasch, A. Aved, Enable fair proof-of-work (pow) consensus for blockchains in iot by miner twins (mint), Future Internet 13 (11) (2021) 291.
|
| [50] |
C.T. Nguyen, D.T. Hoang, D.N. Nguyen, D. Niyato, H.T. Nguyen, E. Dutkiewicz, Proof-of-stake consensus mechanisms for future blockchain networks: fundamen-tals, applications and opportunities, IEEE Access 7 (2019) 85727-85745.
|
| [51] |
M. Snider, K. Samani, T. Jain, Delegated proof of stake: features & tradeoffs, Mul-ticoin Cap. 19 (2018) 1-19.
|
| [52] |
S.R. Niya, E. Schiller, I. Cepilov, F. Maddaloni, K. Aydinli, T. Surbeck, T. Bo- cek, B. Stiller, Adaptation of proof-of-stake-based blockchains for iot data streams, in: 2019 IEEE International Conference on Blockchain and Cryptocurrency, ICBC, IEEE, 2019, pp. 15-16.
|
| [53] |
X. Fan, Q. Chai, Roll-dpos: a randomized delegated proof of stake scheme for scal-able blockchain-based internet of things systems,in:Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Network-ing and Services, 2018, pp. 482-484.
|
| [54] |
J. Mišić, V.B. Mišić, X. Chang, Optimal multi-tier clustering of permissioned blockchain systems for iot, IEEE Trans. Veh. Technol. 71 (3) (2022) 2293-2304.
|
| [55] |
X. Tang, X. Lan, L. Li, Y. Zhang, Z. Han, Incentivizing proof-of-stake blockchain for secured data collection in uav-assisted iot: a multi-agent reinforcement learning approach, IEEE J. Sel. Areas Commun. 40 (12) (2022) 3470-3484.
|
| [56] |
S. Hassan, R. Mihalcea, C. Banea, Random walk term weighting for improved text classification, Int. J. Semant. Comput. 1 (04) (2007) 421-439.
|
| [57] |
M. Bhandary, M. Parmar, D. Ambawade, A blockchain solution based on di-rected acyclic graph for iot data security using iota tangle, in: 2020 5th Interna-tional Conference on Communication and Electronics Systems, ICCES, IEEE, 2020, pp. 827-832.
|
| [58] |
B. Shabandri, P. Maheshwari, Enhancing iot security and privacy using distributed ledgers with iota and the tangle, in: 2019 6th International Conference on Signal Processing and Integrated Networks, SPIN, IEEE, 2019, pp. 1069-1075.
|
| [59] |
S. Rochman, J.E. Istiyanto, A. Dharmawan, V. Handika, S.R. Purnama,Optimization of tips selection on the iota tangle for securing blockchain-based iot transactions, Proc.comput. Sci. 216 (2023) 230-236.
|
| [60] |
R. Soltani, L. Saxena, R. Joshi, S. Sampalli,Protecting routing data in wsns with use of iota tangle, Proc.comput. Sci. 203 (2022) 197-204.
|
| [61] |
https://v2.iota.org/, 2023. (Accessed 30 July 2023).
|
| [62] |
M.A. Kumar, V. Radhesyam, B. SrinivasaRao, Front-end iot application for the bit-coin based on proof of elapsed time (poet), in: 2019 Third International Conference on Inventive Systems and Control, ICISC, IEEE, 2019, pp. 646-649.
|
| [63] |
M. Salimitari, M. Chatterjee, Y.P. Fallah, A survey on consensus methods in blockchain for resource-constrained iot networks, Internet of Things 11 (2020) 100212.
|
| [64] |
M.A. Manolache, S. Manolache, N. Tapus,Decision making using the blockchain proof of authority consensus, Proc.comput. Sci. 199 (2022) 580-588.
|
| [65] |
N. Andola, S. Venkatesan, S. Verma, et al., Poewal: a lightweight consensus mech-anism for blockchain in iot, Pervasive Mob. Comput. 69 (2020) 101291.
|
| [66] |
M.U. Zaman, T. Shen, M. Min, Proof of sincerity: a new lightweight consensus approach for mobile blockchains, in: 2019 16th IEEE Annual Consumer Communi-cations & Networking Conference, CCNC, IEEE, 2019, pp. 1-4.
|
| [67] |
Z. Zhang, D. Zhu, W. Fan, Qpbft: practical byzantine fault tolerance consensus al-gorithm based on quantified-role, in: 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom, IEEE, 2020, pp. 991-997.
|
| [68] |
O. Onireti, L. Zhang, M.A. Imran, On the viable area of wireless practical byzantine fault tolerance (pbft) blockchain networks, in: 2019 IEEE Global Communications Conference, GLOBECOM, IEEE, 2019, pp. 1-6.
