Modeling of Wireless Traffic Load in Next Generation Wireless Networks

Software defined WiFi network (SD-WiFi) is a new paradigm that addresses issues such as mobility management, load management, route policies, link discovery, and access selection in traditional WiFi networks. Due to the rapid growth of wireless devices, uneven load distribution among the network res...

Full description

Saved in:
Bibliographic Details
Published in:Mathematical problems in engineering 2021, Vol.2021, p.1-15
Main Authors: Manzoor, Sohaib, Bajwa, Khalid Bashir, Sajid, Muhammad, Manzoor, Hira, Manzoor, Mahak, Ali, Nouman, Menhas, Muhammad Ilyas
Format: Article
Language:English
Subjects:
Algorithms
Controllers
Cryptography
Decision making
Digital signatures
Efficiency
Internet of Things
Load
Load distribution (forces)
Markov analysis
Markov chains
Mobility management
Optimization
Optimization algorithms
Performance evaluation
Response time
Servers
Software
Switches
Traffic models
Vibration
Wireless access points
Wireless networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Software defined WiFi network (SD-WiFi) is a new paradigm that addresses issues such as mobility management, load management, route policies, link discovery, and access selection in traditional WiFi networks. Due to the rapid growth of wireless devices, uneven load distribution among the network resources still remains a challenging issue in SD-WiFi. In this paper, we design a novel four-tier software defined WiFi edge architecture (FT-SDWE) to manage load imbalance through an improved handover mechanism, enhanced authentication technique, and upgraded migration approach. In the first tier, the handover mechanism is improved by using a simple AND operator and by shifting the association control to WAPs. Unauthorized user load is mitigated in the second tier, with the help of base stations (BSs) which act as edge nodes (ENs), using elliptic ElGamal digital signature algorithm (EEDSA). In the third tier, the load is balanced in the data plane among the OpenFlow enabled switches by using the whale optimization algorithm (WOA). Moreover, the load in the fourth tier is balanced among the multiple controllers. The global controller (GC) predicts the load states of local controllers (LCs) from the Markov chain model (MCM) and allocates packets to LCs for processing through a binary search tree (BST). The performance evaluation of FT-SDWE is demonstrated using extensive OMNeT++ simulations. The proposed framework shows effectiveness in terms of bandwidth, jitter, response time, throughput, and migration time in comparison to SD-WiFi, EASM, GAME-SM, and load information strategy schemes.
ISSN:1024-123X
1563-5147
DOI:10.1155/2021/7293093