Analysis of TTL-based Cache Networks - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2012

Analysis of TTL-based Cache Networks

Abstract

Many researchers have been working on the performance analysis of caching in Information-Centric Networks (ICNs) under various replacement policies like Least Recently Used (LRU), FIFO or Random (RND). However, no exact results are provided, and many approximate models do not scale even for the simple network of two caches connected in tandem. In this paper, we introduce a Time-To-Live based policy (TTL), that assigns a timer to each content stored in the cache and redraws the timer each time the content is requested (at each hit/miss). We show that our TTL policy is more general than LRU, FIFO or RND, since it is able to mimic their behavior under an appropriate choice of its parameters. Moreover, the analysis of networks of TTL-based caches appears simpler not only under the Independent Reference Model (IRM, on which many existing results rely) but also with the Renewal Model for requests. In particular, we determine exact formulas for the performance metrics of interest for a linear network and a tree network with one root cache and N leaf caches. For more general networks, we propose an approximate solution with the relative errors smaller than 0.001 and 0.01 for exponentially distributed and constant TTLs respectively.
Fichier principal
Vignette du fichier
choungmo_ttlcachenets2012.pdf (267.09 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00760915 , version 1 (05-12-2012)

Identifiers

  • HAL Id : hal-00760915 , version 1

Cite

Nicaise Eric Choungmo Fofack, Philippe Nain, Giovanni Neglia, Don Towsley. Analysis of TTL-based Cache Networks. ValueTools - 6th International Conference on Performance Evaluation Methodologies and Tools - 2012, Oct 2012, Cargèse, France. ⟨hal-00760915⟩
175 View
266 Download

Share

Gmail Facebook X LinkedIn More