A Ternary Unification Framework for Optimizing TCAM-Based Packet Classification Systems

Norige, Eric; Liu, Alex X.; Torng, Eric

doi:10.1109/tnet.2018.2809583

Cited by 26 publications

(10 citation statements)

References 38 publications

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“…Compressing rules with prefix-only wildcards has a very old and rich literature in IPv4 networks. To mention a few, we can indicate to one-dimensional solutions ( Draves et al, 1999 ; Rétvári et al, 2013 ), a two-dimensional approach ( Rottenstreich et al, 2013 ), and multidimensional approaches like TCAM unification framework ( Norige, Liu & Torng, 2013 ) and TCAM Razor ( Liu, Meiners & Torng, 2009 ). Further references could be found in Braun & Menth (2014a) .…”

Section: Related Workmentioning

confidence: 99%

WildMinnie: compression of software-defined networking (SDN) rules with wildcard patterns

Khanmirza¹

2022

PeerJ Computer Science

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Software-defined networking (SDN) enables fast service innovations through network programmability. In SDN, a logically centralized controller compiles a set of policies into the network-level rules. These rules are inserted in the TCAM memory of SDN-enabled switches enabling high-speed matching and forwarding of packets. Unfortunately, TCAMs are available in limited capacities and fall short of accommodating all intended rules, especially in networks with large distinct flows like datacenters. Rule compression is a technique that reduces the number of rules by aggregating them with some similarity factors. This paper introduces WildMinnie, a new rule compression method that aggregates rules based on their common address non-prefix wildcards derived from a group of rules with the same output port number. We explore rule conflict issues and provide solutions to resolve them. We demonstrate the capability of WildMinnie in various datacenter topologies with traffics having different diversity of source-destination addresses and show that WildMinnie outperforms the best-known compression method by 20%, on average.

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Section: Related Workmentioning

confidence: 99%

WildMinnie: compression of software-defined networking (SDN) rules with wildcard patterns

Khanmirza¹

2022

PeerJ Computer Science

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“…Anyway, the definition of such techniques requires to overcome two main limitations. The flow tables of the SDN switches are realized by means of TCAMs, which are known to have limited size [4], [5]. Moreover, the continuous polling performed by the SDN controller to collect traffic statistics on SDN switches, increases the signalling overhead and generates measurement inaccuracy due to the latency in the gathering phase [13], [14].…”

Section: Related Workmentioning

confidence: 99%

“…One of the main issues in the process of measuring the TM using SDN rules counters is the limited size, in terms of number of installed rules, of the Ternary Content Addressable Memories (TCAMs) used to build the flow tables of SDN switches [4], [5]. Taking this constraint into account, authors of [6] define the flow spread parameter as a quantitative indicator of the most attracting flows to be measured.…”

Section: Introductionmentioning

confidence: 99%

A Scalable and Error-Tolerant Solution for Traffic Matrix Assessment in Hybrid IP/SDN Networks

Galán-Jiménez

Polverini

Cianfrani

2020

IEEE Trans. Netw. Serv. Manage.

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The advent of the Software Defined Networking (SDN) paradigm represents a great opportunity for the definition of new network management solutions. In this work, we focus on the definition and implementation of a novel technique to solve the Traffic Matrix Assessment (TMA) problem from the perspective of an Internet Service Provider. Since the migration from legacy IP networks to fully-deployed SDN ones needs to be incremental due to budget and technical constraints, this paper proposes a mixed measurement and estimation scalable solution for hybrid IP/SDN networks to accurately solve the TMA problem by exploiting the availability of flow rule counters in SDN switches. The performance evaluation shows that our error-tolerant solution is able to assess the TM with a negligible estimation error by only measuring a small percentage of traffic flows, overcoming other state-of-the-art algorithms proposed in the literature. Moreover, the performance analysis of the proposed implementation using the OpenDaylight controller over an emulated network environment, shows that a trade-off between the quality of the assessed TM and its impact on the network in terms of control messages to be sent can be found by properly tuning the number of measured flows.

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“…A large number of solutions are devoted to optimize the usage of the TCAMs in SDN switches [16], [17]. The aim of these proposals is to reduce, as much as possible, the memory space required to store a set of flow rules.…”

Section: Tcam Size Limitationmentioning

confidence: 99%

“…It is assumed that all the SDN switches can host the same number of rules, i.e., they have the same TCAM size. Since real TCAMs are able to store a range between 2000 and 4000 rules [16], TCAM size is set to 2000 rules in the simulations. Four SFs are considered: Firewall (FW), Intrusion Detection System (IDS), Network Address Translator (NAT) and Proxy.…”

Section: Performance Evaluationmentioning

confidence: 99%

Dynamic In-Network Classification for Service Function Chaining ready SDN networks

Polverini

Galán-Jiménez

Lavacca

et al. 2019

2019 10th International Conference on Networks of the Future (NoF)

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Service Function Chaining (SFC) paradigm consists in steering traffic flows through an ordered set of Service Functions (SFs) so that to realize complex end to end services. SFC architecture introduces all the logical functions that need to be developed in order to provide the required service. The SFC overlay infrastructure can be built on top of many different underlay network technologies. The high flexibility and centrally controlled feature of Software Defined Networking (SDN), make SDN networks to be a perfect underlay to build the SFC architecture. Due to Ternary Content Address Memory (TCAM) limited size, SDN switches have a limitation in the number of flow rules that can be hosted. This constraint is particularly penalizing in case of the SFC classifier function, since it requires to manage a high number of different flows. The limitation imposed by the TCAM size on the SFC classifier can be a bottleneck for the number of SFC requests that the SDN-based SFC architecture can handle. In this paper we define the Dynamic Chain Request Classification Offloading (D-CRCO) problem, as the one of maximizing the number of accepted SFC requests, having the possibility of: i) implement the SFC classifier also in a node that is internal to the SDN-based SFC domain, and ii) install classification rules in a reactive fashion. Furthermore, we propose the Dynamic Nearest Node (DNN) heuristic to solve the D-CRCO problem. Performance evaluation shows that by using DNN heuristic it is possible to triple the number of accepted requests, with respect to existing solutions.

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A Ternary Unification Framework for Optimizing TCAM-Based Packet Classification Systems

Cited by 26 publications

References 38 publications

WildMinnie: compression of software-defined networking (SDN) rules with wildcard patterns

WildMinnie: compression of software-defined networking (SDN) rules with wildcard patterns

A Scalable and Error-Tolerant Solution for Traffic Matrix Assessment in Hybrid IP/SDN Networks

Dynamic In-Network Classification for Service Function Chaining ready SDN networks

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