A Study of Biology-Based Congestion Control Algorithms for Wireless Sensor Network

Network Traffic is one of the major issues in wireless Sensor Networks (WSNs). WSN is a self-constructed and organization less wireless networks which is used to observe and check the physical or environmental conditions and to cooperatively pass their data through the network to a sink where the data can be appropriately observed and examined. Number of research works in wireless sensor networks (WSNs) is primarily focused on improving the network performance along with enhancing the quality of service parameters such as the data arrival rate, available bandwidth, congestion, transmission rate, queue length and energy. Various natural computational algorithms have been proposed for overcoming these issues. In this paper we have discussed about some of the bio-based algorithms such as Genetic Algorithms, Simulated Annealing, Ant Colony Optimization, Particle Swarm Optimization, Firefly Algorithm, etc. to control congestion in wireless sensor networks.