cs 15(4): e2

Research Article

On the Performance of General Cache Networks

Download136 downloads
  • @ARTICLE{10.4108/icst.valuetools.2014.258168,
        author={Nicaise CHOUNGMO FOFACK and Mostafa DEHGHAN and Don TOWSLEY and Misha BADOV and Dennis L. GOECKEL},
        title={On the Performance of General Cache Networks},
        journal={EAI Endorsed Transactions on Cloud Systems},
        volume={1},
        number={4},
        publisher={EAI},
        journal_a={CS},
        year={2015},
        month={2},
        keywords={performance analysis, approximation algorithms, cache networks, lru, fifo, random, time-to-live (ttl)},
        doi={10.4108/icst.valuetools.2014.258168}
    }
    
  • Nicaise CHOUNGMO FOFACK
    Mostafa DEHGHAN
    Don TOWSLEY
    Misha BADOV
    Dennis L. GOECKEL
    Year: 2015
    On the Performance of General Cache Networks
    CS
    EAI
    DOI: 10.4108/icst.valuetools.2014.258168
Nicaise CHOUNGMO FOFACK1,*, Mostafa DEHGHAN2, Don TOWSLEY2, Misha BADOV2, Dennis L. GOECKEL2
  • 1: Orange Labs
  • 2: University of Massachusetts at Amherst
*Contact email: nicaise.choungmofofack@orange.com

Abstract

The performance evaluation of cache networks has gain a huge attention due to content-oriented delivery technologies. If general network topologies are more realistic than hierarchical networks widely studied in the literature, their analysis is significantly challenging. Existing models mainly focus on trees where content custodians are located at the root and the one-way child-to-parent request forwarding schema is common. In this paper, we consider complex and irregular networks where requests may flow possibly in opposite directions from/to several sources/destinations. Moreover, we assume that caches may run one of Time-To-Live (TTL)-based policies recently introduced for content-centric networks and modern Domain Name System [5]. We then derive an analytical framework and a polynomial-time algorithm that approximate accurately performance metrics of arbitrary graph-based and heterogeneous TTL-based cache networks. Simulations show that our simplified methodology may accurately predict metrics of interest on networks of caches running popular replacement algorithms (e.g. LRU, FIFO, or Random) without restricting its scope of application to this interesting use case. Unlike existing approaches, ours scales as network and content catalog sizes increase.