Enhancement of Containerization-based Cloud Computing Performance using Hybrid Metaheuristic Optimization Algorithm: A Review

Enhancement of Containerization-based Cloud Computing Performance using Hybrid Metaheuristic Optimization Algorithm: A Review

연구 분야: Software Development

학회: 2025 International Conference on Electronics and Renewable Systems (ICEARS)

Container-based virtualisation has become a cornerstone of Cloud Computing (CC) due to its lightweight and scalable properties when compared to traditional virtual machines. However, it is still difficult to optimising resource allocation in containerised systems, and current approaches frequently fall short in addressing problems like high computational costs, scalability, cold-start scenarios, and Graphics Processing Unit (GPU) management. Container resource allocation is critical for effectively managing computing workloads in cloud settings, enabling scalability, performance optimization, and cost effectiveness. It is extensively used in a various industry, including e-commerce, healthcare, and finance, where dynamic workloads call for efficient resource management. Traditional resource allocation techniques, while their importance, frequently face difficulties such as unequal load distribution and resource underutilization. To address these constraints, this paper suggests a hybrid metaheuristic optimization algorithm that addresses limitations such as network distance, execution time, and migration costs to provide balanced load distribution. This study attempts to analyse the efficiency, time consumption and latency of resource allocation in dynamic cloud systems by addressing existing limitations.