|
| [69] |
O. Alfandi, S. Otoum, Y. Jararweh,Blockchain solution for iot-based critical in-frastructures: Byzantine fault tolerance, in: NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium, IEEE, 2020, pp. 1-4.
|
| [70] |
R. Zhang, R. Xue, L. Liu, Security and privacy on blockchain, ACM Comput. Surv. 52 (3) (2019) 1-34.
|
| [71] |
F.A. Aponte-Novoa, A.L.S. Orozco, R. Villanueva-Polanco, P. Wightman,The 51% attack on blockchains: a mining behavior study, IEEE Access 9 (2021) 140549-140564.
|
| [72] |
P. Gaži, A. Kiayias, A. Russell, Stake-bleeding attacks on proof-of-stake blockchains, in: 2018 Crypto Valley Conference on Blockchain Technology, CVCBT, IEEE, 2018, pp. 85-92.
|
| [73] |
K.D. Gupta, A. Rahman, S. Poudyal, M.N. Huda, M.P. Mahmud, A hybrid pow-pos implementation against 51 percent attack in cryptocurrency system, in: 2019 IEEE International Conference on Cloud Computing Technology and Science, CloudCom, IEEE, 2019, pp. 396-403.
|
| [74] |
A. Yazdinejad, G. Srivastava, R.M. Parizi, A. Dehghantanha, H. Karimipour, S.R. Karizno,Slpow: secure and low latency proof of work protocol for blockchain in green iot networks, in: 2020 IEEE 91st Vehicular Technology Conference, VTC2020-Spring, IEEE, 2020, pp. 1-5.
|
| [75] |
J. Huang, L. Kong, G. Chen, M.-Y. Wu, X. Liu, P. Zeng, Towards secure industrial iot: blockchain system with credit-based consensus mechanism, IEEE Trans. Ind. Inform. 15 (6) (2019) 3680-3689.
|
| [76] |
W. Li, S. Andreina, J.-M. Bohli, G. Karame, Securing proof-of-stake blockchain protocols, in: Data Privacy Management, Cryptocurrencies and Blockchain Tech-nology: ESORICS 2017 International Workshops, DPM 2017 and CBT DPM 2017 and CBT 2017, Oslo, Norway, September 14-15, 2017, in: Proceedings, Springer, 2017, pp. 297-315.
|
| [77] |
G. Bu, Ö. Gürcan, M. Potop-Butucaru, G-iota: fair and confidence aware tangle, in: IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS, IEEE, 2019, pp. 644-649.
|
| [78] |
G. Bu, W. Hana, M. Potop-Butucaru, E-iota: an efficient and fast metamorphism for iota, in: 2020 2nd Conference on Blockchain Research & Applications for Innovative Networks and Services, BRAINS, IEEE, 2020, pp. 9-16.
|
| [79] |
Q. Bramas, Efficient and secure tsa for the tangle, in: International Conference on Networked Systems, Springer, 2021, pp. 161-166.
|
| [80] |
A. Carelli, A. Palmieri, A. Vilei, F. Castanier, A. Vesco, Enabling secure data ex-change through the iota tangle for iot constrained devices, Sensors 22 (4) (2022) 1384.
|
| [81] |
P. Gangwani, A. Perez-Pons, T. Bhardwaj, H. Upadhyay, S. Joshi, L. Lagos, Securing environmental iot data using masked authentication messaging protocol in a dag-based blockchain: IOTA tangle, Future Internet 13 (12) (2021) 312.
|
| [82] |
Y. Chen, Y. Guo, Y. Wang, R. Bie, Toward prevention of parasite chain attack in iota blockchain networks by using evolutionary game model, Mathematics 10 (7) (2022) 1108.
|
| [83] |
S.A. Kumar, N. Ahmed, A. Bikos, Swiota: anomaly detection for distributed ledger technology-based internet of things (iota) using sliding window (sw) technique,in: IFIP International Internet of Things Conference, Springer, 2022, pp. 177-194.
|
| [84] |
S. Maitra, V.P. Yanambaka, D. Puthal, A. Abdelgawad, K. Yelamarthi, Integration of internet of things and blockchain toward portability and low-energy consumption, Trans. Emerg. Telecommun. Technol. 32 (6) (2021) e4103.
|
| [85] |
E.K. Wang, Z. Liang, C.-M. Chen, S. Kumari, M.K. Khan, Porx: a reputation incentive scheme for blockchain consensus of iiot, Future Gener. Comput. Syst. 102 (2020) 140-151.
|
| [86] |
J. Zou, B. Ye, L. Qu, Y. Wang, M.A. Orgun, L. Li, A proof-of-trust consensus protocol for enhancing accountability in crowdsourcing services, IEEE Trans. Serv.comput. 12 (3) (2018) 429-445.
