DGT DOCS
  • 1. INTRODUCTION
    • 1.1 Executive Summary
    • 1.2 Why DGT
    • 1.3 Distributed Ledgers Technology
      • 1.3.1 Decentralization approach
      • 1.3.2 Consensus Mechanism
      • 1.3.3 Transactions
      • 1.3.4 Layered Blockchain Architecture
      • 1.3.5 Tokenomics
      • 1.3.6 Web 3 Paradigm
      • 1.3.7 Common Myths about Blockchain
    • 1.4 The DGT Overview
      • 1.4.1 Platform Approach
      • 1.4.2 DGT Functional Architecture
      • 1.4.3 Technology Roadmap
    • 1.5 How to create a Solution with DGT Networks
    • 1.6 Acknowledgments
  • 2. REAL WORLD APPLICATIONS
    • 2.1 Case-Based Approach
      • 2.1.1 DGT Mission
      • 2.1.2 The Methodology
      • 2.1.3 Case Selection
    • 2.2 Supply Chain and Vertical Integration
      • 2.2.1 Logistics Solution for Spare Parts Delivery
      • 2.2.2 DGT Based Solution for Coffee Chain Products
    • 2.3 Innovative Financial Services
      • 2.3.1 Crowdfunding Platform
      • 2.3.2 Real World Assets Tokenization
      • 2.3.3 Virtual Neobank over DGT Network
      • 2.3.4 DGT based NFT Marketplace
    • 2.4 Decentralized Green Energy Market
      • 2.4.1 Peer To Peer Energy Trading
      • 2.4.2 DGT based Carbon Offset Trading
    • 2.5 B2B2C Ecosystems and Horizontal Integration
      • 2.5.1 KYC and User Scoring
      • 2.5.2 Decentralized Marketing Attribution
      • 2.5.3 Case Decentralized Publishing Platform
      • 2.5.4 Value Ecosystem
    • 2.6 More Cases
  • 3. DGT ARCHITECTURE
    • 3.1 Scalable Architecture Design
      • 3.1.1 High Level Architecture
      • 3.1.2 DGT Approach
      • 3.1.3 Unique contribution
      • 3.1.4 Component Based Architecture
    • 3.2 Performance Metrics
    • 3.3 Network Architecture
      • 3.3.1 Nework Architecture in General
      • 3.3.2 Network Identification
      • 3.3.3 H-Net Architecture
      • 3.3.4 Transport Level
      • 3.3.5 Segments
      • 3.3.6 Static and Dynamic Topologies
      • 3.3.7 Cluster Formation
      • 3.3.8 Node Networking
      • 3.3.9 Permalinks Control Protocol
    • 3.4 Fault-Tolerant Architecture
      • 3.4.1 Introduction to Fault Tolerance
      • 3.4.2 F-BFT: The Hierarchical Consensus Mechanism
      • 3.4.3 Cluster Based Algorithms
      • 3.4.4 Arbitrator Security Scheme
      • 3.4.5 Heartbeat Protocol
      • 3.4.6 Oracles and Notaries
      • 3.4.7 DID & KYC
    • 3.5 Transactions and Performance
      • 3.5.1 Transaction Basics
      • 3.5.2 Transaction Processing
      • 3.5.3 Transaction and block signing
      • 3.5.4 Transaction Families
      • 3.5.5 Transaction Receipts
      • 3.5.6 Smart Transactions
      • 3.5.7 Private Transactions
      • 3.5.8 Multi signature
    • 3.6 Data-Centric Model
      • 3.6.1 Data layer overview
      • 3.6.2 Global State
      • 3.6.3 Genesis Record
      • 3.6.4 Sharding
      • 3.6.5 DAG Synchronization
    • 3.7 Cryptography and Security
      • 3.7.1 Security Architecture Approach
      • 3.7.2 Base Cryptography
      • 3.7.3 Permission Design
      • 3.7.4 Key Management
      • 3.7.5 Encryption and Decryption
      • 3.7.6 Secure Multi Party Computation
      • 3.7.7 Cryptographic Agility
      • DGTTECH_3.8.4 Gateway Nodes
    • 3.8 Interoperability
      • 3.8.1 Interoperability Approach
      • 3.8.2 Relay Chain Pattern
      • 3.8.3 Virtual Machine Compatibility
      • 3.8.4 Gateway Nodes
      • 3.8.5 Token Bridge
    • 3.9 DGT API and Consumer Apps
      • 3.9.1 Presentation Layer
      • 3.9.2 Application Architecture
    • 3.10 Technology Stack
    • REFERENCES
  • 4. TOKENIZATION AND PROCESSING
    • 4.1 Introduction to Tokenization
      • 4.1.1 DGT Universe
      • 4.1.2 Driving Digital Transformation with Tokens
      • 4.1.3 Real-World Tokenization
      • 4.1.4 Key Concepts and Definitions
    • 4.2 Foundations of Tokenization
