Low-Complexity Data Collection Scheme for UAV Sink Nodes in Cellular IoT Networks

Abstract

Owing to the nature of battery-operated sensors, the residual energy of their battery should be considered when a sink node collects sensory data from them. If a sink attempts to collect data from a sensor that does not have sufficient residual energy to transmit data, the utilization of wireless communication resources may be degraded. However, requiring a periodic residual energy report of the sensors considerably reduces the energy efficiency of them. Consequently, the sink node must be able to estimate the residual energy of the sensors without additional information exchange before attempting to collect data. To tackle this problem, we propose a data collection scheme for mobile sinks in cellular Internet-of-things (IoT) networks. The scheme consists of two phases. In the first phase, the mobile sink estimates the residual energy of the surrounding sensors. To reduce the complexity, we design a state diagram composed of three states based on the Markov chain of the sensor. The sink node calculates the communicable likelihood of each sensor based on the state diagram and collects data from the sensor with the highest likelihood. In the second phase, a cellular base station (BS) selects the appropriate mobile sink to improve the signal-to-interference-plus-noise ratio (SINR) of the signal from a cellular user. Each sink node delivers the bidding price to the BS based on the likelihoods of the sensors. The BS determines an appropriate sink node to allocate resources based on the received bidding prices. Moreover, we show the performance of the proposed method in terms of SINR and IoT network utilization through simulation.