In the progressive disaster scenario where multiple nodes and links are sequentially disrupted with different early warning times, real-time data backup is a critical concern to improve the survivability of a geo-distributed DCN (Geographically distributed Data Center Network). We consider this problem by assuming that different disaster-covered DCN nodes and links have different early warning times and different disaster-covered DCN nodes have distinct sets of backup nodes. Based on integer linear program (ILP), we first propose an optimal data backup scheme to maximize the total amount of data backup. This theoretically provides an upper bound on the total amount of data backup. Then, a heuristic (i.e., Amount-Based Algorithm) is developed to provide a time-efficient solution, in which an adjusting factor is introduced to deal with link bandwidth competitions among multiple disaster-covered DCN nodes. Furthermore, we give another way to increase the amount of data backup for DCN operators by adjusting the bandwidth distribution on the key link which is identified as the one that has the greatest impact on data backup. The extensive numerical results validate the proposed solutions under the progressive disaster scenario with different early warning times for different nodes and links.

在多个节点和链路以不同的预警时间顺序中断的渐进式灾难场景中，实时数据备份是提高地理分布式 DCN（地理分布式数据中心网络）的生存能力的关键问题。我们通过假设不同的灾难覆盖的 DCN 节点和链路具有不同的预警时间并且不同的灾难覆盖的 DCN 节点具有不同的备份节点集来考虑这个问题。基于整数线性规划（ILP），我们首先提出了一个最优的数据备份方案，以最大化数据备份的总量。这在理论上提供了数据备份总量的上限。然后，开发了一种启发式（即基于金额的算法）以提供一种省时的解决方案，其中引入了一个调整因子来处理多个灾难覆盖的 DCN 节点之间的链路带宽竞争。此外，我们还给出了另一种增加DCN运营商数据备份量的方法，即调整关键链路上的带宽分布，该关键链路被确定为对数据备份影响最大的那个。广泛的数值结果验证了在渐进式灾难场景下提出的解决方案，不同节点和链接具有不同的预警时间。