In the emerging field of the Internet of Things (IoT), Wireless Sensor Networks (WSNs) have a key role to play in sensing and collecting measures on the surrounding environment. In the deployment of large scale observation systems in remote areas, when there is not a permanent connection with the Internet, WSNs are calling for replication and distributed storage techniques that increase the amount of data stored within the WSN and reduce the probability of data loss. Unlike conventional network data storage, WSN-based distributed storage is constrained by the limited resources of the sensors. In this paper, we propose a low-complexity distributed data replication mechanism to increase the resilience of WSNbased distributed storage at large scale. In particular, we propose a simple, yet accurate, analytical modeling framework and an extensive simulation campaign, which complement experimental results on the SensLab testbed. The impact of several key parameters on the system performance is investigated.
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