TY  - JOUR
T1  - Packet Switching Data Congestion Control Techniques using Artificial Intelligence
AU - Fasiku, A.I. AU - Ojedayo, B. AU - Obasanya, T.D. AU - Adetan, O. AU - Oyinloye, O.E. 
JO  - Asian Journal of Information Technology
VL  - 20
IS  - 2
SP  - 41
EP  - 48
PY  - 2021
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2021.41.48
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2021.41.48
KW  - Network
KW  -congestion
KW  -ANN
KW  -MATLAB
KW  -C-sharp
AB  - Network technology is very popular now
because most offices and households use the internet for
communication and carry out their day-to-day
transactions. With the present high demand for internet
users, they may experience congestion because of the
increase in the number of users and demand on the
network. Hence, controlling congestion for
packet-switched data on the wired and wireless network
using an artificial intelligence technique is very important
to replace the current TCP protocols. This research used
the neural network technique to realize this goal by
training the model with some data set values which its
result was later compared with the predicted result. This
research works demonstrate great potential to control
congestion for packet-switched on both wired and
wireless networks. MATLAB was used for both the
training of genetic programming and the ANN simulation
for the prediction. When the message sent is higher than
the capacity of the router, it can cause congestion.
Therefore, this application is designed to be installed on
the server to control congestion before its occurrence and
congestion prediction. If some of the packets are queuing
up, the application controls it by passing a message to the
sender that congestion is about to occur along with the
link. Therefore, the sender adjusts the speed of
transmitting packets by reducing the level of the message
the sender is sending and the flow of packets is then
regulated.
ER  -