Distributed partition detection and recovery using UAV in wireless sensor and actor networks

Abstract

Wireless Sensor and Actor Networks (WSANs) have been extensively employed in various domains ranging from elementary data collection to real-time control and monitoring for critical applications. Network connectivity is a vital robustness measure for overall network performance. Different network functions such as routing, scheduling, and QoS provisioning depends on network connectivity. The failure of articulation points in the network disassociates the network into disjoint segments. In this paper, we target the network partition problem and propose a Partition Detection and Recovery using Unmanned Aerial Vehicle algorithm (DPDRU) to recover the partitioned network. It consists of three steps: Initialization, Operational and Detection, and Recovery. In the Initialization phase, sink node collects all the information about the network. In the second phase, i.e. Operational and Detection phase, network nodes communicate regularly by exchanging HEARTBEATS, detects failure, if some nodes do not get a message from the neighbor node and send failure reports, and sink node identifies the network partition problem. In the recovery phase, the sink node sends Unmanned Aerial Vehicle (UAV) at the positional coordinates of the failed node for placing the node for recovery. Our approach primarily focusses on reducing message overhead by sending few update messages to sink node and energy consumption by engaging network nodes only for communication purposes. The requirements for the recovery process i.e., physical movement and communication are fulfilled by UAV. The algorithm is tested according to parameters: Detection Time, Recovery Time, message overhead, and distance traveled by UAV. Simulation results validate the efficacy of the proposed algorithm based on these parameters to provide reliable results.