JOURNAL ARTICLE

An Ensembled Scheme for QoS-Aware Traffic Flow Management in Software Defined Networks

Abstract

In recent times, smart communities such as-smart grid, smart healthcare, and smart manufacturing units consists of large number of connected devices equipped with advanced processing and communication capabilities. The focus of these smart communities have shifted towards the use of intelligent processing and control for providing better quality of service (QoS) to the end user domain. To support this aspect, software defined networking (SDN) is being widely deployed in different domains such as-data center networks, fog/edge computing, smart grid, and vehicular networks. The variable requirements of different applications in smart communities make it necessary to deploy flexible and scalable SDN. The dynamic flow management capability of SDN has lots of potential that needs to be effectively explored in order to provide QoS guarantee for traffic generated from different smart applications. In this direction, in this paper, an ensembled scheme for QoS-aware traffic flow management in SDN is designed. The proposed scheme works in three phases: 1) a linear ordering scheme for dependency removal of the incoming packets is designed, 2) an application-specific traffic classification scheme is designed, and 3) a queue management scheme is designed for efficient scheduling of traffic flow. The proposed scheme is evaluated over an experimental setup. The results obtained shows that the proposed scheme behaves effectively with respect to different QoS parameters.

Keywords:
Computer science Quality of service Computer network Software-defined networking Traffic classification Smart grid Scalability Distributed computing Network packet Scheduling (production processes) Scheme (mathematics) Traffic flow (computer networking) Engineering

Metrics

37
Cited By
7.00
FWCI (Field Weighted Citation Impact)
18
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Software-Defined Networks and 5G
Physical Sciences →  Computer Science →  Computer Networks and Communications
Smart Grid Security and Resilience
Physical Sciences →  Engineering →  Control and Systems Engineering
Network Time Synchronization Technologies
Physical Sciences →  Computer Science →  Computer Networks and Communications
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