The field of cloud computing and edge computing is moving towards optimizing resource allocation and utilization. Researchers are exploring new policies and frameworks for dynamic server allocation, containerized service delivery, and automated algorithm selection to improve performance and reduce costs. A key focus area is the development of stability-aware and adaptive systems that can handle dynamic workloads and volatile conditions. Another important trend is the integration of machine learning and artificial intelligence to predict performance, optimize resource usage, and improve decision-making. Noteworthy papers in this area include:

• Accelerating Containerized Service Delivery at the Network Edge, which presents a decentralized P2P-based system for optimizing image distribution in edge environments.
• SAM: A Stability-Aware Cache Manager for Multi-Tenant Embedded Databases, which introduces a novel autonomic cache manager powered by a dual-factor model that achieves sustained high performance through strategic stability and robustness.