Delay-Aware Routing in Software-Defined Networks Via Network Tomography and Reinforcement Learning

Xu Tao, Doriana Monaco, Alessio Sacco, Simone Silvestri, Guido Marchetto

Research output: Contribution to journalArticlepeer-review

Abstract

Numerous network management tasks in Software-defined networking (SDN) infrastructures, such as routing, resource allocation, and service placement, heavily depend on obtaining an accurate view of the network state. However, monitoring individual network elements incurs substantial overhead and often proves infeasible. To address this challenge, <italic>network tomography</italic> has emerged as a promising approach, capable of inferring the internal network state using end-to-end metrics observed by a limited set of nodes acting as monitors. Despite its potential, previous research in network tomography has not considered specific network management objectives and corresponding challenges, resulting in unsatisfactory performance. In this paper, we propose <italic>Subito</italic> (Shortest Path Routing with Multi-armed Bandits and Network Tomography), which integrates network tomography and <italic>reinforcement learning</italic> within software-defined networks to address the specific needs and challenges of delay-aware <italic>shortest path routing</italic>&#x2013;a cornerstone of various network management tasks. By harnessing the capabilities of network tomography and reinforcement learning, Subito efficiently learns routing strategies with bounded regret, achieves minimal monitoring overhead, and maintains stable routing. Extensive experimental evaluations on synthetic networks and the GENI testbed show significant performance improvements of Subito versus two state-of-the-art approaches.

Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalIEEE Transactions on Network Science and Engineering
DOIs
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
IEEE

Keywords

  • Delays
  • Measurement
  • Monitoring
  • Multi-armed Bandits
  • Network Tomography
  • Reinforcement Learning
  • Reinforcement learning
  • Routing
  • Shortest Path Routing
  • Software-Defined Networking
  • Task analysis
  • Tomography

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Delay-Aware Routing in Software-Defined Networks Via Network Tomography and Reinforcement Learning'. Together they form a unique fingerprint.

Cite this