Improving Quality of Service in Cloud Environments through Dynamic Load Balancing Strategies

Abstract

Improving Quality of Service (QoS) in that of the cloud environments is a very much critical challenge as a result of the dynamic and heterogeneous nature of that of the cloud resources and workloads. Dynamic load balancing techniques play a pivotal position in addressing this venture by means of dispensing workloads efficiently throughout available assets in real-time. This paper explores several dynamic load balancing techniques, together with Round Robin, Least Connections, Weighted Round Robin, Dynamic Least Load, and Hybrid Load Balancing, highlighting their benefits and disadvantages. It emphasizes the importance of non-stop tracking and facts series to ensure the greatest beneficial resource utilization and performance. By enforcing powerful load balancing algorithms, strategically putting load balancers, and making sure scalability and fault tolerance, cloud environments can collect more acceptable performance, reliability, and scalability. The integration of AI and system gaining knowledge of predictive load balancing and the adoption of vicinity computing and self-sufficient load balancers are identified as promising future instructions. Despite the inherent complexities and overheads related to dynamic load balancing, its importance in preserving QoS in cloud environments cannot be overstated, making it a vital detail of modern IT infrastructure.