Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
41 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
41 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Enabling Technologies for Web 3.0: A Comprehensive Survey (2401.10901v1)

Published 29 Dec 2023 in cs.CY

Abstract: Web 3.0 represents the next stage of Internet evolution, aiming to empower users with increased autonomy, efficiency, quality, security, and privacy. This evolution can potentially democratize content access by utilizing the latest developments in enabling technologies. In this paper, we conduct an in-depth survey of enabling technologies in the context of Web 3.0, such as blockchain, semantic web, 3D interactive web, Metaverse, Virtual reality/Augmented reality, Internet of Things technology, and their roles in shaping Web 3.0. We commence by providing a comprehensive background of Web 3.0, including its concept, basic architecture, potential applications, and industry adoption. Subsequently, we examine recent breakthroughs in IoT, 5G, and blockchain technologies that are pivotal to Web 3.0 development. Following that, other enabling technologies, including AI, semantic web, and 3D interactive web, are discussed. Utilizing these technologies can effectively address the critical challenges in realizing Web 3.0, such as ensuring decentralized identity, platform interoperability, data transparency, reducing latency, and enhancing the system's scalability. Finally, we highlight significant challenges associated with Web 3.0 implementation, emphasizing potential solutions and providing insights into future research directions in this field.

PDF HTML Abstract
Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Bookmark Chat Bubble Oval Streamline Icon: https://streamlinehq.com Chat (Pro)
Definition Search Book Streamline Icon: https://streamlinehq.com
References (171)
  1. History of the web. [Online]. Available: https://webfoundation.org/about/vision/history-of-the-web/.
  2. S. Salim, B. Turnbull, and N. Moustafa, “A blockchain-enabled explainable federated learning for securing internet-of-things-based social media 3.0 networks,” IEEE Transactions on Computational Social Systems, pp. 1–17, Dec. 2021.
  3. K. Korkmaz, J. Bruneau-Queyreix, S. B. Mokhtar, and L. Reveillere, “ALDER: Unlocking blockchain performance by multiplexing consensus protocols,” in Proc. IEEE 21st International Symposium on Network Computing and Applications (NCA), vol. 21, Jan. 2022, pp. 9–18.
  4. W.-Y. Lin, X. Zhang, H. Song, and K. Omori, “Health information seeking in the Web 2.0 age: Trust in social media, uncertainty reduction, and self-disclosure,” Computers in Human Behavior, vol. 56, pp. 289–294, Mar. 2016.
  5. B. Stritter, F. Freiling, H. König, R. Rietz, S. Ullrich, A. von Gernler, F. Erlacher, and F. Dressler, “Cleaning up web 2.0’s security mess-at least partly,” IEEE Security & Privacy, vol. 14, no. 2, pp. 48–57, Apr. 2016.
  6. Y.-J. Liu, H. Du, D. Niyato, G. Feng, J. Kang, and Z. Xiong, “Slicing4Meta: An Intelligent Integration Architecture with Multi-dimensional Network Resources for Metaverse-as-a-Service in Web 3.0,” IEEE Communications Magazine, vol. 61, no. 8, pp. 438–449, Aug. 2023.
  7. F. Bashir and N. F. Warraich, “Systematic literature review of semantic web for distance learning,” Interactive Learning Environments, vol. 31, no. 1, pp. 527–543, Aug. 2023.
  8. C. Chen, L. Zhang, Y. Li, T. Liao, S. Zhao, Z. Zheng, H. Huang, and J. Wu, “When digital economy meets Web 3.0: Applications and challenges,” IEEE Open Journal of the Computer Society, vol. 3, pp. 233–245, Oct. 2022.
  9. J. Zarrin, H. Wen Phang, L. Babu Saheer, and B. Zarrin, “Blockchain for decentralization of Internet: prospects, trends, and challenges,” Cluster Computing, vol. 24, no. 4, pp. 2841–2866, May, 2021.
  10. X. Ren, M. Xu, D. Niyato, J. Kang, Z. Xiong, C. Qiu, and X. Wang, “Building Resilient Web 3.0 with Quantum Information Technologies and Blockchain: An Ambilateral View,” arXiv:2303.13050, Mar. 2023.
  11. P. P. Ray, “Web3: A comprehensive review on background, technologies, applications, zero-trust architectures, challenges and future directions,” Internet of Things and Cyber-Physical Systems, pp. 213–248, May, 2023.
  12. O. Adedugbe, E. Benkhelifa, R. Campion, F. Al-Obeidat, A. Bani Hani, and U. Jayawickrama, “Leveraging cloud computing for the semantic web: Review and trends,” Soft Computing, vol. 24, pp. 5999–6014, Nov. 2020.
  13. P. Drakatos, E. Demetriou, S. Koumou, A. Konstantinidis, and D. Zeinalipour-Yazti, “Triastore: A Web 3.0 blockchain datastore for massive IoT workloads,” in Proc. 2021 22nd IEEE International Conference on Mobile Data Management (MDM), 2021, pp. 187–192.
  14. S. Tanwar, “Blockchain revolution from 1.0 to 5.0: technological perspective,” in Blockchain Technology: From Theory to Practice.   Singapore, Springer, 2022, pp. 43–61.
  15. W. Zhao, C. Jiang, H. Gao, S. Yang, and X. Luo, “Blockchain-enabled cyber-physical systems: A Review,” IEEE Internet of Things Journal, vol. 8, no. 6, pp. 4023–4034, Mar. 2020.