      • 4.2.1 Definition and Evolution of Tokenization
      • 4.2.2 Tokenization in the Blockchain/DLT Space
      • 4.2.3 The Tokenization Process
      • 4.2.4 Tokenization on the DGT Platform
      • 4.2.5 Regulatory and Legal Aspects of Tokenization
      • 4.2.6 Typical Blockchain-Based Business Models
    • 4.3 The DEC Transaction Family
      • 4.3.1 DEC Transaction Family Overview
      • 4.3.2 DEC Token Features
      • 4.3.3 DEC Token Protocol
      • 4.3.4 DEC Account Design
      • 4.3.5 DEC Transaction Family Flow
      • 4.3.6 DEC Commands
      • 4.3.7 DEC Processing
      • 4.3.8 Payment Gateways
    • 4.4 Understanding Secondary Tokens
      • 4.4.1 The different types of tokens supported by DGT
      • 4.4.2 How secondary tokens are produced
  • 5. EXPLORING TOKENOMICS
    • 5.1 Introduction
      • 5.1.1 What does tokenomics mean?
      • 5.1.2 Goals of Building the Model for DGT Network
      • 5.1.3 Tokens vs Digital Money
      • 5.1.4 The Phenomenon of Cryptocurrency
      • 5.1.5 Basic Principles of Tokenomics
      • 5.1.6 AB2023 Model
    • 5.2 Node & User Growth
      • 5.2.1 Node Ecosystem
      • 5.2.2 User Growth and Retention Modeling
    • 5.3 Transactions
      • 5.3.1 Transaction Amount Components
      • 5.3.2 Shaping the Transaction Profile: A Three-pronged Approach
      • 5.3.3 Calculation of Transaction Number
    • 5.4 Network Performance Simulation
      • 5.4.1 Endogenous Model
      • 5.4.2 Network Entropy
      • 5.4.3 Network Utility
    • 5.5 Token Supply Model
      • 5.5.1 Introduction to Supply and Demand Dynamics
      • 5.5.2 Token distribution
      • 5.5.3 Supply Protocol
      • 5.5.4 Token Balance and Cumulative Supply
    • 5.6 Token Demand Model
      • 5.6.1 Node-Base Demand
      • 5.6.2 Transaction-Based Token Demand
      • 5.6.3 Staking Part Modeling
      • 5.6.4 Total Demand
    • 5.7 Token Price Simulation
      • 5.7.1 Nelson-Siegel-Svensson model
      • 5.7.2 The Price Model
    • 5.8 Decentralization Measurement
      • 5.8.1 Active Node Index
      • 5.8.2 Node Diversity in Hybrid Networks
      • 5.8.3 Token distribution
      • 5.8.4 Integral Calculation of Decentralization Metric
    • 5.9 Aggregated Metrics
      • 5.9.1 Transaction Throughput: Evaluating Network Performance and Scalability
      • 5.9.2 Market Capitalization: A Dimension of Valuation in Cryptocurrency
      • 5.9.3 Total Value Locked (TVL): A Spotlight on Network Engagement and Trust
  • 6. ADMINISTRATOR GUIDE
    • 6.1 Introduction
      • 6.1.1 Administrator Role
      • 6.1.2 Platform sourcing
      • 6.1.3 DGT Virtualization
      • 6.1.4 Using Pre-Built Virtual Machine Images
      • 6.1.5 Server Preparation
      • 6.1.6 OS Setup and initialization
    • 6.2 DGT CORE: Single Node Setup
      • 6.2.1 Launch the First DGT Node
      • 6.2.2 Dashboard setup
      • 6.2.3 Nodes Port Configuration
      • 6.2.4 Single Node Check
    • 6.3 DGT CORE: Setup Private/Public Network
      • 6.3.1 Network launch preparation
      • 6.3.2 A Virtual Cluster
      • 6.3.3 A Physical Network
      • 6.3.4 Attach node to Existing Network
    • 6.4 DGT Dashboard
    • 6.5 DGT CLI and base transaction families
    • 6.6 GARANASKA: Financial Processing
      • 6.6.1 Overview of DGT’s financial subsystem
      • 6.6.2 DEC emission
      • 6.6.3 Consortium account
      • 6.6.4 User accounts
      • 6.6.5 Payments
    • 6.7 Adjust DGT settings
      • 6.7.1 DGT Topology
      • 6.7.2 Manage local settings
    • 6.8 DGT Maintenance
      • 6.8.1 Stopping and Restarting the Platform
      • 6.8.2 Backing up Databases
      • 6.8.3 Network Performance
      • 6.8.4 Log & Monitoring
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  1. 5. EXPLORING TOKENOMICS
  2. 5.8 Decentralization Measurement

