Cost-aware caching: optimizing cache provisioning and object placement in ICN

TL;DR

This paper introduces a cost-aware caching approach for ICN that optimizes cache size, object placement, and path selection to minimize retrieval costs, revealing that traditional hit-ratio maximization can be suboptimal.

Contribution

It presents two optimization models for cache provisioning in ICN that explicitly incorporate retrieval costs, along with a polynomial-time greedy algorithm and analytical proof of optimality.

Findings

Cost-aware caching reduces retrieval costs significantly.

Traditional hit-ratio maximization can lead to higher overall costs.

The proposed algorithms are proven to be optimal and efficient.

Abstract

Caching is frequently used by Internet Service Providers as a viable technique to reduce the latency perceived by end users, while jointly offloading network traffic. While the cache hit-ratio is generally considered in the literature as the dominant performance metric for such type of systems, in this paper we argue that a critical missing piece has so far been neglected. Adopting a radically different perspective, in this paper we explicitly account for the cost of content retrieval, i.e. the cost associated to the external bandwidth needed by an ISP to retrieve the contents requested by its customers. Interestingly, we discover that classical cache provisioning techniques that maximize cache efficiency (i.e., the hit-ratio), lead to suboptimal solutions with higher overall cost. To show this mismatch, we propose two optimization models that either minimize the overall costs or maximize the hit-ratio, jointly providing cache sizing, object placement and path selection. We formulate a polynomial-time greedy algorithm to solve the two problems and analytically prove its optimality. We provide numerical results and show that significant cost savings are attainable via a cost-aware design.