UsefulLinks
Computer Science
Distributed Systems
Distributed Consensus
1. Introduction to Distributed Consensus
2. Foundational Concepts and System Models
3. Consensus in Crash-Failure Models
4. Consensus in Byzantine-Failure Models
5. Consensus in Public and Permissionless Networks
6. Advanced Topics and Extensions
7. Performance and Optimization
8. Applications and Case Studies
9. Implementation Considerations
7.
Performance and Optimization
7.1.
Performance Metrics
7.1.1.
Latency Measurements
7.1.1.1.
End-to-end Latency
7.1.1.2.
Processing Delays
7.1.1.3.
Network Delays
7.1.2.
Throughput Analysis
7.1.2.1.
Transaction Rate
7.1.2.2.
Batch Processing
7.1.2.3.
Pipeline Optimization
7.1.3.
Scalability Factors
7.1.3.1.
Node Count Impact
7.1.3.2.
Message Complexity
7.1.3.3.
Storage Requirements
7.2.
Communication Optimization
7.2.1.
Message Aggregation
7.2.1.1.
Batch Processing
7.2.1.2.
Compression Techniques
7.2.1.3.
Piggyback Mechanisms
7.2.2.
Network Topology
7.2.2.1.
Overlay Networks
7.2.2.2.
Hierarchical Structures
7.2.2.3.
Proximity Awareness
7.2.3.
Multicast Protocols
7.2.3.1.
Reliable Multicast
7.2.3.2.
Atomic Multicast
7.2.3.3.
Causal Multicast
7.3.
Computational Optimization
7.3.1.
Cryptographic Efficiency
7.3.1.1.
Signature Schemes
7.3.1.2.
Hash Functions
7.3.1.3.
Verification Optimization
7.3.2.
Parallel Processing
7.3.2.1.
Concurrent Validation
7.3.2.2.
Pipeline Stages
7.3.2.3.
Load Balancing
7.3.3.
Memory Management
7.3.3.1.
State Compression
7.3.3.2.
Garbage Collection
7.3.3.3.
Cache Optimization
7.4.
Adaptive Protocols
7.4.1.
Dynamic Parameter Tuning
7.4.1.1.
Timeout Adjustment
7.4.1.2.
Batch Size Optimization
7.4.1.3.
Load-based Adaptation
7.4.2.
Failure Rate Adaptation
7.4.2.1.
Fault Detection Tuning
7.4.2.2.
Recovery Optimization
7.4.2.3.
Redundancy Adjustment
7.4.3.
Network Condition Adaptation
7.4.3.1.
Bandwidth Awareness
7.4.3.2.
Latency Compensation
7.4.3.3.
Congestion Control
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6. Advanced Topics and Extensions
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8. Applications and Case Studies