Module encryption_benchmark 

Encryption Benchmark Value Object

This module provides the EncryptionBenchmark value object for capturing and analyzing encryption performance metrics in the adaptive pipeline system. It enables performance monitoring, algorithm comparison, and optimization decisions based on real-world benchmarks.

Features

• Performance Metrics: Comprehensive capture of throughput, latency, memory, and CPU usage
• Algorithm Comparison: Standardized benchmarking across different encryption algorithms
• Temporal Tracking: RFC3339-compliant timestamp recording for trend analysis
• Serialization Support: Full serde compatibility for persistence and transmission
• Immutable Design: Value object semantics with snapshot-based performance data

Architecture

The EncryptionBenchmark follows Domain-Driven Design principles as a value object, representing an immutable snapshot of encryption performance at a specific point in time. It integrates with the pipeline’s monitoring and optimization systems to guide algorithm selection and resource allocation decisions.

Usage Examples

Creating Benchmark Results

Comparing Algorithm Performance

Performance Analysis

Throughput Analysis

Throughput measurements provide insight into sustained data processing rates:

• High Throughput (>200 MB/s): Excellent for large file processing
• Medium Throughput (50-200 MB/s): Good for general-purpose encryption
• Low Throughput (<50 MB/s): May indicate CPU bottleneck or algorithm inefficiency

Latency Considerations

Latency affects responsiveness in interactive scenarios:

• Low Latency (<10ms): Suitable for real-time processing
• Medium Latency (10-100ms): Acceptable for batch processing
• High Latency (>100ms): May require optimization or algorithm change

Resource Utilization

Memory and CPU usage inform resource allocation decisions:

• Memory Usage: Higher usage may indicate buffering or inefficient implementation
• CPU Usage: Should correlate with throughput; high CPU with low throughput indicates inefficiency

Efficiency Metrics

Calculate efficiency ratios for informed decisions:

Serialization and Persistence

JSON Serialization

Database Storage

Benchmark data maps well to relational databases:

CREATE TABLE encryption_benchmarks (
    id SERIAL PRIMARY KEY,
    algorithm VARCHAR(50) NOT NULL,
    throughput_mbps DOUBLE PRECISION NOT NULL,
    latency_ms INTEGER NOT NULL,
    memory_usage_mb DOUBLE PRECISION NOT NULL,
    cpu_usage_percent DOUBLE PRECISION NOT NULL,
    file_size_mb DOUBLE PRECISION NOT NULL,
    timestamp TIMESTAMP WITH TIME ZONE NOT NULL,
    INDEX idx_algorithm (algorithm),
    INDEX idx_timestamp (timestamp)
);

Time Series Analysis

The RFC3339-compliant timestamp enables trend analysis:

• Track performance changes over time
• Identify performance regressions
• Correlate performance with system changes
• Compare algorithm performance across versions

Structs

EncryptionBenchmark

Encryption performance benchmark results for algorithm comparison and optimization.