Adaptive uplink scheduling model for WiMAX network using evolutionary computing model

Title

Adaptive uplink scheduling model for WiMAX network using evolutionary computing model

Creator

Mahesh D.S.; Chandramouli H.; Chitnis S.R.

Description

The increased usage of smart phones has led to increase usage an internet based application services. These application requires different quality of service (QoS) and bandwidth requirement. WiMAX is an efficient network to provision high bandwidth connectivity and coverage to end user. To meet QoS requirement the exiting model used adaptive model selection scheme. However, these model induce bandwidth wastage as it does not considers any feedback information for scheduling. This work present an Adaptive Uplink Scheduling (AUS) by optimizing MAC layer using Multi-Objective Genetic Algorithm (MOGA). The MAC scheduler use feedback information from both physical layer and application layer. Further, to meet QoS requirement of application and utilize bandwidth efficiently this paper presented an adaptive modulation selection scheme based on user application requirement using MOGA. Our model provides application level based QoS provisioning for WiMAX network. Experiment are conducted to evaluate performance of AUS over exiting model. The overall result attained shows AUS model attain good performance in term of throughput, successful packet transmission and packet collision. 2019 Institute of Advanced Engineering and Science. All rights reserved.

Source

Indonesian Journal of Electrical Engineering and Computer Science, Vol-14, No. 3, pp. 1345-1355.

Date

2019-01-01

Publisher

Institute of Advanced Engineering and Science

Subject

Evolutionary computing; Genetic algorithm; Modulation; Multi-objective; WiMAX

Coverage

Mahesh D.S., Department of CSE, Faculty of Engineering, CHRIST (Deemed to be University), India; Chandramouli H., Department of CSE, East Point College of Engineering, India; Chitnis S.R., Department of CSE, Dayananda Sagar University, India

Rights

All Open Access; Hybrid Gold Open Access

Relation

ISSN: 25024752

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijeecs.v14.i3.pp1345-1355

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065627579&doi=10.11591%2fijeecs.v14.i3.pp1345-1355&partnerID=40&md5=d5ceee88deda22033908a871cba46fe4