Exploring and Implementing Container Scheduling Methods: A Comparative Review and Practical Approach

Container-based virtualization has become prominent as lightweight virtualization due to its scalability, resource utilization, and portability, especially in microservices. Container scheduler plays an essential role in Container services to optimize performance to reduce the overall cost by managing load balancing. Although Containers serve a lot of benefits, resource allocation is one of the major concerns associated with Container technology. This paper systematically reviews the distinct scheduling techniques used for Containers in a cloud environment, where existing scheduling techniques and their shortcomings have been discussed in detail. In the review process, the various issues and challenges in the Container technology have been identified, and the same has been discussed in this paper. Based on crucial elements including different performance metrics like CPU utilization, memory utilization, load balancing, and many others, it gives an in-depth comparison of the existing scheduling techniques like Ant Colony Optimization(ACO), Particle Swarm Optimization(PSO), Bee Colony Optimization(BCO), Chicken Swarm Optimization(CSO) and Genetic Algorithm(GA) outlining their benefits and drawbacks. This study also proposes a hybrid framework for secure and efficient Container scheduling. This framework can be implemented in the future to provide better results compared to existing approaches.