Edge Computing Management With Collaborative Lazy Pulling for Accelerated Container Startup

With the growing demand for latency-sensitive applications in 5G networks, edge computing has emerged as a promising solution. It enables instant response and dynamic resource allocation based on real-time network information by moving resources from the cloud to the network edge. Containers, known for their lightweight nature and ease of deployment, have been recognized as a valuable virtualization technology for service deployment. However, the prolonged startup time of containers can lead to long response time, particularly in edge computing scenarios characterized by long propagation time, frequent deployment, and migration. In this paper, we comprehensively consider image caching, container assignment, and registry selection problem in an edge system. To our best effort, there is no existing work that has taken all the above aspects into account. To address the problem, we propose a novel image caching strategy that employs partial caching, allowing local registries to cache either the least functional or complete version of application images. In addition, a container assignment and registry selection problem is solved by using an edge-based collaborative lazy pulling algorithm. To evaluate the performance of our proposed algorithms, we conduct experiments with real-world app usage data and popular images in a testbed environment. The experimental results demonstrate that our algorithms outperform traditional greedy algorithms in terms of average user response time and cache hit rate.