BESDDFFS: Blockchain and EdgeDrone based secured data delivery for forest fire surveillance

Forest fires have been disastrous to civilizations since time immemorial causing damage to life and property. The human civilization has lived with a pressing need to devise a method to quickly detect and safely transmit fire alerts to minimize losses. This work presents a novel framework for Blockchain and EdgeDrone based Secured Data Delivery for Forest Fire Surveillance (BESDDFFS). A detailed three-layer edge computing architecture is proposed consisting of IoT Layer (wireless network Drones deployed in the forest), the Edge Layer (a Local Processing and Routing Station located at the edge of the IoT network) and a Cloud Server communicating continuously with the Edge Layer. The integration of an edge computing paradigm within a Blockchain setting thereby attaining enhanced levels of security and performance is a defining attribute of this work. Extensive experimentation has been undertaken at software and hardware experimental setups to gauge the efficacy of the proposed architecture. An energy-efficient prospective Leader selection algorithm is proposed as energy conservation is a crucial issue in a resource-constrained wildfire IoT environment. Moreover, an optimal and dynamic drone trajectory algorithm is also proposed to minimize energy consumption. The proposed BESFFSS architecture is compared with baseline algorithms of state-of-the-art approaches. A detailed analysis of QoS parameters reveals that the proposed system achieves up to 66% lesser delay, 36% greater throughput and a 12% greater ratio of successfully delivered packets. The proposed Leader selection (PRELS) algorithm achieves 0.5% lesser energy consumption per node and requires 8.6% lesser time to perform a fair selection of a Leader in a zone.