  16. X. Zhang, G. Min, T. Li, Z. Ma, X. Cao, and S. Wang, “AI and Blockchain Empowered Metaverse for Web 3.0: Vision, Architecture, and Future Directions,” IEEE Communications Magazine, vol. 61, no. 8, pp. 60–66, Jun. 2023.
  17. D. Chen, L. J. Xie, B. Kim, L. Wang, C. S. Hong, L.-C. Wang, and Z. Han, “Federated learning based mobile edge computing for augmented reality applications,” in Proc. 2020 International Conference on Computing, Networking and Communications (ICNC), 2020, pp. 767–773.
  18. R. Gupta. (2022) An introduction to terminologies and layers in web3. [Online]. Available: https://techblog.geekyants.com/an-introduction-to-terminologies-and-layers-in-web3/.
  19. B. Lashkari and P. Musilek, “A comprehensive review of blockchain consensus mechanisms,” IEEE Access, vol. 9, pp. 43 620–43 652, Mar. 2021.
  20. C. T. Nguyen, D. T. Hoang, D. N. Nguyen, D. Niyato, H. T. Nguyen, and E. Dutkiewicz, “Proof-of-stake consensus mechanisms for future blockchain networks: Fundamentals, applications and opportunities,” IEEE Access, vol. 7, pp. 85 727–85 745, Jun. 2019.
  21. S. P. Choudary. (2021) Understanding the incentives for web3. [Online]. Available: https://medium.com/bosonprotocol/understanding-the-incentives-for-web3-ca15ec6b30f7/.
  22. S. Salim, B. Turnbull, and N. Moustafa, “Data analytics of social media 3.0: Privacy protection perspectives for integrating social media and Internet of Things (SM-IoT) systems,” Ad Hoc Networks, vol. 128, pp. 102 786–102 801, Apr. 2022.
  23. X. Liu, Z. Tang, P. Li, S. Guo, X. Fan, and J. Zhang, “A graph learning based approach for identity inference in Dapp platform blockchain,” IEEE Transactions on Emerging Topics in Computing, vol. 10, no. 1, pp. 438–449, Sep. 2020.
  24. K. Yue, Y. Zhang, Y. Chen, Y. Li, L. Zhao, C. Rong, and L. Chen, “A survey of decentralizing applications via blockchain: The 5G and beyond perspective,” IEEE Communications Surveys & Tutorials, vol. 23, no. 4, pp. 2191–2217, Sep. 2021.
  25. G. Weston. (2022) Blockchain for Decentralized Finance (DeFi). [Online]. Available: https://101blockchains.com/web3-guide/.
  26. A. Takyar. (2022) All about web3 gaming. [Online]. Available: https://www.leewayhertz.com/what-is-web3-gaming/.
  27. E. Chondrogiannis, V. Andronikou, E. Karanastasis, A. Litke, and T. Varvarigou, “Using blockchain and semantic web technologies for the implementation of smart contracts between individuals and health insurance organizations,” Blockchain: Research and Applications, vol. 3, no. 2, pp. 100 049–100 063, Dec. 2022.
  28. A. Rungta. (2022) How web 3.0 might revolutionize healthcare. [Online]. Available: https://www.forbes.com/sites/forbesbusinesscouncil/2022/05/23/how-web-30-might-revolutionize-healthcare/?sh=58386429322e/.
  29. H. Li and D. Han, “Edurss: A blockchain-based educational records secure storage and sharing scheme,” IEEE Access, vol. 7, pp. 179 273–179 289, Nov. 2019.
  30. S. T. Siddiqui, M. O. Ahmad, M. Khamruddin, A. K. Gupta, and A. K. Singha, “Blockchain and iot for educational certificates generation and verification,” in Proc. of the 2022 2nd International Conference on Computing and Information Technology (ICCIT), 2022, pp. 298–303.
  31. U. Marjit and P. Kumar, “Towards a decentralized and distributed framework for open educational resources based on IPFS and blockchain,” in Proc. 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), Mar. 2020, pp. 1–6.
  32. L. Cao, “Decentralized AI: Edge intelligence and smart blockchain, Metaverse, Web3, and DeSci,” IEEE Intelligent Systems, vol. 37, no. 3, pp. 6–19, May-Jun. 2022.
  33. S. Wang, W. Ding, J. Li, Y. Yuan, L. Ouyang, and F.-Y. Wang, “Decentralized autonomous organizations: Concept, model, and applications,” IEEE Transactions on Computational Social Systems, vol. 6, no. 5, pp. 870–878, Sep. 2019.
  34. W. Ding, J. Hou, J. Li, C. Guo, J. Qin, R. Kozma, and F.-Y. Wang, “DeSci based on Web3 and DAO: A comprehensive overview and reference model,” IEEE Transactions on Computational Social Systems, vol. 9, no. 5, pp. 1563–1573, Sep. 2022.
  35. Q. Wang, R. Li, Q. Wang, and S. Chen, “Non-fungible token (NFT): Overview, evaluation, opportunities and challenges,” arXiv:2105.07447, Oct. 2021.
  36. A. Murray, D. Kim, and J. Combs, “The promise of a decentralized internet: What is Web3 and how can firms prepare?” Business Horizons, vol. 66, no. 2, pp. 191–202, Mar. 2023.
  37. F. M. Benvcic, P. Skovcir, and I. P. Zarko, “DL-Tags: DLT and smart tags for decentralized, privacy-preserving, and verifiable supply chain management,” IEEE Access, vol. 7, pp. 46 198–46 209, Apr. 2019.
