A TCAM-based Caching Architecture Framework for Packet Classification

Srinivasavarma, Vegesna S. M.; Vidhyut, Shiv; S, Noor Mahammad

doi:10.1145/3409109

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…Finally, there are a number of hardware-based methods for packet classification, the core idea of which is to exhaustively search all the rules in the rule set to get a matching result. Typical hardware-based solutions include ternary content addressable memory (TCAM) [22], field programmable gate array (FPGA) [23] and dedicated network processor chips. The data structure of exhaustive search algorithm is simple, but the classification efficiency based on hardware processing is high.…”

Section: Related Workmentioning

confidence: 99%

“…26. if d='0' then perform steps (22) in the R.eq interval; perform steps (19) in the R.ad interval; 27. ''included'': 28.…”

Section: Algorithm 4 Rule Updatementioning

confidence: 99%

“…33. if d='1' then perform steps (21) in the R.eq interval; perform steps (18) in the R.ad interval; 34. if d='0' then perform steps (22) in the R.eq interval; perform steps (19) in the R.ad interval; } //End of PruningTree(R, T , d) and if there is no overlap between the rule interval and the node interval of the decision tree on a certain dimension, then no pruning operation is required in subsequent dimensions. In addition, compared with the traditional decision tree-based classification method, the PcmSU method has another advantage: as the decision tree is divided into several subtrees, its scale must be reduced to a certain extent, which on the one hand reduces the complexity of decision tree reconstruction when rules are updated, and on the other hand, it also provides the foundation for distributed packet classification method [28], and improves the efficiency of packet classification.…”

Section: Algorithm 4 Rule Updatementioning

confidence: 99%

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PcmSU-A Packet Classification Method Supporting High-Speed Search and Fast Update

Cheng

Shi

2023

IEEE Access

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Packet classification is the core technology that underpins software-defined networking (SDN). With the rapid development of network applications, the increasing complexity of flow tables in SDN brings challenges to update and classification time. In order to achieve fast search and update at the same time, this article proposes a high-performance packet classification method PcmSU based on decision tree. The method optimizes the search and update process in the traditional decision tree-based classification method, and the classification efficiency of the constructed decision tree has been greatly improved compared with that before optimization. Based on the characteristics of the small interval, the reconstruction of the decision tree is greatly reduced and the rule update efficiency is improved. In addition, based on the characteristics of the decision tree constructed by this method, there is no need to consider the specific location and sequence number of rule updates when adding rules, which can avoid introducing rule conflicts. Experimental results show that the PcmSU method not only supports high-speed packet classification and linear memory consumption, but also has fast rule update speed.INDEX TERMS Packet classification, decision tree, SDN, rule update.

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Section: Related Workmentioning

confidence: 99%

“…26. if d='0' then perform steps (22) in the R.eq interval; perform steps (19) in the R.ad interval; 27. ''included'': 28.…”

Section: Algorithm 4 Rule Updatementioning

confidence: 99%

Section: Algorithm 4 Rule Updatementioning

confidence: 99%

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PcmSU-A Packet Classification Method Supporting High-Speed Search and Fast Update

Cheng

Shi

2023

IEEE Access

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“…Ref. [27] designs traffic-aware architecture, monitoring the temporal behavior of rules to update flow table caching in a timely manner.…”

Section: Flow Table Cachingmentioning

confidence: 99%

Reducing Flow Table Update Costs in Software-Defined Networking

Wang,

Yang,

Yang

et al. 2023

Sensors

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In software-defined networking (SDN), the traffic forwarding delay highly depends on the latency associated with updating the forwarding rules in flow tables. With the increase in fine-grained flow control requirements, due to the flexible control capabilities of SDN, more rules are being inserted and removed from flow tables. Moreover, the matching fields of these rules might overlap since multiple control domains might generate different rules for similar flows. This overlap implies dependency relationships among the rules, imposing various restrictions on forwarding entries during updates, e.g., by following update orders or storing entries at specified locations, especially in flow tables implemented using ternary content addressable memory (TCAM); otherwise, mismatching or packet dropping will occur. It usually takes a while to resolve and maintain dependencies during updates, which hinders high forwarding efficiency. To reduce the delay associated with updating dependent rules, in this paper, we propose an updating algorithm for TCAM-based flow tables. We formulate the TCAM maintenance process as an NP-hard problem and analyze the inefficiency of existing moving approaches. To solve the problem, we propose an optimal moving chain for single rule updates and provide theoretical proof for its minimum moving steps. For multiple rules arriving at a switch simultaneously, we designed a dynamic approach to update concurrent entries; it is able to update multiple rules heuristically within a restricted TCAM region. As the update efficiency concerns dependencies among rules, we evaluate our flow table by updating algorithms with different dependency complexities. The results show that our approach achieves about 6% fewer moving steps than existing approaches. The advantage is more pronounced when the flow table is heavily utilized and rules have longer dependency chains.

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TeRa: Ternary and Range based packet classification engine

M.,

2024

Integration

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A TCAM-based Caching Architecture Framework for Packet Classification

Cited by 6 publications

References 27 publications

PcmSU-A Packet Classification Method Supporting High-Speed Search and Fast Update

PcmSU-A Packet Classification Method Supporting High-Speed Search and Fast Update

Reducing Flow Table Update Costs in Software-Defined Networking

TeRa: Ternary and Range based packet classification engine

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