References

  1. World Wide Web Consortium. (2022). Decentralized Identifiers (DIDs) v1.0.

  2. World Wide Web Consortium. (2023). Verifiable Credentials Data Model v2.0.

  3. Buterin, V. (2014). A Next-Generation Smart Contract and Decentralized Application Platform (White Paper). Ethereum.

  4. Beck, R. (2018). Governance in the Blockchain Economy: A Framework and Research Agenda. Journal of the Association for Information Systems, 19(10), 1020–1034.

  5. Helium White Paper. (2020). A Decentralized Wireless Network.

  6. Kassab, S. (2023). The DePIN Sector Map. Messari Research.

  7. Roman, R., Lopez, J. & Mambo, M. (2018). Mobile Edge Computing, Fog et al.: A Survey and Analysis of Security Threats and Challenges. Future Generation Computer Systems, 78, 680–698.

  8. Schollmeier, R. (2002). A Definition of Peer-to-Peer Networking for the Classification of Peer-to-Peer Architectures and Applications. Proceedings First International Conference on Peer-to-Peer Computing (P2P2002), 27–29.

  9. Benet, J. (2014). IPFS – Content Addressed, Versioned, P2P File System.

  10. Tanenbaum, A. S. & Van Steen, M. (2017). Distributed Systems: Principles and Paradigms (2nd ed.). Pearson.

  11. Kurose, J. & Ross, K. (2021). Computer Networking: A Top-Down Approach (8th ed.). Pearson.

  12. Nygren, E., Sitaraman, R. K. & Sun, J. (2010). The Akamai Network: A Platform for High-Performance Internet Applications. SIGOPS Operating Systems Review, 44(3), 2–19.

  13. Cai, Y., Xu, Y., Li, J. et al. (2020). Edge Computing in IoT: Distributed Computing for Smart Healthcare. Journal of Network and Computer Applications, 149, 102461.

  14. Zamyatin, A., Al-Bassam, M., Zindros, D., et al. (2021). SoK: Communication Across Distributed Ledgers. IEEE Security & Privacy Workshops, 99–109.

  15. Polkadot White Paper. (2020). Polkadot: Vision for a Heterogeneous Multi-Chain Framework.

  16. Russell, S. & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.

  17. Silver, D. et al. (2017). The Predictron: End-To-End Learning and Planning. International Conference on Machine Learning (ICML), 3191–3199.

  18. Dean, J. & Ghemawat, S. (2004). MapReduce: Simplified Data Processing on Large Clusters. OSDI, 137–150.

  19. Abadi, M. et al. (2016). TensorFlow: A System for Large-Scale Machine Learning. OSDI, 265–283.

  20. Voigt, P. & Von dem Bussche, A. (2017). The EU General Data Protection Regulation (GDPR). A Practical Guide. Springer.

  21. California Consumer Privacy Act (CCPA). (2018).

  22. Hyperledger Case Studies. (2019). [Multiple publications].

  23. Satyanarayanan, M. (2017). The Emergence of Edge Computing. Computer, 50(1), 30–39.

  24. Mao, Y., You, C., Zhang, J., et al. (2017). A Survey on Mobile Edge Computing: The Communication Perspective. IEEE Communications Surveys & Tutorials, 19(4), 2322–2358.

  25. Pollen Mobile. (2022). Community-Driven Decentralized Mobile Network.

  26. MakerDAO White Paper.

  27. Moloch DAO.

  28. Raicu, I., Foster, I. & Zhao, Y. (2008). Many-Task Computing for Grids and Supercomputers. IEEE Workshop on Many-Task Computing.

  29. Zhang, F. et al. (2020). A Survey on Serverless Computing. ACM Computing Surveys, 53(2).

  30. Shi, W., Cao, J., Zhang, Q., Li, Y. & Xu, L. (2016). Edge Computing: Vision and Challenges. IEEE Internet of Things Journal, 3(5), 637–646.

  31. Li, X., Chen, L. & Xu, Z. (2019). Edge Computing: A Primer. Springer.

  32. Wood, G. (2014). Ethereum: A Secure Decentralised Generalised Transaction Ledger (Yellow Paper).

  33. Huang, J. (NVIDIA). (Various keynotes/interviews).

  34. Wooldridge, M. & Jennings, N. R. (1995). Intelligent Agents: Theory and Practice. Knowledge Engineering Review, 10(2), 115–152.

  35. Costan, V. & Devadas, S. (2016). Intel SGX Explained. IACR Cryptology ePrint Archive, 2016(86).

  36. Zhao, F. et al. (2018). Trusted eXecution on ARM TrustZone. ACM Computing Surveys, 51(6).

  37. Voshmgir, S. (2020). Token Economy: How the Web3 Reinvents the Internet. BlockchainHub.

  38. Wang, T., Kliazovich, D., Bouvry, P. & Khan, S. U. (2017). GreenDCN: A Packet-Level Simulator of Energy-Efficient Data Center Networks. IEEE Transactions on Industrial Informatics, 14(2), 858–867.

  39. Yang, S., Hao, J., He, M., et al. (2020). A Multi-Agent Reinforcement Learning Approach for Performance Optimization in Edge Computing. Sensors, 20(7), 1928.

  40. SAP, Meta, ServiceNow, NVIDIA (Various announcements/interviews on Agentic AI).

Last updated