Traffic Aware Clustering for Congestion Control in Future Wireless Sensor Networks

As data traffic exceeds the total capacity of the channel, congestion in wireless sensor networks (WSNs) has become a pressing problem in the current setting. Overflowing the buffer at each receiving sensor node causes packet drops, decreases the packet delivery ratio, and degrades the throughput of the network because retransmitting each unacknowledged packet is not an optimal energy solution for resource-constrained nodes. One of the most popular methods to reduce node power consumption and increase throughput in WSNs is routing, which is based on heuristics rather than algorithms because the routing problem is NP-hard and heuristics work better than traditional approaches. Considering the connection energy, packet loss rate, and congestion level, the forward ant constructs a number of congestion-free paths from the source to the sink node, and the backward ant calculates the number of successful paths traveling from the sink to the source node. When determining the best route to take, Huffman coding takes into account the percentage of packets dropped along each of several possible routes found through ant colony optimization. Ultimately, simulation findings show that the proposed approach outperforms state-of-the-art methods with respect to average energy consumption, latency, throughput, and packet delivery ratio.