|
| [87] |
Y. Wu, L. Song, L. Liu, J. Li, X. Li, L. Zhou, Consensus mechanism of iot based on blockchain technology, Shock Vib. 2020 ( 2020) 1-9.
|
| [88] |
F.O. Olowononi, D.B. Rawat, C. Liu, Resilient machine learning for networked cy-ber physical systems: a survey for machine learning security to securing machine learning for cps, IEEE Commun. Surv. Tutor. 23 (1) (2020) 524-552.
|
| [89] |
A. Qayyum, J. Qadir, M. Bilal, A. Al-Fuqaha, Secure and robust machine learning for healthcare: a survey, IEEE Rev. Biomed. Eng. 14 (2020) 156-180.
|
| [90] |
C.L. Stergiou, A.P. Plageras, K.E. Psannis, B.B. Gupta, Secure machine learning scenario from big data in cloud computing via internet of things network, in: Hand-book of Computer Networks and Cyber Security: Principles and Paradigms, 2020, pp. 525-554.
|
| [91] |
F. Bravo-Marquez, S. Reeves, M. Ugarte, Proof-of-learning: a blockchain consensus mechanism based on machine learning competitions, in: 2019 IEEE International Conference on Decentralized Applications and Infrastructures, DAPPCON, IEEE, 2019, pp. 119-124.
|
| [92] |
T. Abhiroop, S. Babu, B. Manoj, A machine learning consensus based light-weight blockchain architecture for internet of things, in: 2022 14th International Confer-ence on COMmunication Systems & NETworkS, COMSNETS, IEEE, 2022, pp. 1-6.
|
| [93] |
K. Saadat, N. Wang, R. Tafazolli, Ai-enabled blockchain consensus node selection in cluster-based vehicular networks, IEEE Netw. Lett. (2023).
|
| [94] |
R. Schmid, B. Pfitzner, J. Beilharz, B. Arnrich, A. Polze, Tangle ledger for decen-tralized learning, in: 2020 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW, IEEE, 2020, pp. 852-859.
|
| [95] |
Y. Zhao, Y. Qu, Y. Xiang, Y. Zhang, L. Gao, A lightweight model-based evolutionary consensus protocol in blockchain as a service for iot, IEEE Trans. Serv.comput. (2023).
|
| [96] |
W. Li, Q. Zhang, S. Deng, B. Zhou, B. Wang, J. Cao, Q-learning improved lightweight consensus algorithm for blockchain-structured internet of things, IEEE Internet Things J. (2023).
|
| [97] |
S. Zhang, J.-H. Lee, Analysis of the main consensus protocols of blockchain, ICT Express 6 (2) (2020) 93-97.
|
| [98] |
U. Tariq, Rampant smoothing (rts) algorithm: an optimized consensus mechanism for private blockchain enabled technologies, EURASIP J. Wirel.commun. Netw. 2022 (1) (2022) 1-22.
|
| [99] |
O. Samuel, A.B. Omojo, S.M. Mohsin, P. Tiwari, D. Gupta, S.S. Band, An anonymous iot-based e-health monitoring system using blockchain technology, IEEE Syst. J. (2022).
|
| [100] |
I. Benkhaddra, A. Kumar, M.A. Setitra, L. Hang, Design and development of consen-sus activation function enabled neural network-based smart healthcare using biot, Wirel. Pers. Commun. 130 (3) (2023) 1549-1574.
|
| [101] |
E.S. Rydningen, E. Åsberg, L. Jaccheri, J. Li, Advantages and opportunities of the iota tangle for health data management: a systematic mapping study,in: Proceed-ings of the 5th International Workshop on Emerging Trends in Software Engineering for Blockchain, 2022, pp. 9-16.
|
| [102] |
J.P. Dias, H. Sereno Ferreira, Â. Martins,A blockchain-based scheme for access control in e-health scenarios, in:Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition, SoCPaR 2018, vol. 10, Springer, 2020, pp. 238-247.
|
| [103] |
R. Zou, X. Lv, J. Zhao, Spchain: blockchain-based medical data sharing and privacy-preserving ehealth system, Inf. Process. Manag. 58 (4) (2021) 102604.
|
| [104] |
M. Arifeen, T. Ghosh, R. Islam, A. Ashiquzzaman, J. Yoon, J. Kim, Autoencoder based consensus mechanism for blockchain-enabled industrial internet of things, Internet of Things 19 (2022) 100575.
|
| [105] |
A. Sasikumar, L. Ravi, K. Kotecha, J.R. Saini, V. Varadarajan, V. Subra- maniyaswamy, Sustainable smart industry: a secure and energy efficient consensus mechanism for artificial intelligence enabled industrial internet of things, Comput. Intell. Neurosci. (2022).
