Dynamic adjustment for proactive flow installation mechanism in SDN-based IoT

Cai, Yun Zhan; Wang, Yu Ting; Tsai, Meng-Hsun

doi:10.1016/j.comnet.2021.108167

Cited by 5 publications

(1 citation statement)

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“…Once a matching failure occurs, it will take longer to establish new entries along the forwarding path, which would lead to further congestion and packet loss. Proactive approaches, e.g., [18][19][20], help reduce packet-forwarding latency with traffic prediction and estimation. However, it limits the controller's ability to dynamically react to changes in the network traffic [21], and it does not alleviate issues related to new entry establishment latency.…”

Section: Related Workmentioning

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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