A Bio-Inspired Territorial Predator Scent Marking Algorithm in Software-Defined Data Center

Data centre networks are intended to meet the data transmission needs of the data centre’s highly networked hosts. The network architecture and routing technique can have a major impact on performance parameters such as latency. The fat-tree network is now one of the most popular data centre network architectures. In recent times, data centre network traffic has been steadily expanding. Because of the high volume of traffic, it is nearly impossible for a single server to satisfy all the client’s requests. In this paper, a bio-inspired Territorial Predator Scent Marking Algorithm (TPSMA) is proposed for load balancing in a fat-tree software-defined data centre. The bio-inspired algorithm was developed to increase network Quality of Service (QoS). The proposed technique is validated using the network emulator Mininet, with the Open Network Operating System ONOS controller. The performance study conducted showed that the throughput and network utilization were improved, hence improving the QoS.