  38. Y. Kayikci and N. Subramanian, “Blockchain interoperability issues in supply chain: Exploration of mass adoption procedures,” in Big Data and Blockchain for Service Operations Management, Studies in Big Data, Springer, 2022, pp. 309–328.
  39. T. Wang, S. Zhang, and S. C. Liew, “Linking Souls to Humans with ZKBID: Accountable Anonymous Blockchain Accounts for Web 3.0 Decentralized Identity,” arXiv:2301.02102, Jan. 2023.
  40. O. Avellaneda, A. Bachmann, A. Barbir, J. Brenan, P. Dingle, K. H. Duffy, E. Maler, D. Reed, and M. Sporny, “Decentralized identity: Where did it come from and where is it going?” IEEE Communications Standards Magazine, vol. 3, no. 4, pp. 10–13, Dec. 2019.
  41. S. Cucko and M. Turkanovic, “Decentralized and self-sovereign identity: Systematic mapping study,” IEEE Access, vol. 9, pp. 139 009–139 027, Oct. 2021.
  42. D. T. Hoang, D. N. Nguyen, C. T. Nguyen, E. Hossain, and D. Niyato, “Metaverse Communication and Computing Networks: Applications, Technologies, and Approaches,” IEEE-Wiley, 2023.
  43. Consensys. (2023) A detailed guide on web 3.0. [Online]. Available: https://consensys.net/blockchain-use-cases/decentralized-finance/.
  44. IPFS. (2023) What is IPFS. [Online]. Available: https://docs.ipfs.tech/concepts/what-is-ipfs/#what-ipfs-isn-t/.
  45. Ericsson. IoT connections forecast - Mobility Report. [Online]. Available: https://www.ericsson.com/en/reports-and-papers/mobility-report/dataforecasts/iot-connections-outlook/.
  46. X. Wang, J. Yang, J. Han, W. Wang, and F.-Y. Wang, “Metaverses and DeMetaverses: From digital twins in CPS to parallel intelligence in CPSS,” IEEE Intelligent Systems, vol. 37, no. 4, pp. 97–102, Sep. 2022.
  47. O. Novo and M. D. Francesco, “Semantic interoperability in the IoT: extending the web of things architecture,” ACM Transactions on Internet of Things, vol. 1, no. 1, pp. 1–25, Mar. 2020.
  48. P. Patel, M. I. Ali, and A. Sheth, “From raw data to smart manufacturing: AI and semantic web of things for industry 4.0,” IEEE Intelligent Systems, vol. 33, no. 4, pp. 79–86, Oct. 2018.
  49. W. Group. Web of things (wot) architecture. [Online]. Available: https://w3c.github.io/wot-architecture/.
  50. H. Jethva. JSON A Brief Background. [Online]. Available: https://www.alibabacloud.com/blog/basics-of-working-with-json-in-sql-server_597409.
  51. M. Tao, J. Zuo, Z. Liu, A. Castiglione, and F. Palmieri, “Multi-layer cloud architectural model and ontology-based security service framework for iot-based smart homes,” Future Generation Computer Systems, vol. 78, pp. 1040–1051, Jan. 2018.
  52. M. A. Rahman, M. S. Hossain, M. S. Islam, N. A. Alrajeh, and G. Muhammad, “Secure and provenance enhanced Internet of health things framework: A blockchain managed federated learning approach,” IEEE Access, vol. 8, pp. 205 071–205 087, Nov. 2020.
  53. S. Saxena, B. Bhushan, and M. A. Ahad, “Blockchain based solutions to secure IoT: Background, integration trends and a way forward,” Journal of Network and Computer Applications, vol. 181, p. 103050, May, 2021.
  54. B. Farahani, F. Firouzi, and M. Luecking, “The convergence of IoT and distributed ledger technologies (DLT): Opportunities, challenges, and solutions,” Journal of Network and Computer Applications, vol. 177, p. 102936, Mar. 2021.
  55. T. L. Koreshoff, T. W. Leong, and T. Robertson, “Approaching a human-centred internet of things,” in Proc. of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, 2013, pp. 363–366.
  56. S. M. Oteafy and H. S. Hassanein, “Iot in the fog: A roadmap for data-centric iot development,” IEEE Communications Magazine, vol. 56, no. 3, pp. 157–163, Mar. 2018.
  57. Q. Wu, G. Ding, Y. Xu, S. Feng, Z. Du, J. Wang, and K. Long, “Cognitive Internet of Things: a new paradigm beyond connection,” IEEE Internet of Things Journal, vol. 1, no. 2, pp. 129–143, Mar. 2014.
  58. M. Yannuzzi, R. Milito, R. Serral-Gracià, D. Montero, and M. Nemirovsky, “Key ingredients in an iot recipe: Fog computing, cloud computing, and more fog computing,” in Proc. 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2014, pp. 325–329.
  59. S. Wang, L. Ouyang, Y. Yuan, X. Ni, X. Han, and F.-Y. Wang, “Blockchain-enabled smart contracts: architecture, applications, and future trends,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 11, pp. 2266–2277, Feb. 2019.
  60. T. M. Fernández-Caramés and P. Fraga-Lamas, “A review on the use of blockchain for the internet of things,” IEEE Access, vol. 6, pp. 32 979–33 001, May, 2018.
  61. G. Hatzivasilis, I. Askoxylakis, G. Alexandris, D. Anicic, A. Broring, V. Kulkarni, K. Fysarakis, and G. Spanoudakis, “The Interoperability of Things: Interoperable solutions as an enabler for IoT and Web 3.0,” in Proc. 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), Nov. 2018, pp. 1–7.
