About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
Performance Evaluation Methodologies and Tools. 14th EAI International Conference, VALUETOOLS 2021, Virtual Event, October 30–31, 2021, Proceedings

Research Article

A TTL-based Approach for Content Placement in Edge Networks

Download(Requires a free EAI acccount)
3 downloads
Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-030-92511-6_1,
        author={Nitish K. Panigrahy and Jian Li and Faheem Zafari and Don Towsley and Paul Yu},
        title={A TTL-based Approach for Content Placement in Edge Networks},
        proceedings={Performance Evaluation Methodologies and Tools. 14th EAI International Conference, VALUETOOLS 2021, Virtual Event, October 30--31, 2021, Proceedings},
        proceedings_a={VALUETOOLS},
        year={2021},
        month={12},
        keywords={TTL cache Utility maximization Edge network},
        doi={10.1007/978-3-030-92511-6_1}
    }
    
  • Nitish K. Panigrahy
    Jian Li
    Faheem Zafari
    Don Towsley
    Paul Yu
    Year: 2021
    A TTL-based Approach for Content Placement in Edge Networks
    VALUETOOLS
    Springer
    DOI: 10.1007/978-3-030-92511-6_1
Nitish K. Panigrahy1,*, Jian Li2, Faheem Zafari3, Don Towsley1, Paul Yu4
  • 1: University of Massachusetts, Amherst
  • 2: Binghamton University, SUNY, Binghamton
  • 3: Imperial College London
  • 4: U.S. Army Research Laboratory, Adelphi
*Contact email: nitish@cs.umass.edu

Abstract

Edge networks are promising to provide better services to users by provisioning computing and storage resources at the edge of networks. However, due to the uncertainty and diversity of user interests, content popularity, distributed network structure, cache sizes, it is challenging to decide where to place the content, and how long it should be cached. In this paper, we study the utility optimization of content placement at edge networks through timer-based (TTL) policies. We propose provably optimal distributed algorithms that operate at each network cache to maximize the overall network utility. Our TTL-based optimization model provides theoretical answers to how long each content must be cached, and where it should be placed in the edge network. Extensive evaluations show that our algorithm outperforms path replication with conventional caching algorithms over some network topologies.

Keywords
TTL cache Utility maximization Edge network
Published
2021-12-08
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-92511-6_1
Copyright © 2021–2025 ICST
EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL