DRAW: data replication for enhanced data availability in IoT-based sensor systems

Abstract

internet of Things (IoT) technology is gaining increasing popularity with the ubiquity of the internet. It has the potential to connect real-world physical objects to the internet to make them readily accessible to users by deploying Wireless Sensor Networks (WSNs). However, WSNs face various challenges due to the nature of deployment and limited resources of sensor nodes. WSNs may also suffer from node failures as well as local memory shortages which result in significant amount of data loss. Data replication is a promising technique to preserve valuable sensed data in the network. in this paper, we propose DRaW, A fully distributed hop-by-hop data replication technique for IoT-based wireless sensor systems. DRaW ensures maximum data availability under high node failures to preserve data. Our extensive simulation results show that compared to a state-of-the-art technique, DRaW improves data availability and average replicas created in the network with a maximum gain of about 15% and 18%, respectively. Furthermore, DRaW provides a better replica spread which determines the quality of data dissemination in the network.