A Model for Congestion Mitigation in Long-Term Evolution  Networks Using Traffic Shaping

A Model for Congestion Mitigation in Long-Term Evolution Networks Using Traffic Shaping

Oyebode Aduragbemi

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Kuyoro Shade O.

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Babcock University

A Model for Congestion Mitigation in Long-Term Evolution Networks Using Traffic Shaping

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Abstract

Long-Term Evolution (LTE) has evolved the field of data transmission, bringing about the era of 4th Generation Networks capable of providing broadband speeds to mobile users based on the development experienced in the field of data transmission. There has been a sporadic increase in the utilization of Long-Term Evolution (LTE) networks, due to the ever-growing utilization of network links and network services, certain issues begin to rise, one of such issues is the problem of congestion. The more utilized a network becomes, the more vulnerable it is to congestion. Data networks become congested when network cannot keep up with the growing demand for the networks resources. The focus of this work is on proposing a model to mitigate the effects of congestion on Long-Term Evolution (LTE) networks. The model was evaluated using the NS-2 network simulator and Network Utilization, Network Delay, Throughput metrics would be used to evaluate the efficiency of the model. The enhanced model performed better and more efficiently than previous solutions, offering a better way to mitigate the effects of congestion in Long-Term Evolution networks.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Oyebode Aduragbemi. 2018. \u201cA Model for Congestion Mitigation in Long-Term Evolution Networks Using Traffic Shaping\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 18 (GJCST Volume 18 Issue E2).

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GJCST Volume 18 Issue E2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-E Classification C.2.1

C.2.3

Submission ReceivedDecember 10, 2017
Peer Review Double Blind
Handling Editor
Accepted January 1, 2018
Published January 15, 2018

Version of record

v1.2

Issue date

May 2, 2018

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Article Matrices

Total Score: 102

Country: Nigeria

Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security

Authors: Kuyoro Shade O., Oyebode Aduragbemi (PhD/Dr. count: 0)

View Count (all-time): 308

Total Views (Real + Logic): 6074

Total Downloads (simulated): 1578

Publish Date: 2018 05, Wed

Monthly Totals (Real + Logic):

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Total Views: 6074

Total Downloads: 1578

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