An Adaptive Rendering and Data Orchestration Model for High-Scale Mobile and Web Application Platforms

Abstract

Delivering a consistent, high-performance user experience (UX) across diverse network conditions, device capabilities, and application states remains a formidable challenge for high-scale web and mobile platforms. Traditional rendering strategies (purely client-side or server-side) fail to dynamically optimize resource consumption and latency. This paper proposes the Adaptive Rendering and Data Orchestration Model (ARDOM), a novel architecture that dynamically adjusts content delivery strategy based on real-time client context. ARDOM employs a Client Context Evaluator (CCE) to assess three primary vectors—network bandwidth, device capability (CPU/RAM), and user intent—and dictates the optimal rendering approach (Client-Side Rendering - CSR, Server-Side Rendering - SSR, or Streaming/Progressive Rendering - PR). Central to the model is a Decoupled Data Orchestrator (DDO) which prefetches and prioritizes data based on the chosen rendering mode and projected user needs. The empirical evaluation demonstrates that ARDOM achieves up to a $65\%$ reduction in Time-to-Interactive (TTI) for low-end devices on constrained networks (simulating 3G connectivity) compared to a pure CSR baseline, and a $25\%$ reduction in server load compared to a pure SSR baseline, establishing a verifiable blueprint for optimizing cross-platform performance and resource efficiency.