Espresso-HF

Theobald, Michael; Nowick, Steven M.; Wu, Tao

doi:10.1145/240518.240533

Cited by 15 publications

(1 citation statement)

References 15 publications

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“…Network operators should consider this trade-off when choosing which method to use. In [18] the authors suggest SDN rule compression by following the concept of longest prefix matching with priorities using the Espresso [19] heuristic and show that their algorithm leads to 17% savings only. We succeed in reaching better compression ratios using MINNIE.…”

Section: Related Workmentioning

confidence: 99%

Minnie : An SDN world with few compressed forwarding rules

et al. 2017

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International audienceSoftware Defined Networking (SDN) is gaining momentum with the support of major manufacturers. While it brings flexibility to the management of flows within the data center fabric, this flexibility comes at the cost of smaller routing table capacities. Indeed, the Ternary Content-Addressable Memory (TCAM) needed by SDN devices has smaller capacities than CAMs used in legacy hardware. In this paper, we investigate compression techniques to maximize the utility of SDN switches forwarding tables. We validate our algorithm, called MINNIE, with intensive simulations for well-known data center topologies, to study its efficiency and compression ratio for a large number of forwarding rules. Our results indicate that MINNIE scales well, being able to deal with around a million of different flows with less than 1000 forwarding entries per SDN switch, requiring negligible computation time. To assess the operational viability of MINNIE in real networks, we deployed a testbed able to emulate a k = 4 Fat-Tree data center topology. We demonstrate on the one hand, that even with a small number of clients, the limit in terms of number of rules is reached if no compression is performed, increasing the delay of new incoming flows. MINNIE, on the other hand, reduces drastically the number of rules that need to be stored, with no packet losses, nor detectable extra delays if routing lookups are done in the Application-Specific Integrated Circuits (ASICs). Hence, both simulations and experimental results suggest that MINNIE can be safely deployed in real networks, providing compression ratios between 70% and 99%

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Section: Related Workmentioning

confidence: 99%

Minnie : An SDN world with few compressed forwarding rules

et al. 2017

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Highly Space Efficient Blacklisting

Kühnel

Meyer

2014

Advances in Intelligent Systems and Computing

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A Parallel State Assignment Algorithm for Finite State Machines

Bader

Madduri

2004

Lecture Notes in Computer Science

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Abstract. This paper summarizes the design and implementation of a parallel algorithm for state assignment of large Finite State Machines (FSMs). High performance CAD tools are necessary to overcome the computational complexity involved in the optimization of large sequential circuits. FSMs constitute an important class of logic circuits, and state assignment is one of the key steps in combinational logic optimization. The SMP-based parallel algorithm -based on the sequential program JEDI targeting multilevel logic implementation -scales nearly linearly with the number of processors for FSMs of varying problem sizes chosen from standard benchmark suites while attaining quality of results comparable to the best sequential algorithms.

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Espresso-HF

Cited by 15 publications

References 15 publications

Minnie : An SDN world with few compressed forwarding rules

Minnie : An SDN world with few compressed forwarding rules

Highly Space Efficient Blacklisting

A Parallel State Assignment Algorithm for Finite State Machines

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