Fairness-Aware Dynamic Rate Control and Flow Scheduling for Network Utility Maximization in Network Service Chain

Lin Gu, Deze Zeng, Sheng Tao, Song Guo, Hai Jin, Albert Y. Zomaya, Weihua Zhuang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

44 Citations (Scopus)


Network function virtualization (NFV) decouples the traditional network functions from specific or proprietary hardware, such that virtualized network functions (VNFs) can run in software form. By exploring NFV, a consecutive set of VNFs can constitute a service function chain (SFC) to provide the network service. From the perspective of network service providers, how to maximize the network utility is always one of the major concerns. To this end, there are two main issues need to be considered at runtime: 1) how to handle the unpredictable network traffic burst? and 2) how to fairly allocate resources among various flows to satisfy different traffic demands? In this paper, we investigate a fairness-aware flow scheduling problem for network utility maximization, with joint consideration of resource allocation and rate control. Based on a discrete-time queuing model, we propose a low-complexity online-distributed algorithm using the Lyapunov optimization framework, which can achieve arbitrary optimal utility with different fairness levels by tuning the fairness bias parameter. We theoretically analyze the optimality of the algorithm and evaluate its efficiency by both simulation and testbed-based experiments.

Original languageEnglish
Article number8673789
Pages (from-to)1059-1071
Number of pages13
JournalIEEE Journal on Selected Areas in Communications
Issue number5
Publication statusPublished - 1 May 2019


  • fairness
  • flow scheduling
  • network utility maximization
  • NFV
  • rate control

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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