Interval graph multi-coloring-based resource reservation for energy-efficient containerized cloud data centers

Containerized deployment of microservices has quickly become a well-known virtualization technology due to its higher portability, scalability, good isolation, and lightweight solutions. However, it faces several challenges in terms of the capital and operational expenses in large-scale data centers. In particular, services in cloud are usually instantiated as a group of containers, which continuously trigger frequent communication workloads and hence significantly degrades the service performance due to inefficient allocation of containers. Thus to deploy microservices, service providers must consider different types of objectives, such as optimizing the communication cost or the operational cost, which are joint objectives that have previously been studied independently. In this paper, we study the problem of communication-aware container-based advance reservation to optimize the energy and communication cost for microservices deployment. We applied the interval graph model to map the container reservation scenario of microservices and derived various performance bounds. Then, we propose greedy graph multi-coloring-based centralized and distributed algorithms to find an efficient allocation of containers. Through theoretical analysis and extensive experimental results, we demonstrate that the proposed approaches can decrease the total cost by up to 31% compared to the current state-of-the-art methods.