5.8.1 Active Node Index

Previous5.8 Decentralization MeasurementNext5.8.2 Node Diversity in Hybrid Networks

Last updated 1 year ago

In the complex weave of decentralized networks, each node stands as a pivotal component, embodying a fraction of the network’s overall health and functionality. The Active Node Index (ANI) emerges as a crucial metric in this digital tapestry, shedding light on the vitality and engagement level of nodes within the network.

ANI=NActiveNodesNnodes        (41)ANI = \frac {N_{Active Nodes}} {N_{nodes}} \ \ \ \ \ \ \ \ \tag{41}ANI=Nnodes​NActiveNodes​​        (41)

Breaking down the equation, represents the number of nodes actively participating in the network, while signifies the total number of nodes, both active and inactive, within the network.

At its core, ANI provides a snapshot into the vibrancy and participatory health of the network. A higher ANI indicates a larger proportion of nodes taking an active role in the network's processes, such as transaction validation, block creation, and consensus formation, embodying a robust and lively network. Conversely, a lower ANI suggests diminished active participation, potentially signaling issues like network stagnation, reduced reliability, or decreased interest and trust among participants.

Implications on Network Performance:

  • Reliability and Trust: A consistently high ANI symbolizes a reliable network, fostering trust among users due to the numerous nodes verifying transactions and maintaining the ledger.

  • Security Dynamics: A network underpinned by a vast multitude of active nodes inherently embeds a heightened level of security. More nodes participating equates to a distributed consensus, mitigating the risk of malicious attacks and enhancing the resilience against potential threats.

  • Network Latency and Throughput: Active participation from nodes accelerates transaction verification and block addition to the blockchain, reducing latency and elevating throughput in the network, thus providing a smoother and more efficient user experience.

  • Decentralization: A healthy ANI typically correlates with a high degree of decentralization. The proportionate active involvement of nodes ensures that control and verification processes are not confined to a limited subset, preserving the democratic ethos of decentralized networks.

  • Incentive and Reward Systems: In networks where node activity is incentivized, a high ANI might indicate that the reward system is effectively encouraging participation. It symbolizes that nodes find it economically viable and rewarding to stay active, contributing to the network's stability and security.

Thus, the ANI stands as not merely a numerical value but as a barometer, capturing the pulsating life and activity within the decentralized network, facilitating a realm where technology and participation harmoniously intertwine to architect a reliable, secure, and thriving digital ecosystem.

Figure 93 Active Node Index over time