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Joint Virtual Network Function Placement and Flow Routing in Edge-Cloud Continuum

  • Stony Brook University
  • University of Texas at Arlington

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Network Function Virtualization (NFV) is becoming one of the most popular paradigms for providing cost-efficient, flexible, and easily-managed network services by migrating network functions from dedicated hardware to commercial general-purpose servers. Despite the benefits of NFV, it remains a challenge to deploy Service Function Chains (SFCs), placing virtual network functions (VNFs) and routing the corresponding flow between VNFs, in the edge-cloud continuum with the objective of jointly optimizing resource and latency. In this paper, we formulate the SFC Deployment Problem (SFCD). To address this NP-hard problem, we first introduce a constant approximation algorithm for a simplified SFCD limited at the edge, followed by a promotional algorithm for SFCD in the edge-cloud continuum, which also maintains a provable constant approximation ratio. Furthermore, we provide an online algorithm for deploying sequentially-arriving SFCs in the edge-cloud continuum and prove the online algorithm achieves a constant competitive ratio. Extensive simulations demonstrate that on average, the total costs of our offline and online algorithms are around 1.79 and 1.80 times the optimal results, respectively, and significantly smaller than the theoretical bounds. In addition, our proposed algorithms consistently outperform the popular benchmarks, showing the superiority of our algorithms.

Original languageEnglish
Pages (from-to)872-886
Number of pages15
JournalIEEE Transactions on Computers
Volume73
Issue number3
DOIs
StatePublished - Mar 1 2024

Keywords

  • Network function virtualization
  • cloud computing
  • edge computing
  • joint resource and latency optimization
  • service function chain deployment

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