Traffic aware dynamic load distribution in the Data Plane of SDN using Genetic Algorithm: A case study on NSF network

Bhowmik, Chaitali; Gayen, Tirthankar

doi:10.1016/j.pmcj.2022.101723

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…The properties of switches play critical roles in implementing forwarding actions in adherence to the specified forwarding rules. This separation of control and data planes determines the main difference between SDN and traditional networking paradigms, presenting more significant flexibility, programmability, and scalability [8].…”

Section: Data Planementioning

confidence: 99%

“…When the SDN design relies on a centralized entity, it becomes vulnerable to a single point of failure. If the controller crashes, most network functionalities, including traffic monitoring, will be disrupted, and security measures will be compromised [8]. The nature of a single controller makes it ineffective in handling significant network traffic.…”

Section: Features That Make the Sdn Environment Vulnerable To Various...mentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Intrusion Detection Systems based Machine Learning Approaches Applied to Software-Defined Networks (SDN): Research Issues and Challenges

Janabi,

Kanakis,

Johnson

2023

Preprint

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: Cybersecurity has become a critical area in the digital field in recent years. The expansion of networks has revolutionised the way network structures are organised and managed. However, with increased connectivity and the growing complexity of modern networks, the threat of cyber-attacks has become more intense. As technology continues to advance, it brings both opportunities and challenges. One of the major challenges is the need to secure networks and sensitive data from various malicious activities. Traditional networks have evolved to include Software Defined Network (SDN), which offers a more flexible and programmable framework. Researchers should focus on detecting attacks in SDN because SDN networks are becoming more popular and attractive targets for clients due to their programmability and dynamic nature. The centralised controller, known as the backbone of an SDN, becomes a single point of failure and a potential target for attackers if not properly secured. Researchers need to emphasise the detection of attacks in SDN in order to mitigate these risks. By understanding the potential vulnerabilities and attack methods specific to SDN, researchers can develop effective detection approaches and propose countermeasures. This methodology helps protect the network from potential threats and minimises the impact of successful attacks. Therefore, this survey paper provides a review of Intrusion Detection Systems (IDSs) in Software-Defined Networks (SDN) to provide a thorough understanding of SDN security issues.

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Section: Data Planementioning

confidence: 99%

Section: Features That Make the Sdn Environment Vulnerable To Various...mentioning

confidence: 99%

A Survey of Intrusion Detection Systems based Machine Learning Approaches Applied to Software-Defined Networks (SDN): Research Issues and Challenges

Janabi,

Kanakis,

Johnson

2023

Preprint

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“…Throughput performance was not evaluated. Load equalization was accomplished through utilization of a genetic algorithm [26]. The GA entails a selection process, crossover and mutation for estimating the optimal load balancing among the controllers.…”

Section: Load Balancing In Control Planementioning

confidence: 99%

An Adaptive Symmetrical Load Balancing Scheme for Next Generation Wireless Networks

Manzoor,

Mazhar,

Binaris

et al. 2023

Symmetry

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In dense Wi-Fi networks, achieving load balancing is critical to optimize network utilization and provide equitable network consumption among the users. Traditional Wi-Fi networks have issues in attaining effective load balancing. Software-Defined Networking (SDN) has presented a viable solution by isolating the data plane and control plane, enabling more agile and cost-effective networks. In this paper we put forward an Adaptive Symmetrical Load Balancing (ASLB) scheme to ensure fairness of load symmetry in Software Defined Wi-Fi Networks (SD-Wi-Fi), while also optimizing the flows transition process using an Analytical Hierarchal Process (AHP). User activity is monitored by access points (APs), which operate under OpenFlow standards. Three essential features, packet volume, packet category and delay hindrance, are used for flow assignment to various controllers. The controllers are arranged in two tiers, universal and regional controllers. The universal controller (UC) handles the workload statistics of regional controllers (RC) in the form of clusters. Extensive simulations using OMNeT++ simulator are performed. The performance parameters taken into consideration are throughput, delay, packet loss rate, network transition count and workload distribution. Our findings demonstrate that the ASLB technique effectively optimizes the network utilization and ensures equitable network consumption among the end users. The proposed scheme outperforms the Mean Probe Delay scheme (MPD), Channel Measurement-based Access Selection scheme (CMAS), Received Signal Strength Indicator-based scheme (RSSI) and Distributed Antenna Selection scheme (DASA), being 40% higher in throughput and 25% lower in delay.

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Dynamic Load Balancing Schemes for Software-Defined Networking (SDN)

Baniya,

Nand,

Bhushan

2024

Algorithms for Intelligent Systems

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Traffic aware dynamic load distribution in the Data Plane of SDN using Genetic Algorithm: A case study on NSF network

Cited by 6 publications

References 39 publications

A Survey of Intrusion Detection Systems based Machine Learning Approaches Applied to Software-Defined Networks (SDN): Research Issues and Challenges

A Survey of Intrusion Detection Systems based Machine Learning Approaches Applied to Software-Defined Networks (SDN): Research Issues and Challenges

An Adaptive Symmetrical Load Balancing Scheme for Next Generation Wireless Networks

Dynamic Load Balancing Schemes for Software-Defined Networking (SDN)

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