In-switch dynamic flow aggregation in software defined networks

Chao, Tzu-Yu; Wang, Kuochen; Wang, Lichun; Lee, Chain-Wu

doi:10.1109/icc.2017.7997429

Cited by 11 publications

(7 citation statements)

References 6 publications

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“…Other solutions [88] [89] [90] focus on aggregating the number of flows with similar features going to the same destination to reduce the number of flows operation. An Integer Linear Programming model (ILP) was introduced in [89] to minimize the total cost.…”

Section: A Routing With Flows Operations Awarementioning

confidence: 99%

Dynamic Routing and Failure Recovery Approaches for Efficient Resource Utilization in OpenFlow-SDN: A Survey

et al. 2022

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Software Defined Networks (SDN) is a new network paradigm that emerged to offer better network management through the separation of network control logic and data forwarding element. This separation speed up network innovation without the need to rely on the vendor-proprietary interface for network element configuration to forward packets. However, SDN is flow driven network, for each arrived flow, a feasible path is computed to forward the flow to its destination. Afterward, the SDN control logic process the corresponding routing and instruct the set of data forwarding elements to install them on their Flowtable to guide the routing process. Unfortunately, the network changes more frequently in dynamic large-scale networks and the Flowtable is a constraint with limited space. These challenges require the SDN controller to compute paths more often which may also need a large number of flow routing rules placement. In addition, the frequency of communication link failures increases lately. The successful deployment of SDN heavily depends on how it satisfies the reliability requirement with uninterrupted services. Several studies were conducted to compute the optimal path for data forward to meet their Quality of Service demand. Other studies focus on reducing the frequency of link failure. Some studies were conducted to manage the constraint Flowtable resources. This survey focuses on Routing rules placement, unoptimized routing, link, and switch load balancing, failure detection, and recovery. The paper extensively discusses each issue and analyzes the weakness of the current solutions. Finally, it highlights potential challenges that need future research attention.

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Section: A Routing With Flows Operations Awarementioning

confidence: 99%

Dynamic Routing and Failure Recovery Approaches for Efficient Resource Utilization in OpenFlow-SDN: A Survey

et al. 2022

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“…The scheme leverages on bit weaving and removes bit swapping to construct BST of non-prefix flow entries to improve the execution time. It was observed that some rules are unaggregatable, therefore FFTA misses the potential opportunity of aggregating such flow entries [66]. Moreover, as the size of the network increase, it will be computationally expensive.…”

Section: Flow Rule Aggregationmentioning

confidence: 99%

“…To address the shortcoming of FTRS, Chao et al [66] proposed an in-switch dynamic flow aggregation (IDFA) mechanism as a switch application to avoid the link between the switch to the controller. IDFA adds redundant flow entries insertion and verification to dynamically adjust and aggregate entries based on a threshold value.…”

Section: Flow Rule Aggregationmentioning

confidence: 99%

Software Defined Networking Flow Table Management of OpenFlow Switches Performance and Security Challenges: A Survey

et al. 2020

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Software defined networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane. The data plane is composed of forwarding elements called switches and the control plane is composed of controllers. SDN is gaining popularity from industry and academics due to its advantages such as centralized, flexible, and programmable network management. The increasing number of traffics due to the proliferation of the Internet of Thing (IoT) devices may result in two problems: (1) increased processing load of the controller, and (2) insufficient space in the switches’ flow table to accommodate the flow entries. These problems may cause undesired network behavior and unstable network performance, especially in large-scale networks. Many solutions have been proposed to improve the management of the flow table, reducing controller processing load, and mitigating security threats and vulnerabilities on the controllers and switches. This paper provides comprehensive surveys of existing schemes to ensure SDN meets the quality of service (QoS) demands of various applications and cloud services. Finally, potential future research directions are identified and discussed such as management of flow table using machine learning.

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“…In order to achieve dependable result, the simulation is run 1000 times for each number of flow entries generated randomly. Here compression ratio is the number of entries after reduction to that of original entries [8,32]. Therefore, lower compression ratio means more entries are aggregated.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Among the main issues with SDN such as switch designs [8,9], distributed controller platforms [10,11], resilient communication [12,13], and security [14,15], flow table management is one of the primary tasks directly influencing the performance. From OpenFlow 1.3 [16,17], there were several improvements including multiple flow tables (MFT).…”

Section: Introductionmentioning

confidence: 99%

Entry Aggregation and Early Match Using Hidden Markov Model of Flow Table in SDN

Wang

Youn

2019

Sensors

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The usage of multiple flow tables (MFT) has significantly extended the flexibility and applicability of software-defined networking (SDN). However, the size of MFT is usually limited due to the use of expensive ternary content addressable memory (TCAM). Moreover, the pipeline mechanism of MFT causes long flow processing time. In this paper a novel approach called Agg-ExTable is proposed to efficiently manage the MFT. Here the flow entries in MFT are periodically aggregated by applying pruning and the Quine–Mccluskey algorithm. Utilizing the memory space saved by the aggregation, a front-end ExTable is constructed, keeping popular flow entries for early match. Popular entries are decided by the Hidden Markov model based on the match frequency and match probability. Computer simulation reveals that the proposed scheme is able to save about 45% of space of MFT, and efficiently decrease the flow processing time compared to the existing schemes.

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In-switch dynamic flow aggregation in software defined networks

Cited by 11 publications

References 6 publications

Dynamic Routing and Failure Recovery Approaches for Efficient Resource Utilization in OpenFlow-SDN: A Survey

Dynamic Routing and Failure Recovery Approaches for Efficient Resource Utilization in OpenFlow-SDN: A Survey

Software Defined Networking Flow Table Management of OpenFlow Switches Performance and Security Challenges: A Survey

Entry Aggregation and Early Match Using Hidden Markov Model of Flow Table in SDN

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