adaptive-timeout

Adaptive timeout calculation with EWMA-based tracking and fallback strategies.

Install

``
npm install adaptive-timeout
`

Usage

`js
const AdaptiveTimeout = require('adaptive-timeout')

const timeouts = new AdaptiveTimeout()

// Record a sample when you get a response
timeouts.put('10.0.0.1:8080', 150)

// Get timeout for next request (attempt 1, 2, 3...)
timeouts.get('10.0.0.1:8080', 1) // adaptive based on recorded samples
timeouts.get('unknown-peer', 1) // uses fallback strategy
`

API

#### const timeouts = new AdaptiveTimeout([options])

Create a new instance.

Options:

- maxSize - max cache entries (default: 65536)
- maxAge - entry TTL in ms (default: 600000 / 10 minutes)
- fallback - timeout sequence for unknown keys (default: [500, 750, 1000, 1500, 2000])
- min - minimum timeout for known keys (default: 300)
- max - maximum timeout for known keys (default: 5000)
- jitter - random jitter range in ms (default: 256)

#### timeouts.put(key, value)

Record a sample. Updates the exponentially weighted moving average.

Returns { avg, variance }.

#### timeouts.get(key, [attempt])

Get a timeout value.

For known keys: calculates adaptive timeout with linear backoff based on attempt number.

For unknown keys: returns value from fallback sequence based on attempt number.

#### timeouts.getValue(key)

Get raw stats for a key. Returns { avg, variance } or null.

#### timeouts.has(key)

Check if a key exists.

#### timeouts.delete(key)

Remove a key.

#### timeouts.clear()

Remove all entries.

#### timeouts.size

Number of entries.

How it works

Uses TCP-style EWMA (exponentially weighted moving average) to track values:

- avg blends 87.5% old + 12.5% new sample
- variance blends 75% old + 25% new deviation

Timeout for known keys: (avg + 2 variance) attempt + jitter`

Unknown keys use an aggressive fallback sequence to probe quickly.

License

Apache 2.0