  62. World Wide Web Consortium (W3C). (2006) Linked data. [Online]. Available: https://www.w3.org/DesignIssues/LinkedData.html/.
  63. V. Shevchuk. (2008) Unified architecture. [Online]. Available: https://opcfoundation.org/about/opc-technologies/opc-ua/.
  64. S. Ferber. (2012) Production performance management. [Online]. Available: https://iot.eclipse.org/adopters/testbeds/production-performance-management/.
  65. C. Choi and J. Choi, “Ontology-based security context reasoning for power IoT-cloud security service,” IEEE Access, vol. 7, pp. 110 510–110 517, Aug. 2019.
  66. B. A. Mozzaquatro, C. Agostinho, D. Goncalves, J. Martins, and R. Jardim-Goncalves, “An ontology-based cybersecurity framework for the Internet of Things,” Sensors, vol. 18, no. 9, p. 3053, Sep. 2018.
  67. M. Gheisari, H. E. Najafabadi, J. A. Alzubi, J. Gao, G. Wang, A. A. Abbasi, and A. Castiglione, “OBPP: An ontology-based framework for privacy-preserving in IoT-based smart city,” Future Generation Computer Systems, vol. 123, pp. 1–13, Oct. 2021.
  68. I. Szilagyi and P. Wira, “Ontologies and semantic web for the internet of things-a survey,” in Proc. IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society, 2016, pp. 6949–6954.
  69. Ericsson. 5G network coverage outlook-Mobility Report. [Online]. Available: https://www.ericsson.com/en/reports-and-papers/mobility-report/dataforecasts/network-coverage/.
  70. X. Lin and N. Lee, “Introduction to 5G and Beyond,” 5G and Beyond: Fundamentals and Standards, pp. 1–25, Aug. 2021.
  71. A. Weissberger, “IMT vision–Framework and overall objectives of the future development of IMT for 2020 and beyond,” Recommendation ITU, vol. 2083, no. 0, Jan. 2015.
  72. 3GPP. (2022) System architecture for the 5G system (5GS), 3GPP TS23.501. [Online]. Available: https://2020.standict.eu/standards-watch/system-architecture-5g-system/.
  73. L. Chettri and R. Bera, “A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems,” IEEE Internet of Things Journal, vol. 7, no. 1, pp. 16–32, Oct. 2019.
  74. S. Hakak, T. R. Gadekallu, P. K. R. Maddikunta, S. P. Ramu, P. M, C. De Alwis, and M. Liyanage, “Autonomous vehicles in 5G and beyond: A survey,” Vehicular Communications, vol. 39, pp. 100 551–100 582, Feb. 2023.
  75. N. Abbas, Y. Zhang, A. Taherkordi, and T. Skeie, “Mobile edge computing: A survey,” IEEE Internet of Things Journal, vol. 5, no. 1, pp. 450–465, Sep. 2018.
  76. Y. Siriwardhana, P. Porambage, M. Liyanage, and M. Ylianttila, “A survey on mobile augmented reality with 5G mobile edge computing: Architectures, applications, and technical aspects,” IEEE Communications Surveys & Tutorials, vol. 23, no. 2, pp. 1160–1192, Feb. 2021.
  77. I. Ahmed, H. Khammari, A. Shahid, A. Musa, K. S. Kim, E. De Poorter, and I. Moerman, “A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives,” IEEE Communications Surveys and Tutorials, vol. 20, no. 4, pp. 3060–3097, Jun. 2018.
  78. M. Mezzavilla, M. Zhang, M. Polese, R. Ford, S. Dutta, S. Rangan, and M. Zorzi, “End-to-end simulation of 5G mmWave networks,” IEEE Communications Surveys & Tutorials, vol. 20, no. 3, pp. 2237–2263, Apr. 2018.
  79. T. S. Rappaport, G. R. MacCartney, M. K. Samimi, and S. Sun, “Wideband millimeter-wave propagation measurements and channel models for future wireless communication system design,” IEEE Transactions on Communications, vol. 63, no. 9, pp. 3029–3056, May, 2015.
  80. Y. Cheng and M. Pesavento, “Joint optimization of source power allocation and distributed relay beamforming in multiuser peer-to-peer relay networks,” IEEE Transactions on Signal Processing, vol. 60, no. 6, pp. 2962–2973, Feb. 2012.
  81. Q. Wang, P. Wang, W. Sun, and Y. Zhang, “Low-Latency Communications for Digital Twin Empowered Web 3.0,” IEEE Network, Early Access, doi: 10.1109/MNET.2023.3319380, Oct. 2023.
  82. A.-S. Bana, E. de Carvalho, B. Soret, T. Abrao, J. C. Marinello, E. G. Larsson, and P. Popovski, “Massive MIMO for Internet of Things (IoT) connectivity,” Physical Communication, vol. 37, pp. 100 859–100 866, Dec. 2019.
  83. N. H. Chu, D. T. Hoang, D. N. Nguyen, K. T. Phan, E. Dutkiewicz, D. Niyato, and T. Shu, “Metaslicing: A novel resource allocation framework for metaverse,” IEEE Transactions on Mobile Computing, pp. 1–18, 2023.
  84. P. Fang and T. Wolf, “Implementing Virtual Network Functions in Named Data Networking and Web 3.0,” in Proc. 2023 International Conference on Computing, Networking and Communications (ICNC), 2023, pp. 117–123.
