SnmpKit.SnmpSim.CorrelationEngine (snmpkit v0.6.6)

Implement realistic correlations between different metrics.

Network metrics don't exist in isolation - they influence each other in predictable ways:

  • Signal quality degrades with higher utilization
  • Error rates increase with poor signal quality
  • Temperature affects equipment performance
  • Power consumption correlates with activity levels

This module provides sophisticated correlation modeling for authentic network simulation.

Summary

Types

correlation_config()
correlation_type()

Functions

apply_correlations(primary_oid, primary_value, device_state, correlations, current_time)

Apply correlations to a device's metrics based on primary metric changes.

calculate_power_consumption_correlation(device_metrics, device_type)

Model power consumption correlations with activity and temperature.

calculate_signal_throughput_correlation(snr_db, power_level_dbmv, max_throughput)

Calculate signal quality impact on throughput for DOCSIS devices.

calculate_temperature_performance_correlation(temperature_celsius, equipment_type)

Calculate temperature impact on equipment performance.

calculate_utilization_error_correlation(utilization_percent, interface_type)

Calculate utilization impact on error rates.

get_device_correlations(device_type)

Get standard correlation configurations for common device types.

Types

correlation_config()

@type correlation_config() :: %{
  type: correlation_type(),
  strength: float(),
  delay_seconds: integer(),
  threshold: float(),
  noise_factor: float()
}

correlation_type()

@type correlation_type() ::
  :positive | :negative | :threshold | :exponential | :logarithmic

Functions

apply_correlations(primary_oid, primary_value, device_state, correlations, current_time)

@spec apply_correlations(atom(), number(), map(), list(), DateTime.t()) :: map()

Apply correlations to a device's metrics based on primary metric changes.

Examples

device_state = %{
  interface_utilization: 0.8,
  signal_quality: 85.0,
  temperature: 45.0
}

correlations = [
  {:interface_utilization, :error_rate, :positive, 0.7},
  {:signal_quality, :throughput, :positive, 0.9},
  {:temperature, :cpu_usage, :positive, 0.6}
]

updated_state = SnmpKit.SnmpSim.CorrelationEngine.apply_correlations(
  :interface_utilization, 0.8, device_state, correlations, DateTime.utc_now()
)

calculate_power_consumption_correlation(device_metrics, device_type)

@spec calculate_power_consumption_correlation(map(), atom()) :: float()

Model power consumption correlations with activity and temperature.

Power consumption correlates with:

  • CPU utilization
  • Network activity
  • Temperature (cooling requirements)

calculate_signal_throughput_correlation(snr_db, power_level_dbmv, max_throughput)

@spec calculate_signal_throughput_correlation(float(), float(), float()) :: float()

Calculate signal quality impact on throughput for DOCSIS devices.

Signal quality (SNR, power levels) directly affects achievable throughput in cable modem systems.

calculate_temperature_performance_correlation(temperature_celsius, equipment_type)

@spec calculate_temperature_performance_correlation(float(), atom()) :: %{
  cpu_impact: float(),
  signal_impact: float(),
  error_impact: float()
}

Calculate temperature impact on equipment performance.

Higher temperatures affect:

  • CPU performance (thermal throttling)
  • Signal quality (thermal noise)
  • Error rates (increased bit errors)

calculate_utilization_error_correlation(utilization_percent, interface_type)

@spec calculate_utilization_error_correlation(float(), atom()) :: float()

Calculate utilization impact on error rates.

Higher utilization typically leads to increased error rates due to:

  • Buffer overflows
  • Increased collision probability
  • Thermal effects

get_device_correlations(device_type)

@spec get_device_correlations(atom()) :: list()

Get standard correlation configurations for common device types.

Examples

correlations = SnmpKit.SnmpSim.CorrelationEngine.get_device_correlations(:cable_modem)