Optimal Condition‐Based Backup and Mission Abort Decisions for Cloud Computing Systems
Qingan Qiu, Bosen Liu, Cuicui Pei, Rongchi Sun, Xian Zhao
Abstract
ABSTRACT This study addresses the growing safety challenges associated with data transmission and processing in cloud computing systems, particularly in light of their vulnerability to external shocks such as hacker attacks. We introduce risk control strategies that focus on condition‐based data backup and mission abort decisions. We establish a mission abort threshold based on the number of shocks specific to cloud computing systems engaged in data transmission, aiming to reduce the risk of system failures. Before executing a mission abort decision, we propose a condition‐based backup strategy that triggers data backup once the transmitted data reaches a predefined threshold, thus mitigating the risk of data loss. Within the framework of the integrated backup and mission abort strategies, we evaluate critical system performance metrics, including mission success probability (MSP) and expected total costs, utilizing a recursive method. Optimization of integrated backup and mission abort policies seeks to minimize expected total costs associated with system failures, mission failures, data backups, and data loss. To validate the effectiveness of our proposed strategies, we conduct a comprehensive numerical example, demonstrating that the implementation of condition‐based backup and abort thresholds can significantly reduce expected costs and enhance MSP.