Are you a DePIN? A Decision Tree to Classify Decentralized Physical Infrastructure Networks
- URL: http://arxiv.org/abs/2501.17416v1
- Date: Wed, 29 Jan 2025 05:05:53 GMT
- Title: Are you a DePIN? A Decision Tree to Classify Decentralized Physical Infrastructure Networks
- Authors: Michael S. Andrew, Mark C. Ballandies,
- Abstract summary: Decentralized physical infrastructure networks (DePINs) are an emerging vertical within "Web3"
This study proposes a novel decision tree for classifying systems as DePIN.
The paper demonstrates the application of the decision tree to various blockchain systems, including Helium and Bitcoin.
- Score: 0.0
- License:
- Abstract: Decentralized physical infrastructure networks (DePINs) are an emerging vertical within "Web3" replacing the traditional method that physical infrastructures are constructed. Yet, the boundaries between DePIN and traditional method of building crowd-sourced infrastructures such as citizen science initiatives or other Web3 verticals are not always so clear cut. In this work, we systematically analyze the differences between DePIN and other Web2 and Web3 verticals. For this, the study proposes a novel decision tree for classifying systems as DePIN. This tree is informed by prior studies and differentiates DePIN from related concepts using criteria such as the presence of a three-sided market, token-based incentives for supply, and the requirement for physical asset placement in those systems. The paper demonstrates the application of the decision tree to various blockchain systems, including Helium and Bitcoin, showcasing its practical utility in differentiating DePIN systems. This research offers significant contributions towards establishing a more objective and systematic approach to identifying and categorizing DePIN systems. It lays the groundwork for creating a comprehensive and unbiased database of DePIN systems, which will inform future research and development within this emerging sector.
Related papers
- Payments Use Cases and Design Options for Interoperability and Funds Locking across Digital Pounds and Commercial Bank Money [0.0]
We focus on three key capabilities: communication between digital pound ecosystem participants, funds locking, and interoperability across digital pounds and commercial bank money.
We conclude that a financial market infrastructure (FMI) providing specific capabilities could simplify the experience of ecosystem participants, simplify the operating platforms for both the Bank of England and digital pound Payment Interface Providers (PIPs) and facilitate the creation of innovative services.
arXiv Detail & Related papers (2024-09-13T09:12:32Z) - CyberNFTs: Conceptualizing a decentralized and reward-driven intrusion detection system with ML [0.0]
The study employs an analytical and comparative methodology, examining the synergy between cutting-edge Web3 technologies and information security.
The proposed model incorporates blockchain concepts, cyber non-fungible token (cyberNFT) rewards, machine learning algorithms, and publish/subscribe architectures.
arXiv Detail & Related papers (2024-08-31T21:15:26Z) - Adaptive Interface-PINNs (AdaI-PINNs): An Efficient Physics-informed Neural Networks Framework for Interface Problems [0.0]
We present an efficient physics-informed neural networks (PINNs) framework, termed Adaptive Interface-PINNs (AdaI-PINNs)
This framework is an enhanced version of its predecessor, Interface PINNs or I-PINNs.
In AdaI-PINNs, the activation functions vary solely in their slopes, which are trained along with the other parameters of the neural networks.
arXiv Detail & Related papers (2024-06-07T04:22:32Z) - IT Strategic alignment in the decentralized finance (DeFi): CBDC and digital currencies [49.1574468325115]
Decentralized finance (DeFi) is a disruptive-based financial infrastructure.
This paper seeks to answer two main questions 1) What are the common IT elements in the DeFi?
And 2) How the elements to the IT strategic alignment in DeFi?
arXiv Detail & Related papers (2024-05-17T10:19:20Z) - Performance Analysis of Decentralized Physical Infrastructure Networks and Centralized Clouds [42.37170902465878]
Decentralized Physical Infrastructure Networks (DePINs) aim to enhance data sovereignty and confidentiality and increase resilience against a single point of failure.
This work focuses on the potential of DePINs to disrupt traditional centralized architectures by taking advantage of the Internet of Things (IoT) devices and crypto-economic design in combination with blockchains.
arXiv Detail & Related papers (2024-04-12T08:00:38Z) - Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning [51.13534069758711]
Decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities.
Federated Learning (FL) enables participants to collaboratively train models while safeguarding data privacy.
This paper investigates the synergy between blockchain's security features and FL's privacy-preserving model training capabilities.
arXiv Detail & Related papers (2024-03-28T07:08:26Z) - A Taxonomy for Blockchain-based Decentralized Physical Infrastructure
Networks (DePIN) [0.1979158763744267]
We conduct a literature review and analysis of DePIN systems from a conceptual architecture.
We identify and define relevant components and attributes, establishing a clear hierarchical structure.
arXiv Detail & Related papers (2023-08-17T05:08:43Z) - Hierarchical certification of nonclassical network correlations [50.32788626697182]
We derive linear and nonlinear Bell-like inequalities for networks, whose violation certifies the absence of a minimum number of classical sources in them.
We insert this assumption, which leads to results more amenable to certification in experiments.
arXiv Detail & Related papers (2023-06-27T18:00:01Z) - Rank Diminishing in Deep Neural Networks [71.03777954670323]
Rank of neural networks measures information flowing across layers.
It is an instance of a key structural condition that applies across broad domains of machine learning.
For neural networks, however, the intrinsic mechanism that yields low-rank structures remains vague and unclear.
arXiv Detail & Related papers (2022-06-13T12:03:32Z) - Understanding the wiring evolution in differentiable neural architecture
search [114.31723873105082]
Controversy exists on whether differentiable neural architecture search methods discover wiring topology effectively.
We study the underlying mechanism of several existing differentiable NAS frameworks.
arXiv Detail & Related papers (2020-09-02T18:08:34Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.