  85. X. Luo, H.-H. Chen, and Q. Guo, “Semantic communications: Overview, open issues, and future research directions,” IEEE Wireless Communications, vol. 29, no. 1, pp. 210–219, Jan. 2022.
  86. H. Ning, H. Wang, Y. Lin, W. Wang, S. Dhelim, F. Farha, J. Ding, and M. Daneshmand, “A survey on the metaverse: The state-of-the-art, technologies, applications, and challenges,” IEEE Internet of Things Journal, vol. 10, no. 16, pp. 14 671–14 688, Aug. 2023.
  87. H. Xie, Z. Qin, G. Y. Li, and B.-H. Juang, “Deep learning enabled semantic communication systems,” IEEE Transactions on Signal Processing, vol. 69, pp. 2663–2675, Apr. 2021.
  88. J. Wang, H. Du, Z. Tian, D. Niyato, J. Kang, and X. Shen, “Semantic-aware sensing information transmission for metaverse: A contest theoretic approach,” IEEE Transactions on Wireless Communications, vol. 22, no. 8, pp. 5214–5228, Jan. 2023.
  89. N. C. Luong, T. L. Van, S. Feng, H. Du, D. Niyato, and D. I. Kim, “Edge computing for metaverse: Incentive mechanism versus semantic communication,” IEEE Transactions on Mobile Computing, pp. 1–17, 2023.
  90. W. H. Hassan et al., “Current research on Internet of Things (IoT) security: A survey,” Computer Networks, vol. 148, pp. 283–294, Jan. 2019.
  91. Y. Wang, Z. Su, N. Zhang, R. Xing, D. Liu, T. H. Luan, and X. Shen, “A survey on metaverse: Fundamentals, security, and privacy,” IEEE Communications Surveys and Tutorials, vol. 25, no. 1, pp. 319–352, Jan. 2023.
  92. Z. Liu, X. Xu, F. Han, Q. Zhao, L. Qi, W. Dou, and X. Zhou, “Secure Edge Server Placement with Non-Cooperative Game for Internet of Vehicles in Web 3.0,” IEEE Transactions on Network Science and Engineering, Early Access, pp. 1–12, Oct. 2023.
  93. F. A. Sunny, P. Hajek, M. Munk, M. Z. Abedin, M. S. Satu, M. I. A. Efat, and M. J. Islam, “A systematic review of blockchain applications,” IEEE Access, vol. 10, pp. 59 155–59 177, Jun. 2022.
  94. J. Al-Jaroodi and N. Mohamed, “Blockchain in industries: A survey,” IEEE Access, vol. 7, pp. 36 500–36 515, Mar. 2019.
  95. C. Fan, S. Ghaemi, H. Khazaei, and P. Musilek, “Performance evaluation of blockchain systems: A systematic survey,” IEEE Access, vol. 8, pp. 126 927–126 950, Jun. 2020.
  96. F. Casino, T. K. Dasaklis, and C. Patsakis, “A systematic literature review of blockchain-based applications: Current status, classification and open issues,” Telematics and Informatics, vol. 36, pp. 55–81, Mar. 2019.
  97. R. Yang, F. R. Yu, P. Si, Z. Yang, and Y. Zhang, “Integrated blockchain and edge computing systems: A survey, some research issues and challenges,” IEEE Communications Surveys & Tutorials, vol. 21, no. 2, pp. 1508–1532, Jan. 2019.
  98. H. Zhou, Z. Shi, X. Ouyang, and Z. Zhao, “Building a blockchain-based decentralized ecosystem for cloud and edge computing: an allstar approach and empirical study,” Peer-to-Peer Networking and Applications, vol. 14, no. 6, pp. 3578–3594, Jun. 2021.
  99. M. I. Khalid, I. Ehsan, A. K. Al-Ani, J. Iqbal, S. Hussain, S. S. Ullah et al., “A comprehensive survey on blockchain-based decentralized storage networks,” IEEE Access, vol. 11, pp. 10 995–11 015, Jan. 2023.
  100. A. A. Monrat, O. Schelen, and K. Andersson, “A survey of blockchain from the perspectives of applications, challenges, and opportunities,” IEEE Access, vol. 7, pp. 117 134–117 151, Aug. 2019.
  101. K. Gai, Y. Wu, L. Zhu, L. Xu, and Y. Zhang, “Permissioned blockchain and edge computing empowered privacy-preserving smart grid networks,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 7992–8004, Mar. 2019.
  102. Z. Guan, G. Si, X. Zhang, L. Wu, N. Guizani, X. Du, and Y. Ma, “Privacy-preserving and efficient aggregation based on blockchain for power grid communications in smart communities,” IEEE Communications Magazine, vol. 56, no. 7, pp. 82–88, Jul. 2018.
  103. C. T. Nguyen, D. T. Hoang, D. N. Nguyen, Y. Xiao, H.-A. Pham, E. Dutkiewicz, and N. H. Tuong, “Fedchain: Secure proof-of-stake-based framework for federated-blockchain systems,” IEEE Transactions on Services Computing, vol. 16, no. 4, pp. 2642–2656, Jan. 2023.
  104. A. Miller, A. Kosba, J. Katz, and E. Shi, “Nonoutsourceable scratch-off puzzles to discourage bitcoin mining coalitions,” in Proc. 22Nd ACM Sigsac Conference on Computer and Communications Security, 2015, pp. 680–691.
  105. S. Yan, “Analysis on blockchain consensus mechanism based on proof of work and proof of stake,” in Proc. 2022 International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI), 2022, pp. 464–467.