|
| [106] |
M. Kara, A. Laouid, M. Hammoudeh, M. AlShaikh, A. Bounceur, Proof of chance: a lightweight consensus algorithm for the internet of things, IEEE Trans. Ind. Inform. 18 (11) (2022) 8336-8345.
|
| [107] |
A. Sasikumar, N. Senthilkumar, V. Subramaniyaswamy, K. Kotecha, V. Indragandhi, L. Ravi, An efficient, provably-secure dag based consensus mechanism for industrial internet of things, Int. J. Interact. Des. Manuf. (2022) 1-11.
|
| [108] |
L. Cui, S. Yang, Z. Chen, Y. Pan, M. Xu, K. Xu, An efficient and compacted dag-based blockchain protocol for industrial internet of things, IEEE Trans. Ind. Inform. 16 (6) (2019) 4134-4145.
|
| [109] |
Y. Liu, K. Wang, Y. Lin, W. Xu, Lightchain: a lightweight blockchain system for industrial internet of things, IEEE Trans. Ind. Inform. 15 (6) (2019) 3571-3581.
|
| [110] |
G. Leduc, S. Kubler, J.-P. Georges, Innovative blockchain-based farming market-place and smart contract performance evaluation, J. Clean. Prod. 306 (2021) 127055.
|
| [111] |
M.A. Ferrag, L. Shu, X. Yang, A. Derhab, L. Maglaras, Security and privacy for green iot-based agriculture: review, blockchain solutions, and challenges, IEEE Access 8 (2020) 32031-32053.
|
| [112] |
R. Chaganti, V. Varadarajan, V.S. Gorantla, T.R. Gadekallu, V. Ravi, Blockchain-based cloud-enabled security monitoring using internet of things in smart agricul-ture, Future Internet 14 (9) (2022) 250.
|
| [113] |
K. Dey, U. Shekhawat, Blockchain for sustainable e-agriculture: literature review, architecture for data management, and implications, J. Clean. Prod. 316 (2021) 128254.
|
| [114] |
Y. Li, Y. Fan, L. Zhang, J. Crowcroft, Raft consensus reliability in wireless networks: probabilistic analysis, IEEE Internet Things J. ( 2023).
|
| [115] |
A.K. Bapatla, S.P. Mohanty, E. Kougianos, sfarm: a distributed ledger based remote crop monitoring system for smart farming,in: IFIP International Internet of Things Conference, Springer, 2021, pp. 13-31.
|
| [116] |
J. Chen, W. Gan, M. Hu, C.-M. Chen, On the construction of a post-quantum blockchain for smart city, J. Inf. Secur. Appl. 58 (2021) 102780.
|
| [117] |
E. Pournaras, Proof of witness presence: blockchain consensus for augmented democracy in smart cities, J. Parallel Distrib. Comput. 145 (2020) 160-175.
|
| [118] |
M.A. Uddin, A. Stranieri, I. Gondal, V. Balasubramanian, An efficient selec-tive miner consensus protocol in blockchain oriented iot smart monitoring, in: 2019 IEEE International Conference on Industrial Technology, ICIT, IEEE, 2019, pp. 1135-1142.
|
| [119] |
S.V. Sanghami, J.J. Lee, Q. Hu, Machine-learning-enhanced blockchain consensus with transaction prioritization for smart cities, IEEE Internet Things J. 10 (8) (2022) 6661-6672.
|
| [120] |
Z. Zheng, J. Pan, L. Cai, Lightweight blockchain consensus protocols for vehicular social networks, IEEE Trans. Veh. Technol. 69 (6) (2020) 5736-5748.
|
| [121] |
R. Huang, X. Yang, P. Ajay, Consensus mechanism for software-defined blockchain in internet of things, Internet Things Cyber-Phys. Syst. 3 (2023) 52-60.
|
| [122] |
S. Biswas, K. Sharif, F. Li, S. Maharjan, S.P. Mohanty, Y. Wang, Pobt: a lightweight consensus algorithm for scalable iot business blockchain, IEEE Internet Things J. 7 (3) (2019) 2343-2355.
|
| [123] |
A.K. Vishwakarma, H. Zhong, Y.N. Singh, Consensus mechanism for peer-to-peer energy trading, in: Recent Trends in Electronics and Communication: Select Pro-ceedings of VCAS 2020, Springer, 2022, pp. 355-364.
|
| [124] |
S. Chen, H. Mi, J. Ping, Z. Yan, Z. Shen, X. Liu, N. Zhang, Q. Xia, C. Kang, A blockchain consensus mechanism that uses proof of solution to optimize energy dispatch and trading, Nat. Energy 7 (6) (2022) 495-502.
|