Authenticated Quality of Service Aware Routing in Software Defined Networks

2019 ◽  
pp. 110-127 ◽  
Author(s):  
Samet Aytaç ◽  
Orhan Ermiş ◽  
Mehmet Ufuk Çağlayan ◽  
Fatih Alagöz
Keyword(s):  
Quality Of Service ◽  
Software Defined Networks

scholarly journals A Survey on Machine Learning and Deep Learning based Quality of Service aware Protocols for Software Defined Networks

2021 ◽  
Author(s):  
Hiren Kumar Deva Sarma
Keyword(s):  
Machine Learning ◽  
Quality Of Service ◽  
Deep Learning ◽  
Service Level Agreement ◽  
Service Level ◽  
Future Research ◽  
Traffic Classification ◽  
Software Defined Networks ◽  
Research Issues

<p>Quality of Service (QoS) is one of the most important parameters to be considered in computer networking and communication. The traditional network incorporates various quality QoS frameworks to enhance the quality of services. Due to the distributed nature of the traditional networks, providing quality of service, based on service level agreement (SLA) is a complex task for the network designers and administrators. With the advent of software defined networks (SDN), the task of ensuring QoS is expected to become feasible. Since SDN has logically centralized architecture, it may be able to provide QoS, which was otherwise extremely difficult in traditional network architectures. Emergence and popularity of machine learning (ML) and deep learning (DL) have opened up even more possibilities in the line of QoS assurance. In this article, the focus has been mainly on machine learning and deep learning based QoS aware protocols that have been developed so far for SDN. The functional areas of SDN namely traffic classification, QoS aware routing, queuing, and scheduling are considered in this survey. The article presents a systematic and comprehensive study on different ML and DL based approaches designed to improve overall QoS in SDN. Different research issues & challenges, and future research directions in the area of QoS in SDN are outlined. <b></b></p>

Quality of Service in Software Defined Networks for Scientific Applications: Opportunities and Challenges

2020 ◽  
Vol 46 (8) ◽  
pp. 561-568
Author(s):  
J. E. Lozano-Rizk ◽  
R. Rivera-Rodriguez ◽  
J. I. Nieto-Hipolito ◽  
S. Villarreal-Reyes ◽  
A. Galaviz-Mosqueda ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Software Defined Networks ◽  
Scientific Applications

RESEARCH OF LOAD BALANCING PROCESSES IN SOFTWARE-DEFINED NETWORKS BASED ON GENETIC ALGORITHM

2021 ◽  
Vol 77 ◽  
pp. 43-57
Author(s):  
D. A. Perepelkin ◽  
◽  
V. T. Nguyen ◽  
Keyword(s):  
Genetic Algorithm ◽  
Quality Of Service ◽  
Load Balancing ◽  
Software Defined Networks ◽  
Network Congestion ◽  
Network Resources ◽  
Global View ◽  
Simulation Results ◽  
Required Quality

As a new network paradigm, software-defined networks (SDN) are able to cope with the limitations of traditional networks. SDNs use a management controller with a global view of the network and switching devices that act as packet forwarding equipment, known as «OpenFlow switches». Network resources limitations and ensuring quality of service requirements lead to an important need for load balancing between SDN switches. The purpose of work  research and analysis of load balancing processes in SDN based on genetic algorithm. To confirm the effectiveness and correctness of the genetic algorithm in SDN, the software for modeling the load balancing processes has been developed. The simulation results confirmed the efficiency of the genetic algorithm in SDN for balancing and redistributing network traffic in order to ensure the required quality of service and reduce network congestion.

scholarly journals SLA-driven Federated Cloud Networking: Quality of Service for Cloud-based Software Defined Networks

2014 ◽  
Vol 34 ◽  
pp. 655-660 ◽  
Author(s):  
Alexander Stanik ◽  
Marc Koerner ◽  
Leonidas Lymberopoulos
Keyword(s):  
Quality Of Service ◽  
Software Defined Networks ◽  
Cloud Networking
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