A Novel Methodology for Container Scheduling and Load Balancing in Distributed Environments

Deployment of applications in distributed environments via containers has gained huge popularity lately, specifically with cloud-based ecosystems. Inspired by the quick growth of container usage and deployment in distributed environments, efficient scheduling techniques are of prior significance embedded with load balancing in it for cloud computing tasks. Most of the scheduling strategies adopt conventional methods and fail to execute efficiently in the dynamic cloud or distributed environments where applications around the world depend on them for scalability, efficiency, and availability. Existing applications focus more on performance metrics instead of scheduling efficiency, so often they offer performance that can come at the expense of scheduling. This paper proposes a new algorithm that includes consideration of contention over the network, along with efficient canister planning and load distribution. The algorithm we have designed to achieve the proposed scheduling and load balancing is Contention-aware Greedy Heuristic Scheduling and Load Balancing for Containers (CGHSLBC), which has been extensively evaluated under continuous workload and has outperformed current state-of-the-art algorithms by 20% in load balancing efficiency and 25% in network contention reduction, demonstrating its promise for container scheduling in dynamic distributed environments.