Data recovery after geographic correlated attacks

In distributed storage networks, ensuring data availability in the presence of hardware faults is an important requirement. Typically, redundancy schemes such as replication and erasure coding are used to ensure this. In case of hardware failures, these networks may be disconnected into multiple components, each of which may require access to the data. In addition, the placement of redundant information must also be optimized as it is ever-changing and requires constant updating. We study the problem of selecting a set of nodes in networks of this kind so that data availability is maintained in the face of geographically correlated failures. We model failure events of arbitrary shapes as the union of disks or line segments in the plane and present approximation algorithms for the problem of selecting a minimum number of redundant information locations (such as replicas or coded file segments) so that data recovery is guaranteed at every node in the face of any failure event. Using tools from computational geometry, our algorithms are efficient and provide good guarantees.