International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 183 - Number 1 |
Year of Publication: 2021 |
Authors: Imeh J. Umoren, Samuel B. Okon |
10.5120/ijca2021921238 |
Imeh J. Umoren, Samuel B. Okon . A Multidimensional Fuzzy Knowledge-based System for Optimizing Wireless Local Area Networks Performance. International Journal of Computer Applications. 183, 1 ( May 2021), 8-19. DOI=10.5120/ijca2021921238
With the dawn of Wireless Local Area Networks (WLAN), network operators of third generation (3G) and fourth generation (4G) networks can properly address traffic requirements through subscribers and hotspot locations. Primarily, a significant aspect to consider is the issue of performance leading to Quality of Service (QoS) of mobile data networks allow subscribers to experience seamless and ubiquitous services as well as very high data rates. In this paper, we study the existing problem of network degradation which impact the provision of such seamless connectivity. In network performance, most indicators for performance optimization, includes Packet loss, Packet delay and Jitter (PLPDJ. As wireless networks evolve, demand for information services with high reliability, quick response times (QRT) and ubiquitous connectivity continues to upsurge rapidly. These issues are commonly affected by wireless networks inherent variances from wireline networks. Hence, network traffic metrics; latency, packet Loss and packet delay in certain wireless environments experienced some challenges in networks performance. To overcome these challenges, we consider network performance optimization techniques and proposed a framework using Type 1 Fuzzy knowledge-based approach for efficient WLAN performance. First, a performance measures on a typical wireless local area network with IP address 102.89.2.166 was carried out for a period of twenty-one (21) days based on specified performance metrics. Results shows that the average latency on a given WLAN was 11399ms (0.19m) as compared to jitter which was 1076ms (0.017m). Again, the download speed was established at 191.46Mbs compared to Upload speed which was at 35.7Mbps. Secondly, we obtain statistical operational field data and carried out simulation with the proposed model. Results indicates a minimization on congestions on the representative network environment which shows efficient network performance. Consequently, the evaluation carried out with Triangular Membership Functions (TMF) demonstrates an optimized WLAN Performance with QOS provisioning.