ACSRO: Adaptive cuckoo search based rate adjustment for optimized congestion avoidance and control in wireless sensor networks

Several sensor nodes in the wireless network collect the data rigorously which aids in many of the applications. The network with high and the consistent data load is the only requirement of the wireless sensor networks. Due to the limited sources of the network and the high data loads, networks may be affected by congestion. Congestion is a highly objectionable issue which leads to information loss and the deprived performance of the wireless sensor networks. In this paper, an adaptive cuckoo search based optimal rate adjustment (ACSRO) for the congestion avoidance and control is proposed. The rate adjustment regulates the share rate of the node to mitigate the congestion. The performance of the proposed rate optimization approach is evaluated using the evaluation metrics such as throughput, delay, normalized packet loss, normalized queue size, and congestion level. The results of the proposed rate optimization show that the congestion is compacted and the performance of the WSN is improved.