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Traffic-Aware Placement of Network Function Virtualization (NFV) in Cloud Environment: Issues and Open Challenges

by Nadim Rana, Zeba Khan, Javed Azmi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 85
Year of Publication: 2026
Authors: Nadim Rana, Zeba Khan, Javed Azmi
10.5120/ijca2026926371

Nadim Rana, Zeba Khan, Javed Azmi . Traffic-Aware Placement of Network Function Virtualization (NFV) in Cloud Environment: Issues and Open Challenges. International Journal of Computer Applications. 187, 85 ( Feb 2026), 8-18. DOI=10.5120/ijca2026926371

@article{ 10.5120/ijca2026926371,
author = { Nadim Rana, Zeba Khan, Javed Azmi },
title = { Traffic-Aware Placement of Network Function Virtualization (NFV) in Cloud Environment: Issues and Open Challenges },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2026 },
volume = { 187 },
number = { 85 },
month = { Feb },
year = { 2026 },
issn = { 0975-8887 },
pages = { 8-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number85/traffic-aware-placement-of-network-function-virtualization-nfv-in-cloud-environment-issues-and-open-challenges/ },
doi = { 10.5120/ijca2026926371 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-02-26T16:48:45.347051+05:30
%A Nadim Rana
%A Zeba Khan
%A Javed Azmi
%T Traffic-Aware Placement of Network Function Virtualization (NFV) in Cloud Environment: Issues and Open Challenges
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 85
%P 8-18
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Network Function Virtualization (NFV) marks a fundamental shift in how network services are designed and deployed by separating network functions from proprietary hardware and running them as software on standard cloud infrastructures. While NFV provides flexibility, scalability, and cost savings, the performance of virtualized services depends heavily on the placement of Virtual Network Functions (VNFs), especially under changing and diverse traffic patterns. Poor placement can lead to increased packet delay, inefficient resource utilization, and breaches of service-level agreements. This paper offers a thorough analysis of traffic-aware VNF placement in cloud and hybrid cloud–edge settings. This study reviews current NFV placement methods, including Integer Linear Programming (ILP), Binary Integer Programming (BIP), mixed-integer models, heuristic algorithms, and recent AI-driven approaches, and discusses their advantages and limitations with respect to traffic management, latency, scalability, and computational demand. Emphasis is placed on how traffic features, service chaining, and deployment architecture affect placement choices. Additionally, the paper explores how analytics and intelligent orchestration can improve VNF placement decisions. It proposes a tool-supported framework that leverages historical traffic data, Microsoft Azure infrastructure, and the Open Network Automation Platform (ONAP) to improve placement strategies. Finally, the paper identifies key research gaps, challenges, and issues, including handling traffic fluctuations, multi-objective optimization, cloud–edge coordination, security concerns, and the explanation of AI-based solutions. This work serves as a reference for researchers and practitioners interested in developing scalable, traffic-aware, and deployable NFV placement solutions.

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Index Terms

Computer Science
Information Sciences

Keywords

Network Function Virtualization (NFV) Virtualized Network Function (VNF) Binary Integer Programming (BIP) Network Automation Platform (ONAP)

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