TY - EJOUR
AU - Farahani, Shoorangiz Shams Shamsabad
PY - 2024
DA - February
TI - Soft Computing-Based Congestion Control Schemes in Wireless Sensor Networks: Research Issues and Challenges
T2 - Majlesi Journal of Electrical Engineering
VL - 15
L1 - https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/soft-computing-based-congestion-control-schemes-in-wireless-sensor-networks-research-issues-and-challenges/
DO - 10.52547/mjee.15.1.39
N2 - Wireless Sensor Networks (WSNs) are a special class of wireless ad-hoc networks where their performance is affected by different factors. Congestion is of paramount importance in WSNs. It badly affects channel quality, loss rate, link utilization, throughput, network life time, traffic flow, the number of retransmissions, energy, and delay. In this paper, congestion control schemes are classified as classic or soft computing-based schemes. The soft computing-based congestion control schemes are classified as fuzzy logic-based, game theory-based, swarm intelligence-based, learning automata-based, and neural network-based congestion control schemes. Thereafter, a comprehensive review of different soft computing-based congestion control schemes in wireless sensor networks is presented. Furthermore, these schemes are compared using different performance metrics. Finally, specific directives are used to design and develop novel soft computing-based congestion control schemes in wireless sensor networks.
IS - 1
PB - OICC Press
KW - Wireless Sensor Networks (WSNs), Soft Computing, Neural network, Game Theory, fuzzy logic, Learning Automata, Congestion control 
EN -