Compressing forwarding tables for datacenter scalability

Ori Rottenstreich, Marat Radan, Yuval Cassuto, Isaac Keslassy, Carmi Arad, Tal Mizrahi, Yoram Revah, Avinatan Hassidim

Research output: Contribution to journalArticlepeer-review


With the rise of datacenter virtualization, the number of entries in the forwarding tables of datacenter switches is expected to scale from several thousands to several millions. Unfortunately, such forwarding table sizes would not fit on-chip memory using current implementations. In this paper, we investigate the compressibility of forwarding tables. We first introduce a novel forwarding table architecture with separate encoding in each column. It is designed to keep supporting fast random accesses and fixed-width memory words. Then, we show that although finding the optimal encoding is NP-hard, we can suggest an encoding whose memory requirement per row entry is guaranteed to be within a small additive constant of the optimum. Next, we analyze the common case of two-column forwarding tables, and show that such tables can be presented as bipartite graphs. We deduce graph-theoretical bounds on the encoding size. We also introduce an algorithm for optimal conditional encoding of the second column given an encoding of the first one. In addition, we explain how our architecture can handle table updates. Last, we evaluate our suggested encoding techniques on synthetic forwarding tables as well as on real-life tables.

Original languageEnglish
Article number140113
Pages (from-to)138-151
Number of pages14
JournalIEEE Journal on Selected Areas in Communications
Issue number1
StatePublished - Jan 2014


  • Compression
  • Datacenter virtualization
  • Forwarding information base
  • Layer-2 datacenter

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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