Data preservation under spatial failures in sensor networks

In this paper, we address the problem of preserving generated data in a sensor network in case of node failures. We focus on the type of node failures that have explicit spatial shapes such as circles or rectangles (e.g., modeling a bomb attack or a river overflow). We consider two different schemes for introducing redundancy in the network, by simply replicating data or by using erasure codes, with the objective to minimize the communication cost incurred to build such data redundancy. We prove that the problem is NP-hard using either replication or coding. We design O(α)-approximation centralized and distributed algorithms for the two redundancy schemes, where α is the "fatness" of the potential node failure events. Using erasure codes, data distribution can be handled in an efficient distributed manner. Simulation results show that by exploiting the spatial properties of the node failure patterns, one can substantially reduce the communication cost compared to the resilient data storage schemes in the prior literature.