OpenFlow Based Load Balancing for Software-Defined Network Applications

Rofie, S. A. Mohamad; Ramli, I; Redzwan, K. N; Hassan, S. M. Mohd; Ibrahim, Marufat

doi:10.1166/asl.2018.10718

Cited by 6 publications

(2 citation statements)

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“…Then a dynamic algorithm is run to update the flow table considering the server utilization. The researchers in the SDN system utilizes a form of load balancing to provide network congestion management in [124] by finding the best path using Dijkstra's algorithm.…”

Section: B Artificial Intelligence Based Load Balancing Techniquesmentioning

confidence: 99%

A Systematic Review of Load Balancing Techniques in Software-Defined Networking

et al. 2020

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The traditional networks are facing difficulties in managing the services offered by cloud computing, big data, and the Internet of Things as the users have become more dependent on their services. Software-Defined Networking (SDN) has pulled enthusiasm in the integration process of technologies and function as per the user's requirements for both academia and industry, and it has begun to be embraced in actual framework usage. The emergence of SDN has given another idea to empower the focal programmability of the system. Because of the increasing demand and the scarcity of resources, the load balancing issue needs to be addressed efficiently to manage the incoming traffic and resources and to improve network performance. One of the most critical issues is the role of the controller in SDN to balance the load for having a better Quality of Service (QoS). Though there are few survey articles written on load balancing, there is no detail and systematic review conducted in load balancing in SDN. Hence, this paper extends and reviews the discussion with a taxonomy of current emerging load balancing techniques in SDN systematically by categorizing the techniques as conventional and artificial intelligence-based techniques to improve the service quality. The review also includes the study of metrics and parameters which have been used to measure the performance. This review would allow gaining more information on load balancing approaches in SDN and enables the researchers to fill the current research gaps.

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Section: B Artificial Intelligence Based Load Balancing Techniquesmentioning

confidence: 99%

A Systematic Review of Load Balancing Techniques in Software-Defined Networking

et al. 2020

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“…These switches can provide some limited services in addition to the switching functions. The SDN controller is able to configure and manage all deployed OF switches via a proper interface, i.e., any supported version of OF protocol [38]. The SDN controller employs a clustering algorithm introduced in Reference [39] so that each Fog node or a group of Fog nodes are associated with a distributed SDN controller.…”

Section: Sdn Operation and Integrationmentioning

confidence: 99%

Secure and Reliable IoT Networks Using Fog Computing with Software-Defined Networking and Blockchain

Muthanna

Ateya

Khakimov

et al. 2019

JSAN

118

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Designing Internet of Things (IoT) applications faces many challenges including security, massive traffic, high availability, high reliability and energy constraints. Recent distributed computing paradigms, such as Fog and multi-access edge computing (MEC), software-defined networking (SDN), network virtualization and blockchain can be exploited in IoT networks, either combined or individually, to overcome the aforementioned challenges while maintaining system performance. In this paper, we present a framework for IoT that employs an edge computing layer of Fog nodes controlled and managed by an SDN network to achieve high reliability and availability for latency-sensitive IoT applications. The SDN network is equipped with distributed controllers and distributed resource constrained OpenFlow switches. Blockchain is used to ensure decentralization in a trustful manner. Additionally, a data offloading algorithm is developed to allocate various processing and computing tasks to the OpenFlow switches based on their current workload. Moreover, a traffic model is proposed to model and analyze the traffic indifferent parts of the network. The proposed algorithm is evaluated in simulation and in a testbed. Experimental results show that the proposed framework achieves higher efficiency in terms of latency and resource utilization.

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An Efficient Fog‐Based Model for Secured Data Communication

Narayana

Patibandla

2021

Integration of Cloud Computing With Internet of Things

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OpenFlow Based Load Balancing for Software-Defined Network Applications

Cited by 6 publications

References 0 publications

A Systematic Review of Load Balancing Techniques in Software-Defined Networking

A Systematic Review of Load Balancing Techniques in Software-Defined Networking

Secure and Reliable IoT Networks Using Fog Computing with Software-Defined Networking and Blockchain

An Efficient Fog‐Based Model for Secured Data Communication

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