Minimizing Latency Due to Flow Table Overflow by Early Eviction of Flow Entries in SDN

Khan, Mohsin; Sah, Vibhav K.; Mudgal, Pradhumn; Hegde, S. M.

doi:10.1109/icccnt.2018.8493926

Cited by 9 publications

(6 citation statements)

References 10 publications

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“…Khan et al 15 Early eviction strategy using LRU policy Instantaneous Delay and Latency are decreased.…”

Section: Policy Approach Performancementioning

confidence: 99%

A novel eviction policy based on shortest remaining time for software defined networking flow tables

Dhandapani,

Thanganadar Thangathai,

Hamead Haja Moinudeen

2023

Int J Network Mgmt

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SummarySoftware defined networking is a modern paradigm that divides the control plane from the data plane for improved network manageability. A flow table in the data plane has limited and expensive memory called TCAM. The presence of unwanted flow rules would lead to flow bloat conditions and make the lookup operation inefficient. Eviction schemes based on LRU policy have been widely studied in the literature which preempts the life of the least recently used flow rule and reduces the occupancy of the flow table. LRU considers the past behavior for the eviction of a flow rule. This paper proposes a novel policy that preempts a flow rule by considering its future characteristic, the shortest remaining time (SRT). A rule with a higher probability of being used is avoided from eviction to mitigate the degradation of performance. The modeling of the SRT technique exhibits better utilization of a flow rule that has higher probability of being used. On the other hand, LRU does not guarantee that the evicted flow rule will not be used frequently in the future and it has been shown that an incorrectly evicted flow rule incurs controller delay. The experimental results show that for different traffic rates, SRT has reduced the delay by 15%, reinstallation count by 25%, and jitter by 40%. SRT has increased utilization by 22% compared to LRU.

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“…Khan et al 15 Early eviction strategy using LRU policy Instantaneous Delay and Latency are decreased.…”

Section: Policy Approach Performancementioning

confidence: 99%

A novel eviction policy based on shortest remaining time for software defined networking flow tables

Dhandapani,

Thanganadar Thangathai,

Hamead Haja Moinudeen

2023

Int J Network Mgmt

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“…At present, most researches on the flow table overflow of OpenFlow switch focus on how to solve the flow table overflow problem caused by large traffic flows in a normal network environment. For example, set an appropriate timeout value of flow entries to reduce the total number of flow entries in the flow table space [25][26][27]; balance the utilization of flow table space by redirecting flows from switches with high flow table space utilization to switches with sufficient free flow table space [28][29][30]; aggregate flow entries [31][32][33]; find out the most suitable flow entry to delete when the flow table space is in its saturation status [34][35][36].…”

Section: Security and Communication Networkmentioning

confidence: 99%

A Table Overflow LDoS Attack Defending Mechanism in Software-Defined Networks

Xie

Xing

Zhang

et al. 2021

Security and Communication Networks

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In order to achieve requirements such as fast search of flow entries and mask matching, OpenFlow hardware switches usually use TCAM to store flow entries. Limited by the capacity of TCAM, the current commercial OpenFlow switches can only support hundreds of thousands of flow entries, which makes SDN network using OpenFlow hardware switches vulnerable to the threat of flow table overflow attack. Among them, low-rate DoS (LDoS) attack against table overflow poses a serious threat to SDN networks due to its high attack efficiency and concealed flow, and it is also difficult to detect. In this regard, this paper analyzed two types of LDoS attack flow against table overflow and proposed an attack detection and defense mechanism named SAIA (Small-flow Analysis and Inport-flow Analysis) through the design of table overflow prediction and flow entries deletion strategy. Experiments conducted through the SDN network environment showed that SAIA can effectively detect and suppress LDoS attack flows in the flow table in large-scale network conditions and verified that the deployment of SAIA is lightweight. At the same time, SAIA implemented the flow entry deletion strategy based on LRU when the flow table overflows in a nonattack situation, which further enhances the stability of the network.

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“…To enable eviction in OpenFlow, one can learn from the conventional rule replacement used in computer memory management. When the flow table of switches is not enough to accommodate new flows, the SDN controller uses first-in-first-out (FIFO), random, and least recently used (LRU) concepts to actively remove less important or inactive rules like in the work of [14,15]. A prior study by Zarek et al [16] verified that LRU outperformed the other eviction method with better performance in terms of hit ratio.…”

Section: Eviction Mechanismmentioning

confidence: 99%

“…Thus, suitable eviction mechanisms are important to enable the removal of unused flow entries efficiently. Several eviction implementation logics are proposed in [14,15,24,25] and [26] to eliminate entries of lower importance to free space. Intuitively, these approaches implement first-in-first-out (FIFO) [23], random [19], and least recently used (LRU) [13,25] logic.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, the process of adding an entry (update operation) in the switch flow table is hard and very slow when the flow table is full to its capacity. As the capacity threshold is required to enable an eviction policy to remove unused entries as illustrated in Equation ( 11), an experimental prior study reports that when the flow table usage ratio reaches from 80% to its capacity, it may not give optimal performance [15]. Therefore, once the threshold is crossed, the eviction policy will be activated.…”

Section: Adaptive-hybrid Idle and Hard Timeout Allocation Algorithm (...mentioning

confidence: 99%

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Adaptive and Hybrid Idle–Hard Timeout Allocation and Flow Eviction Mechanism Considering Traffic Characteristics

et al. 2020

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Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traffics from the proliferation of the Internet of Thing (IoT) devices increase the processing load on the controller and generates an additional number of entries stored in the flow table. However, the switch flow table memory (TCAM) cannot accommodate many entries. Packets from multimedia flows are usually large in size and thus suffer processing delay and require more flow set up requests. The SDN controller may be overloaded and face some scalability problems because it supports a limited number of requests from switches. OpenFlow uses timeout configuration to manage flow setup request. The conventional fixed timeout cannot cope up with the dynamic nature of traffic flows. This paper controls the frequent flow setup requests by proposing an adaptive and hybrid idle–hard timeout allocation (AH-IHTA). The algorithm considers traffic patterns, flow table usage ratio, and returns appropriate the timeout to different flows. The performance evaluations conducted have shown a 28% and 39% reduction in the flow setup request and flow eviction, respectively.

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Minimizing Latency Due to Flow Table Overflow by Early Eviction of Flow Entries in SDN

Cited by 9 publications

References 10 publications

A novel eviction policy based on shortest remaining time for software defined networking flow tables

A novel eviction policy based on shortest remaining time for software defined networking flow tables

A Table Overflow LDoS Attack Defending Mechanism in Software-Defined Networks

Adaptive and Hybrid Idle–Hard Timeout Allocation and Flow Eviction Mechanism Considering Traffic Characteristics

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