CloudSimSDN‐NFV: Modeling and simulation of network function virtualization and service function chaining in edge computing environments. (22nd October 2019)

• Record Type: Journal Article
• Authors: Son, Jungmin; He, TianZhang; Buyya, Rajkumar
• Is Part Of: Software, practice & experience. Volume 49:Number 12(2019)
• Page Start: 1748
• Page End: 1764
• Publication Date: 2019-10-22
• Subjects: cloud computing -- edge computing -- network function virtualization (NFV) -- service function chaining (SFC) -- simulation software -- software‐defined clouds -- software‐defined networking (SDN); Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2755
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: Software‐defined networking (SDN) has evolved and brought an innovative paradigm shift in computer networks by utilizing a programmable software controller with open protocols. Network functions, previously served on dedicated hardware, have shifted to network function virtualization (NFV) that enabled functions to be virtualized and provisioned dynamically upon generic hardware. In addition to NFV, edge computing utilizes the edge resources close to end‐users, which can reduce the end‐to‐end service delay and the network traffic volume. Although these innovative technologies gained significant attention from both academia and industry, there are limited tools and simulation frameworks for the effectiveness evaluation in a repeatable and controllable manner. Furthermore, large‐scale experimental infrastructures are expensive to setup and difficult to maintain. Even if they are created, they are not available or accessible for the majority of researchers throughout the world. In this paper, we propose a framework for simulating NFV functionalities in both edge and cloud computing environments. In addition to the basic network functionalities supported by SDN in CloudSimSDN, we added new NFV features, such as virtualized network functions allocation, migration, and autoscaling with the support of corresponding network functionalities, such as flow load balancing, rerouting, and service function chaining (SFC) maintenance. We evaluated our simulation framework with autoscaling and placement policies for SFC in the integrated edge and cloud computing environments. The results demonstrate its effectiveness in measuring and evaluating the end‐to‐end delay, response time, resource utilization, network traffic, and power consumption with different algorithms in each scenario.