Dynamic Task Scheduling for Digital Twins to Meet Telesurgery Real-Time Requirements

Recent developments in 6G technology are projected to revolutionize applications with stringent real-time requirements, such as telesurgery. This paper presents a novel approach for supporting real-time decision-making in remote surgery by leveraging digital twins to overcome distance barriers. We address the communication challenges inherent to telesurgical digital twins and introduce an end-to-end formulation of data synchronization using Integer Linear Programming (ILP). We propose various grouping strategies for critical surgical tasks to support dynamic task scheduling within the telesurgical digital twin environment. These strategies include Interrelated Dependency (IRD), Highest Priority-Nearest Deadline (HPND), Shortest Transmission Time (STT), and Shortest Validity Time (SVT). We apply the knapsack approach to optimize task scheduling, aiming to maximize the sum of task priorities while minimizing the number of tasks that miss their deadlines. Performance evaluation shows that the HPND grouping strategy yields better results than other grouping strategies across key performance metrics, including transmitted task size, task priorities, and the reduction of tasks that miss their deadlines.