LAUSR

The Internet of Things (IoT) evolving from the conventional wireless sensor networks (WSNs) with more smart sensors has attracted significant attention. As one of the most crucial metrics for evaluating the quality of service (QoS) of both IoT and WSNs, sensing coverage characterizes the monitoring status of a sensing field of interest. However, the existence of coverage holes will remarkably degrade the QoS of the IoT. Based on the novel confident information coverage (CIC) model, this paper provides an in-depth study on how to energy-efficiently heal the multimodal CIC holes (MCICH) in a narrowband IoT (NB-IoT)-enabled hybrid IoT deployed for radiological pollution monitoring, where both mobile and stationary sensors equip multimodal sensing units for sensing dissimilar multimodal physical attributes and the NB-IoT provides satisfied network connectivity. We pinpoint the MCICH healing (MCICHH) problem with the objective of energy-efficiently dispatching a series of multimodal mobile IoT sensors to the CIC holes such that the MCIC holes can be headed and the CIC performance can be satisfied. After proving the NP-completeness of MCICHH by reducing it to the set partition problem, we develop a family of effective heuristic schemes including the centralized-MCICHH, the distributed-MCICHH and random CIC hole healing, all of which target for efficiently healing the MCIC holes while minimizing the total moving energy consumption of the dispatched multimodal mobile sensors or maximizing the average remaining energy of the multimodal mobile sensors. Extensive experiments verify the effectiveness and practicality of the proposed schemes.