6th International Conference on Performance Evaluation Methodologies and Tools

Research Article

Analysis of TTL-based Cache Networks

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  • @INPROCEEDINGS{10.4108/valuetools.2012.250250,
        author={CHOUNGMO FOFACK Nicaise Eric and NAIN Philippe and NEGLIA Giovanni and TOWSLEY Don},
        title={Analysis of TTL-based Cache Networks},
        proceedings={6th International Conference on Performance Evaluation Methodologies and Tools},
        keywords={information centric networks caches ttl renewal theory},
  • CHOUNGMO FOFACK Nicaise Eric
    NAIN Philippe
    NEGLIA Giovanni
    Year: 2012
    Analysis of TTL-based Cache Networks
    DOI: 10.4108/valuetools.2012.250250
CHOUNGMO FOFACK Nicaise Eric1,*, NAIN Philippe2, NEGLIA Giovanni2, TOWSLEY Don3
  • 1: Université de Nice Sophia Antipolis; Inria Sophia Antipolis Méditerranée
  • 2: Inria Sophia Antipolis Méditerranée
  • 3: University of Massachusetts at Amherst
*Contact email: nicaise.choungmo_fofack@inria.fr


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 under 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 $10^{-3}$ and $10^{-2}$ for exponentially distributed and constant TTLs respectively.