  106. L. Chen, L. Xu, N. Shah, Z. Gao, Y. Lu, and W. Shi, “On security analysis of proof-of-elapsed-time (poet),” in Proc. Stabilization, Safety, and Security of Distributed Systems: 19th International Symposium, SSS 2017, November 5–8, 2017, Proceedings 19, 2017, pp. 282–297.
  107. D. Puthal, S. P. Mohanty, V. P. Yanambaka, and E. Kougianos, “PoAh: A novel consensus algorithm for fast scalable private blockchain for large-scale IoT frameworks,” arXiv:2001.07297, Jan. 2020.
  108. X. Liu, G. Zhao, X. Wang, Y. Lin, Z. Zhou, H. Tang, and B. Chen, “Mdp-based quantitative analysis framework for proof of authority,” in Proc. 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), Jan. 2019, pp. 227–236.
  109. Z. Liu, S. Tang, S. S. Chow, Z. Liu, and Y. Long, “Fork-free hybrid consensus with flexible proof-of-activity,” Future Generation Computer Systems, vol. 96, pp. 515–524, Jul. 2019.
  110. T. M. Hewa, Y. Hu, M. Liyanage, S. S. Kanhare, and M. Ylianttila, “Survey on blockchain-based smart contracts: Technical aspects and future research,” IEEE Access, vol. 9, pp. 87 643–87 662, Mar. 2021.
  111. Z. Liu, Y. Xiang, J. Shi, P. Gao, H. Wang, X. Xiao, B. Wen, Q. Li, and Y.-C. Hu, “Make Web3.0 Connected,” IEEE Transactions on Dependable and Secure Computing, vol. 19, no. 5, pp. 2965–2981, May, 2022.
  112. W. Wang, D. T. Hoang, P. Hu, Z. Xiong, D. Niyato, P. Wang, Y. Wen, and D. I. Kim, “A survey on consensus mechanisms and mining strategy management in blockchain networks,” IEEE Access, vol. 7, pp. 22 328–22 370, Jan. 2019.
  113. A. Singh, K. Click, R. M. Parizi, Q. Zhang, A. Dehghantanha, and K.-K. R. Choo, “Sidechain technologies in blockchain networks: An examination and state-of-the-art review,” Journal of Network and Computer Applications, vol. 149, pp. 102 471–102 487, Jan. 2020.
  114. W. Chen, Y. Chen, X. Chen, and Z. Zheng, “Toward secure data sharing for the iov: A quality-driven incentive mechanism with on-chain and off-chain guarantees,” IEEE Internet of Things Journal, vol. 7, no. 3, pp. 1625–1640, Oct. 2019.
  115. T. Zhou, X. Li, and H. Zhao, “Dlattice: A permission-less blockchain based on dpos-ba-dag consensus for data tokenization,” IEEE Access, vol. 7, pp. 39 273–39 287, Mar. 2019.
  116. Y. Lin, Z. Gao, H. Du, D. Niyato, J. Kang, R. Deng, and X. S. Shen, “A unified blockchain-semantic framework for wireless edge intelligence enabled Web 3.0,” IEEE Wireless Communications, Early Access, doi: 10.1109/MWC.018.2200568, Mar. 2023.
  117. A. Furfaro, L. Argento, D. Saccá, F. Angiulli, and F. Fassetti, “An infrastructure for service accountability based on digital identity and blockchain 3.0,” in Proc. IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2019, pp. 632–637.
  118. W. Zou, D. Lo, P. S. Kochhar, X.-B. D. Le, X. Xia, Y. Feng, Z. Chen, and B. Xu, “Smart contract development: Challenges and opportunities,” IEEE Transactions on Software Engineering, vol. 47, no. 10, pp. 2084–2106, Sep. 2019.
  119. C. Wu, J. Xiong, H. Xiong, Y. Zhao, and W. Yi, “A review on recent progress of smart contract in blockchain,” IEEE Access, vol. 10, pp. 50 839–50 863, May, 2022.
  120. X. Jia, W. Xu, P. Deng, S. Gao, L. Tang, Y. Wang, M. Zhang, L. Bao, and D. Lin, “Cross-organisational data sharing framework based on blockchain-probes,” IET Networks, vol. 12, no. 2, pp. 77–85, Jul. 2023.
  121. R. Sheldon and B. Posey. (2023) 7 decentralized data storage networks compared. [Online]. Available: https://www.techtarget.com/searchstorage/tip/Comparing-4-decentralized-data-storage-offerings/.
  122. F. Casino, E. Politou, E. Alepis, and C. Patsakis, “Immutability and decentralized storage: An analysis of emerging threats,” IEEE Access, vol. 8, pp. 4737–4744, Dec. 2019.
  123. M. Xu, X. Ren, D. Niyato, J. Kang, C. Qiu, Z. Xiong, X. Wang, and V. C. Leung, “When quantum information technologies meet blockchain in Web 3.0,” IEEE Network, Early Access, doi: 10.1109/MNET.134.2200578, pp. 1–8, May, 2023.
  124. Y. Lin, Z. Gao, Y. Tu, H. Du, D. Niyato, J. Kang, and H. Yang, “A Blockchain-based Semantic Exchange Framework for Web 3.0 toward Participatory Economy,” IEEE Communications Magazine, vol. 61, no. 8, pp. 94–100, Jun. 2023.
  125. D. M. Doe, J. Li, N. Dusit, Z. Gao, J. Li, and Z. Han, “Promoting the Sustainability of Blockchain in Web 3.0 and the Metaverse Through Diversified Incentive Mechanism Design,” IEEE Open Journal of the Computer Society, vol. 4, pp. 171–184, Mar. 2023.
