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World Journal of Engineering
Research and Technology

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.218

ICV : 79.45

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Abstract

THE IMPACT OF PEOPLE MOVEMENT ON THE THROUGHPUT OF WI-FI NETWORKS AND THE SIGNIFICANT CHANGES THAT AFFECT WLAN PERFORMANCE BY NO CLUSTERING OR GROUPING &WITH CLUSTERING & MOBISIM V3 SOFTWARE TO MODEL THE J N T UNIVERSITY HYDERABAD INDIA

Seyed Amin Ahmadi Olounabadi*, Prof. Avula. Damodaram and
Prof. V Kamakshi Prasad

ABSTRACT

The use of network technologies and facilities has always been explored by users, researchers and experts .One of the issues that the network has to deal with, how to send and receive, and network communications. In this research, we are looking at how people are moving on the throughput of Wi-Fi networks and the significant changes that affect WLAN performance. We examined the background of the research and related protocols, we were trying to model the Jawaharlal Nehru Technological University Hyderabad in India. In conducting research, we concluded that the behavior of moving network nodes can be examined in two model (1) No Clustering or grouping (2) Clustering and grouping. In our study, with two methods without any grouping and with grouping and clustering and we proved that the use of clustering or grouping algorithms in the model of Jawaharlal Nehru Technological University Hyderabad, India, Optimizes network utilization and can provide better quality and better bandwidth. One of the reasons for this quality is the lower number of packets dropped. The delivery rate of packets for clustering or grouping was clearly better in all four scenarios, and better intelligence packets arrived at destination, about 10% of packet delivery rates were improved. Throughput in all four scenarios is far better than that without grouping or clustering; this difference was well seen, on average, we saw something close to 33 percent better (grouping and clustering). The average end-to-end delay criterion was not debatable, since it was somewhat better in terms of grouping and clustering, and in some cases without it, and sometimes even worse, at a lower rate, we lost an average of 10%, which is, of course, entirely dependent on the nodes' movement has been and is not reliable, but it is still a better result.

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