Multi-Tenancy- and Redundancy-Aware In-Network Aggregation using Programmable Switches

Sol Han, Hochan Lee, Subin Han, Heewon Kim, Sangheon Pack

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Recent advances in programmable switches make it possible to aggregate data in partition-aggregation applications (e.g., MapReduce applications) at programmable switches. However, a well-designed aggregation scheme is indispensable for aggregating as much data as possible under the limited resources of programmable switches in an environment where multiple applications are running concurrently. In this article, we propose a multi-tenancy and redundancy-aware in-network aggregation (MARINA) scheme that preferentially aggregates highly redundant data at a programmable switch and improves aggregation performance by constructing a multi-tenancy-aware aggregation tree. Evaluation results demonstrate that MARINA can improve data aggregation performance by up to 81 percent compared with the conventional approach using statically partitioned resources and sequential aggregation.

Original languageEnglish
Pages (from-to)94-100
Number of pages7
JournalIEEE Network
Volume37
Issue number3
DOIs
Publication statusPublished - 2023 May 1

Bibliographical note

Publisher Copyright:
© 1986-2012 IEEE.

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications

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