7.8 KiB
Understanding the Logos Blockchain Whitepaper
Title: Understanding the Logos Blockchain Whitepaper | A High-Level Conceptual Overview/Review of the Logos Blockchain
Purpose: This document reflects an approach of whitepaper review that combines a rough-draft whitepaper review containing comments/reflections/concerns with a further simplification of concepts to make everything more digestible to more people outside of the internal Status infra team for communication purposes. In addition, this review will provide a gauge of difficulty of understanding involved with various different terms/concepts.
Tags: #learning #whitepaper #Logos
**"We build everything on top of consensus." ** Dr. Corey Petty
How-To (Get Cookin')
There are some descriptions below which detail the usage of visual guidance metrics available in the form of "cookbook-like" instructions for how to consume this document:
Gauges | Description | Visualization |
---|---|---|
Difficulty | 1-10 (Ticks/Pips) | [||||||||||] |
Time | In Minutes | X Minutes |
Resources | Article/Video Links w/ Visual Content | Conceptual & Pictoral "Ingredients List" of Links |
See below 'Recipe' and modify accordingly to above in Figma.
Operating Definitions: Easiness/Difficulty is defined as the ease of which the concepts can be generally understood.
Time/Scope is in reference to the size of information necessary to learn to gain a decent level of comprehension.
Resources is for links relevant to helping people understand the concepts.
Necessary Terminology by Layer
The Six (6) Technology Layers of Logos as a Blockchain
- Terminology Template: here
Consensus
- BBA
- Difficulty: [||||||||||]
- Time: 5m
- Resources:
- Leaderless
- DAGs
- CIC
- Messaging
- Permissionless
- Scalability
- Decentralization
- Security
- Communication Costs
- Stream or Subgraph
- Staking
- Sybil Resistance
- CFT (Crash Fault Tolerant)
- BFT (Byzantine Fault Tolerant)
- Finality
- Social Applications
- Bootstrapping
- Rounds
- Round-less
- PBFT
- DAG-Based Consensus (Avalanche-like)
- Liveness
- Asynchronous (P2P)
- Execution-Layer Decoupling
- Interchangeability
- Liveness
- Extensibility
- Highly-Partitioned Blockchains with Local Views
- Ordering
- Reputation
- Confidence
- Network Congestion
- Topology
- Resilience (Consensus context)
- Verifiability
- Non-Repudiation
- Snowball
- Lachesis
- Glacier
Node Reputation
- Ikingut (Reputation Algorithm)
- Important Conceptual Goals
- Simple
- Lightweight
- Pluggable
- Adaptive
- Dynamic
- Robust
- No Transitive Trust
- Reasonable Bootstrap Time
- Reputation Polling (Polling Dynamics)
- Indirect Request
- Direct Request
- Unirep (an example)
- Qualities Necessary
- Requires Verifiability
- Requires Non-Repudiation
- Privacy Preserving (preserve origins of score, emit opinions without a way to trace back the origins - MPC)
- Local Heuristic
- Algorithm
- Each Iteration
- Voting
- Agent Action (Post-Consensus Decision Finality)
- Min-Multiplicative Reputation Punishment
- Multiplicative
- Linear
- Each Iteration
- Experimental Research
- Starting Point
- Trust Wisdom per Node (requires further elaboration)
- Adversary Types and Effects (requires further elaboration)
- Current Stage of Testing/Challenges
- Silent-Omniscient Adversaries
- Modulating Punishment/No Punishment Impacts to Conditions
- Adding Multiplicative-min Punishment
- Attacks
- Con-Artist Attack
- The On-Off Attack
- Effects on Glacier Consensus
- Limitations
- No immediate defense against coordinated attacks
- Reputation does not add to security
- Future Work
- Circumstantial Impact of Reputation on Consensus
- Long-running Simulation
- Sudden changes in Collective Byzantine Behavior
- Pending Questions
- Interaction of Stake-based and Reputation-based selection
- Stake simulations are necessary for exploring options
- Relevant in the incentives discussion?
- How much (and if) does reputation really help in a coordinated attack? (Assuming patient con-artist attack)
- Complex interactions here, this model would particularly benefit having a prototype/PoC
- Interaction of Stake-based and Reputation-based selection
- Starting Point
- Important Conceptual Goals
- Node Challenges
- Design
- Eigentrust
- Transitive Trust
- Understanding the Math
- Trust Decay
- Malicious Clusters (describe nuances better | trusted nodes cannot overlap the malicious collective)
- Trust for Consensus
- Separation of Reputation
- Confidant
- XRep
- P-Grid
- R2Trust
- Generic Taxonomy
- Dimensions
- #Single
- Multiple
- Time computation
- Aggregation
- Deterministic sum of positive and negative ratings
- Probabilistic
- Logic
- Local vs gathered data
- Age of data
- Frequency of data
- Weight of multiple dimensions
- Value Control
- External
- Internal
- Data Aging
- None
- Decay
- Death of old/selected
- Selection
- Ranking-based
- Threshold (trusted/untrusted)
- Probabilistic selection
- Dimensions
Network Layer and Mempool
- Node Discovery
- Subnetworks
- Design
- Implementation
- Ideas
- Mempool
- Challenges
- Approach
- Mempool Design
Staking and Multi-DAG
- Factory of DAGs
- Concept
- Algorithm
- Sub-DAG
- Cross-DAG
- Bridge (Intermediary) Nodes
- Gravity
- Application-Level User-Driven
- Direct Communication Channel
- Direct Communication VGER
- Challenges
- Probabilistic finality and cross-network communication
- Network partitioning, forks and cross-network communication
- Weak Subjectivity - Reputation of nodes matters to clients. Nodes are clients of other networks.
- Staking: Verifying Weights
- Glacier Algorithm Quiesces
- Approach
- Deterministic Finality
- Secondary Consensus Protocol (form local opinion on external DAG)
- Intermediary DAG (Intersection of nodes participating mutually in common structures)
- Vertex Sealing
- XSub (Cross-sub-DAG communication)
- XDAG (Cross-DAG communication)
- XDAG Fees
- Communication Patterns
- Direct
- User-Coordinated Channel
- Sub-DAG-Coordinated Channel
- Stake Sub-DAG
Data Model and Concurrency
- Reference Work
- Approach
- Data Model Design
- Challenges
- Concept
- Data Structures and Constraints
- Concurrent Execution (Threads)
- Execution Patterns
- Useful patterns
- Example of EVM execution on this model
- Explore and describe
- Anti-patterns
- High Contention
- Low Affinity
- Useful patterns