A Framework For Using Network Virtualization Functions For Video Streams

Subject Areas : Intelligent Multimedia Processing and Communication Systems (IMPCS)

Ali Asghar  Khavasi ¹ (Principal Lecturer, Centria University of Applied Sciences, Finland)

Received: 2021-02-01 Accepted : 2021-05-24 Published : 2020-12-21

Keywords: Service Performance Chain, CloudSim, Virtual Network Functions, Software-defined networking, Video Streams,

Abstract :

Introduction: This paper investigates a way to stream online videos using SDN / NFV that can help to reduce latency and packet loss and cost. This method reduces Capex and Opex costs due to its software and low hardware dependency. Software-centric networks and virtualization of network functions have been introduced in the computer networks arena as a new way to design, deploy and manage network services. Those can provide more flexible and more flexible and adaptable to the consumer and provider according to the needs of end users and service providers to consolidate and deliver network components using standard IT virtualization technologies. This paper presents the architecture and prototype of a video streaming service compatible with SDN / NVF-enabled networks, allowing simplified networking and applications and reduced management costs.Method: The simulation framework of this paper conforms to the MANO architecture to implement the standard NFV evaluation method. In CloudSim, each simulation occurs by sending and receiving events between modules.Results: As expected, NoScale-Min policies in both LFF and MFF methods lead to exceptionally long response times due to resource shortages in VNFs. On the other hand, the delay of the NoScale-Max policy is short due to resource constraints enough is assigned to the VNF.Discussion: In this paper, we proposed CloudSimSDN-NFV as a framework for new simulation tool of video streams to evaluate NFV features in edge and cloud environments along with other features of SDN and cloud computing environments. This framework is designed and developed on CloudSimSDN. We describe the modeling and simulation of NFV and edge computing and the detailed design and implementation of our framework. Two used scenarios were presented to help understand how to use the new tool, and several algorithms were implemented and evaluated based on the framework.

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