  126. B. Bhushan, C. Sahoo, P. Sinha, and A. Khamparia, “Unification of blockchain and internet of things (biot): requirements, working model, challenges and future directions,” Wireless Networks, vol. 27, pp. 55–90, Aug. 2021.
  127. Q. Wang, R. Li, Q. Wang, S. Chen, M. Ryan, and T. Hardjono, “Exploring Web3 from the view of blockchain,” arXiv:2206.08821, Jun. 2022.
  128. T. Berners-Lee, J. Hendler, and O. Lassila, “The Semantic web,” Scientific American, vol. 284, no. 5, pp. 34–43, May 2001.
  129. S. Bratt. Semantic Web, and Other W3C Technologies to Watch. [Online]. Available: https://www.w3.org/2007/Talks/0130-sb-W3CTechSemWeb/0130-sb-W3CTechSemWeb.pdf/.
  130. Semantic web. [Online]. Available: https://www.w3.org/standards/semanticweb/.
  131. RDF 1.1 concepts and abstract syntax. [Online]. Available: https://www.w3.org/TR/rdf11-concepts/.
  132. RDF Schema 1.1. [Online]. Available: https://www.w3.org/TR/rdf-schema/.
  133. T. R. Gruber, “A translation approach to portable ontology specifications,” Knowledge Acquisition, vol. 5, no. 2, pp. 199–220, Sep. 1993.
  134. J. Lehmann et al., “DBpedia–a large-scale, multilingual knowledge base extracted from wikipedia,” Semantic Web, vol. 6, no. 2, pp. 167–195, 2015.
  135. E. Sandhaus, “Semantic technology at the new york times: Lessons learned and future directions,” in Proc. Semantic Web–ISWC 2010: 9th International Semantic Web Conference, ISWC 2010, November 7-11, 2010, Revised Selected Papers, Part II 9.   Springer, 2010, pp. 355–355.
  136. J. Weaver and P. Tarjan, “Facebook linked data via the graph API,” Semantic Web, vol. 4, no. 3, pp. 245–250, 2013.
  137. N. Noy, Y. Gao, A. Jain, A. Narayanan, A. Patterson, and J. Taylor, “Industry-scale knowledge graphs: Lessons and challenges,” Queue, vol. 17, no. 2, pp. 48–75, Jul. 2019.
  138. P. Hitzler, “A review of the semantic web field,” Communications of the ACM, vol. 64, no. 2, pp. 76–83, Feb. 2021.
  139. C. Wang, H. Ma, G. Chen, and S. Hartmann, “Using an estimation of distribution algorithm to achieve multitasking semantic web service composition,” IEEE Transactions on Evolutionary Computation, vol. 27, no. 3, pp. 490–504, Apr. 2022.
  140. G. Kang, J. Liu, Y. Xiao, Y. Cao, B. Cao, and M. Shi, “Web services clustering via exploring unified content and structural semantic representation,” IEEE Transactions on Network and Service Management, vol. 19, no. 4, pp. 4082–4096, Aug. 2022.
  141. G. Zou, Z. Qin, Q. He, P. Wang, B. Zhang, and Y. Gan, “DeepWSC: Clustering web services via integrating service composability into deep semantic features,” IEEE Transactions on Services Computing, vol. 15, no. 4, pp. 1940–1953, Sep. 2020.
  142. W. Pang, H. Li, X. Ma, and H. Zhang, “A semantic-centered cloud control framework for autonomous unmanned system,” Journal of Systems Engineering and Electronics, vol. 33, no. 4, pp. 771–784, Aug. 2022.
  143. X. Li, D. Yang, J. Yuan, A. Donkers, and X. Liu, “Bim-enabled semantic web for automated safety checks in subway construction,” Automation in Construction, vol. 141, p. 104454, Sep. 2022.
  144. S. N. D. Ververidis and E. Anastasovitis. (2016) Architecture and interface design. [Online]. Available: https://www.researchgate.net/publication/322655519_D61_-_DigiArt_-_Architecture_and_Interface_Design/.
  145. D. Patterson, “Interactive 3D web applications for visualization of world health organization data,” in Proc. of the Australasian Computer Science Week Multiconference, 2016, pp. 1–8.
  146. D. Fan, T. Liang, H. He, M. Guo, and M. Wang, “Large-scale oceanic dynamic field visualization based on webgl,” IEEE Access, vol. 11, pp. 82 816–82 829, Aug. 2021.
  147. V. Munday. (2019) Introduction to web 3d technologies. [Online]. Available: https://medium.com/varvara.munday/introduction-to-web-3d-technologies-a26b1dc68454/.
  148. Z. Mateusz and M. Cezary. Web 3d programming: Past, present and future. [Online]. Available: https://emphie.com/insights/web-3d-programming5/.
  149. S. Discher, R. Richter, and J. Döllner, “Concepts and techniques for web-based visualization and processing of massive 3d point clouds with semantics,” Graphical Models, vol. 104, pp. 101 036–101 048, Jul. 2019.
  150. Opc. (2021) The 4 technologies that will make web 3.0 a reality. [Online]. Available: https://www.makeuseof.com/technologies-web-3-0/.
  151. P. Plex. (2023) Everything you need to know about web 3.0 and its impact on your business. [Online]. Available: https://pixelplex.io/blog/what-is-web-3-0/.
