Spread Scheduling Strategy In Docker Container Using Meta-Heuristic Optimization

Abstract

In recent time, spread scheduling plays a major role in docker swarm and it operates on a single objective in order to disseminate the containers for a service with possible nodes. However, if a node undergoes overloading or underloading, a fault-tolerant engine is always considered reliable. Such failure of nodes should be addressed in a faster manner in a cluster of nodes to carry out the operations in docker container. In this paper, we propose a new spread scheduling strategy using a meta-heuristic optimization that will solve the problem and no node will be overloaded and underloaded after failure of nodes in cluster. The study takes into consideration, the constraints associated with scheduling and clusters the priority task in the docker and enables optimal scheduling. The simulation is conducted to study the efficacy of the model in terms of various parameters that includes resource cost, execution time and energy consumption.