Generation and collection of data for normal and conflicting flows in software defined network flow table

Khairi, Mutaz H. H.; Ariffin, Sharifah Hafizah Syed; Latiff, N. M. Abdul; Yusof, Kamaludin Mohamad

doi:10.11591/ijeecs.v22.i1.pp307-314

Cited by 7 publications

(8 citation statements)

References 23 publications

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“…The Topo.py application established the topology of the switches and hosts. Similar topologies have been used in previous studies on SDN conflict flows, including those undertaken to pursue knowledge [18,20,[22][23].…”

Section: B Sdn Topologymentioning

confidence: 99%

“…Conflict prediction identifies unwanted system behavior, and prediction-related capabilities should be incorporated based on the evaluation of the prediction model to ensure practical control applications. In [18], cross-layering between flow components was investigated using OpenFlow table variables, and an accurate approach was recommended by analyzing the entire input table.…”

Section: Introductionmentioning

confidence: 99%

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Utilizing Extremely Fast Decision Tree (EFDT) Algorithm to Categorize Conflict Flow on a Software-Defined Network (SDN) Controller

Khairi,

Ali Abdalla,

Hassan

et al. 2024

Eng. Technol. Appl. Sci. Res.

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Software-Defined Networks (SDNs) provide a contemporary approach to networking technology, offering a versatile and dynamically efficient network architecture for enhanced surveillance and performance. However, SDN architectures may encounter flow conflicts. These conflicts arise when modifications are made to specific flow properties, such as priority, match field, and action. Despite the existence of recommended solutions, the process of resolving conflicts in SDN continues to encounter difficulties. This study proposes an Extremely Fast Decision Tree (EFDT) classification technique to detect and categorize conflicts inside the flow table. The novelty of this method is based on the development of an accurate and effective machine-learning technique implemented on the Ryu controller plane and validated using the Mininet simulator. The effectiveness and efficiency of the proposed method were evaluated using various indicators, demonstrating superior performance in recognizing and categorizing conflict flow types in all flow sizes ranging from 10,000 to 100,000.

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Section: B Sdn Topologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Utilizing Extremely Fast Decision Tree (EFDT) Algorithm to Categorize Conflict Flow on a Software-Defined Network (SDN) Controller

Khairi,

Ali Abdalla,

Hassan

et al. 2024

Eng. Technol. Appl. Sci. Res.

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“…It has been utilized as a hybrid and combined with other techniques due to its excellent features and ability to adapt to the changing environment. Some of such studies are references [43][44][45].…”

Section: Recent Trends and Future Research Tendency In Lb And Routingmentioning

confidence: 99%

A Survey on Load Balancing, Routing, and Congestion in SDN

Mousa¹,

Abdullah²

2022

ETJ

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 Categorizeing existing approaches along with their features exposes promising techniques and future directions' suggestions.  This work surveys and categorizes existing load balance, routing, and congestion solutions.  The investigated metrics of previous works are statically analyzed so as to highlight the most important factors that should be evaluated.  Enhancing network performance and AIbased approaches are the highest investigated topics in the last 6 years.High traffic could result in load imbalance or network congestion, which degrades the network's performance and efficiency. Thus, it is crucial to adopt efficient routing and load balancing models to face these challenging issues.Additionally, when investigating a new approach, it is essential to consider the most important metrics to evaluate this potential approach precisely. This paper presents an intensive analysis of recently available SDN-based load balancing and routing techniques. Furthermore, the features and issues of each technique are stated. Moreover, the most important metrics that should be evaluated are statically analyzed. Also, a brief survey of available network congestion solutions is shown. Additionally, taxonomies of available load balancing, routing techniques, and congestion solutions are presented. Finally, we shed light on the trends, promising techniques, and future directions' suggestions that could be utilized further in research. Investigating SDN-based research published by wellknown academic publishers in the last six years shows that enhancing network performance and AI-based approaches are the highest investigated topics with 28% and 27%, respectively, of the total investigated issues. Other topics took lower percentages. As far as we know, this study is the first work that jointly surveys and categorizes all existing approaches in the field of decreasing delay and congestion in SDN-based networks

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“…The SDN controller uses messages to communicate and exchange information with the underlying switches [18]. The RESTCONF APIs provided by OF plugin are OF topology, OF statistics, and OF programming.…”

Section: Openflow Protocolmentioning

confidence: 99%

BG-SDN: A Big Graph Framework for Topology Modeling and Traffic Analysis in Large-Scale SDN

Samaan

Jeiad

2022

Preprint

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This paper presented a new method of modeling a Software Defined Networking (SDN) network as a graph and importing traffic data into the created graph using graph techniques to speed up the computations required in traffic analysis and management. For this purpose, a specialized application named TMTA (Topology Modeling and Traffic Analysis) is created to model the SDN network topology as a graph and feed the created graph with traffic data. To achieve high performance, the TMTA application is integrated with the Neo4j graph database utilizing its ability to store and process big graphs consisting of massive amounts of highly interconnected data in a scalable and reliable manner. For performance evaluation, various sizes of network topologies ranging from 41 to 62,586 devices are modeled using the TMTA application and stored in Neo4j. Evaluation results show that the proposed big graph framework can handle large-scale topologies effectively and perform traffic analysis tasks, i.e., calculating the control score of each device in the network and finding the shortest path between devices in a very reasonable time.

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Generation and collection of data for normal and conflicting flows in software defined network flow table

Cited by 7 publications

References 23 publications

Utilizing Extremely Fast Decision Tree (EFDT) Algorithm to Categorize Conflict Flow on a Software-Defined Network (SDN) Controller

Utilizing Extremely Fast Decision Tree (EFDT) Algorithm to Categorize Conflict Flow on a Software-Defined Network (SDN) Controller

A Survey on Load Balancing, Routing, and Congestion in SDN

BG-SDN: A Big Graph Framework for Topology Modeling and Traffic Analysis in Large-Scale SDN

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