Defining Priority Metrics and Implementing Dynamic Chunk Scheduling

To transcend generic preloading, Tier 2 systems must define **priority metrics** grounded in content criticality, user engagement signals, and fetch efficiency.

**Priority Dimensions:**

| Metric | Definition | Implementation Example |
|———————|—————————————————————————|————————————————|
| Content Criticality | How central a component is to core user goals (e.g., hero product, CTAs) | Assign score 1–5; higher = preload sooner |
| Engagement Signal | Real-time user behavior: scroll depth, hover, click history | Use fetch weights updated via service worker analytics |
| Fetch Efficiency | Estimated load time, bandwidth cost, and cache availability | Prioritize cached first, then fresh with low size|

**Priority-Based Chunk Scheduling via Service Workers**
Service workers act as central orchestration layers, parsing component metadata and scheduling preloads conditionally. A minimal implementation:

// service-worker.js
const priorityQueue = new PriorityQueue((a, b) => a.priority – b.priority);

const registerPriorityPreload = (component, priority) => {
priorityQueue.enqueue({ component, priority });
processQueue();
};

const processQueue = () => {
while (!priorityQueue.isEmpty()) {
const { component, priority } = priorityQueue.dequeue();
const networkInfo = getCurrentNetworkConditions();
if (networkInfo.speed > THRESHOLD && !isCached) {
fetch(component).then(res => res.arrayBuffer()).then(buffer => {
const blob = new Blob([buffer], { type: ‘application/javascript’ });
preloadComponent(blob, component);
});
}
}
};

This framework decouples preload logic from static manifests, enabling dynamic, context-aware resource fetching.

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