Improving Makespan in Dynamic Task Allocation for Cloud Robotic Systems with Time Window Constraints

A scheduling method in a robotic network cloud system with minimal makespan is beneficial because the system can complete all tasks assigned to it in the fastest way. Robotic network cloud systems can be translated into graphs, where nodes represent hardware with independent computing power and edges represent data transmissions between nodes. Time-window constraints on tasks are a natural way to order tasks. The makespan is the maximum amount of time between when a node starts executing its first scheduled task and when all nodes have completed their last scheduled task. The load balancing scheduling ensures that the time between when the first node completes its scheduled tasks and when all other nodes complete their scheduled tasks is as short as possible. We propose a new load balancing algorithm for task scheduling with minimal makespan. We prove the correctness of the proposed algorithm and present simulations illustrating the obtained results.