New Scheduling Strategy Based on Multi-Criteria Decision Algorithm

This paper presents a new scheduling strategy proposed to optimize the scheduling of several containers submitted online by users in a private infrastructure of nodes i.e. a cloud platform. In the literature, several scheduling frameworks and studies are proposed. The majority of these works use a scheduling strategy based on one criterion, such as Spread and Bin Packing strategies. The Spread strategy consists to select the node having the least number of executed containers to balance the containers load between all nodes of the infrastructure. The Bin Packing strategy consists to select the most compacted node in terms of resources to reduce the number of used nodes of the infrastructure. However, the submitted containers are defined according to a multi-criteria, such as the number of used CPUs and the used memory size. The state of each node is also defined according to a multi-criteria, such as the number of executed containers, the number of available CPUs and the size of available memory. The novelty of our scheduling strategy is to choose the node that executes a container by combining the Spread and the Bin Packing principles using the Technique for the Order of Prioritisation by Similarity to Ideal Solution (TOPSIS) algorithm. TOPSIS is a multi-criteria decision analysis algorithm. Our proposed strategy is implemented in Docker Swarm. Docker swarm is an important container scheduler framework developed by Docker. Experiments demonstrate the potential of our strategy under different scenarios.