Revisiting Cache Freshness for Emerging Real-Time Applications

TL;DR

This paper examines the limitations of TTL-based caching for real-time applications and proposes an adaptive policy to improve data freshness, addressing the gap between traditional caching and the needs of emerging real-time systems.

Contribution

It introduces a novel adaptive caching policy that enhances data freshness for real-time applications, overcoming TTL limitations.

Findings

Adaptive policy improves data freshness in real-time scenarios

Traditional TTL caching is insufficient for emerging real-time applications

Proposed method balances cache freshness and performance

Abstract

Caching is widely used in industry to improve application performance by reducing data-access latency and taking the load off the backend infrastructure. TTLs have become the de-facto mechanism used to keep cached data reasonably fresh (i.e., not too out of date with the backend). However, the emergence of real-time applications requires tighter data freshness, which is impractical to achieve with TTLs. We discuss why this is the case, and propose a simple yet effective adaptive policy to achieve the desired freshness.