Internet-of-Things in Motion: A Cooperative Data Muling Model for Public Safety

Abstract

In emerging Internet-of-Things (IoT) scenarios, a team of drones can be tasked to collect data at specific locations of interest, ferry it to remote places where a cloud infrastructure is used for sharing the collected data as a service to the community. In such an "Internet-of-Things in motion" scenario, terrain modeling, path finding, fair task allocation are key parameters upon which a successful mission depends. This paper describes a model developed to control a team of drones in order to cover irregular areas of uneven terrain. The model is based on an auction-based algorithm to coordinate the team of drones, relies on a 3D landscape model for path allocation. Experiments were conducted to assess the field readiness of the drone technology, simulated experiments were carried out to determine the relative eciency, the fairness of work allocation of the proposed model.