Development of an Intelligent Fuzzy-Based Algorithm for Data Congestion Management Scheme in Wireless LAN
J.C. Ochi1, C.O. Ohaneme2, A.C.O. Azubog3
1Josiah C. Ochi, Department of Electronic and Computer Engineering, Nnamdi Azikiwe University, Awka Anambra State Nigeria.
2Dr. Cletus O. Ohaneme, Department of Electronic and Computer Engineering, Nnamdi Azikiwe University, Awka Anambra State Nigeria.
3Dr. Augustine C.O. Azubog, Department of Electronic and Computer Engineering, Nnamdi Azikiwe University, Awka Anambra State Nigeria.
Manuscript received on 13 October 2015 | Revised Manuscript received on 22 October 2015 | Manuscript Published on 30 October 2015 | PP: 15-26 | Volume-5 Issue-5, October 2015 | Retrieval Number: C2168085315/15©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Network congestion control remains a critical issue and a high priority, especially given the growing size, demand, and speed (bandwidth) of the increasing wireless services. Congestion control is the problem of managing network traffic or a network state where the total demand for resources such as bandwidth among the competing users exceeds the available capacity. This paper presents a fuzzy logic approach to congestion mitigation in TCP oriented network using University of Nigeria Nsukka (UNN) situated at the South-Eastern part of Nigeria as a case study. Using a deductive study mechanism, an intelligent fuzzy-based algorithm for the congestion management is developed while showing a validation analysis plot of the proposed scheme in relation to other TCP variants such as TCP Tahoe, TCP Reno, TCP-New Reno, TCP Vegas and TCP selective acknowledgments (SACKs), i.e.TCP-TRONVS. From the implementation of the proposed scheme, it was observed that a significant improvement in the Quality of service (QoS) metrics (such as latency, throughput, buffer utilization, and packet Loss Ratio) for users is practically feasible.
Keywords: Network Congestion, Latency, Packet Loss, Buffer Utilization, Throughput.
Scope of the Article: Data Analytics