  152. C. et al. (2020) The Spatial Web and Web 3.0. [Online]. Available: https://www2.deloitte.com/us/en/insights/topics/digital-transformation/web-3-0-technologies-in-business.html/.
  153. H. Wu, H. Zhang, J. Cheng, J. Guo, and W. Chen, “Perspectives on point cloud-based 3D scene modeling and XR presentation within the cloud-edge-client architecture,” Visual Informatics, vol. 7, no. 3, pp. 59–64, Sep. 2023.
  154. S. Van Nguyen, S. T. Le, M. K. Tran, and H. M. Tran, “Reconstruction of 3D digital heritage objects for VR and AR applications,” Journal of Information and Telecommunication, vol. 6, no. 3, pp. 254–269, Dec. 2022.
  155. J. Flotynski, D. Brutzman, F. G. Hamza-Lup, A. Malamos, N. Polys, L. F. Sikos, and K. Walczak, “The semantic web3d: towards comprehensive representation of 3D content on the semantic web,” in Proc. 2019 International Conference on 3D Immersion (IC3D), 2019, pp. 1–9.
  156. F. Qin, S. Gao, X. Yang, M. Li, and J. Bai, “An ontology-based semantic retrieval approach for heterogeneous 3d cad models,” Advanced Engineering Informatics, vol. 30, no. 4, pp. 751–768, Oct. 2016.
  157. S. E. Kim, M. W. Lee, C. H. Jung, C. S. Park, J. M. Kim, and S. P. Lee, “Representation of vr-based health information for smart city,” in Proc. 25th International Conference on 3D Web Technology, 2020, pp. 1–7.
  158. Z. Ma, Y. Ding, P. Yue, L. Zhang, Y. Liang, and Y. Deng, “Research and application of 3D visualization technology of borehole data based on WebGL,” in Proc. 2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS), Dec. 2021, pp. 978–983.
  159. L. Li, X. Qiao, Q. Lu, P. Ren, and R. Lin, “Rendering optimization for mobile web 3d based on animation data separation and on-demand loading,” IEEE Access, vol. 8, pp. 88 474–88 486, May, 2020.
  160. H. Fan, G. Kong, and C. Zhang, “An Interactive platform for low-cost 3D building modeling from VGI data using convolutional neural network,” Big Earth Data, vol. 5, no. 1, pp. 49–65, Apr. 2021.
  161. R. Tabarés, “Html5 and the evolution of html; tracing the origins of digital platforms,” Technology in Society, vol. 65, pp. 1–8, Feb, 2021.
  162. Z. Lei, H. Zhou, W. Hu, G.-P. Liu, Q. Deng, D. Zhou, Z.-W. Liu, and X. Gao, “Unified 3-d interactive human-centered system for online experimentation: Current deployment and future perspectives,” IEEE Transactions on Industrial Informatics, vol. 17, no. 7, pp. 4777–4787, Aug. 2020.
  163. B. Maclntyre and T. F. Smith, “Thoughts on the Future of WebXR and the Immersive Web,” in Proc. 2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), 2018, pp. 338–342.
  164. K. Hanfati, S. Sukaridhoto, D. K. Basuki, R. P. N. Budiarti, E. D. Fajrianti, and I. A. Al Hafidz, “Design and Implementation of WebXR Health Learning Module Application,” in Proc. 2022 International Electronics Symposium (IES), 2022, pp. 632–637.
  165. X. Guo and I. Mogra, “Using web 3D and WebXR game to enhance engagement in primary school learning,” in Proc. 2022 IEEE International Symposium on Multimedia (ISM), 2022, pp. 181–184.
  166. B. D. S. Gonccalves, O. Postolache, and J. M. D. Pereira, “Gait rehabilitation in virtual reality serious game interactive scenarios,” in Proc. 2022 International Conference and Exposition on Electrical And Power Engineering (EPE), 2022, pp. 672–676.
  167. P. Winter, A. H. Lorimer, P. Snyder, and B. Livshits, “What’s in your wallet? privacy and security issues in Web 3.0,” arXiv:2109.06836, Feb. 2021.
  168. M. Grieco. (2022) Webassembly tutorial. [Online]. Available: https://www.youtube.com/watch?v=_8T9T6MQ1fU/.
  169. Mozilla Developer Network. (2023) Webassembly. [Online]. Available: https://developer.mozilla.org/en-US/docs/WebAssembly/.
  170. X. Sun, F. R. Yu, P. Zhang, Z. Sun, W. Xie, and X. Peng, “A survey on Zero-Knowledge-Proof in blockchain,” IEEE Network, vol. 35, no. 4, pp. 198–205, Aug. 2021.
  171. M. Shen, Z. Tan, D. Niyato, Y. Liu, J. Kang, Z. Xiong, L. Zhu, W. Wang et al., “Artificial intelligence for web 3.0: A comprehensive survey,” arXiv:2309.09972, Aug. 2023.
User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (12)
  1. Md Arif Hassan (2 papers)
  2. Mohammad Behdad Jamshidi (1 paper)
  3. Bui Duc Manh (4 papers)
  4. Nam H. Chu (11 papers)
  5. Chi-Hieu Nguyen (6 papers)
  6. Nguyen Quang Hieu (16 papers)
  7. Cong T. Nguyen (13 papers)
  8. Dinh Thai Hoang (125 papers)
  9. Diep N. Nguyen (86 papers)
  10. Nguyen Van Huynh (34 papers)
  11. Mohammad Abu Alsheikh (24 papers)
  12. Eryk Dutkiewicz (62 papers)