An Energy-Efficient Machine-Type Communication for Maritime Internet of Things

Abstract

The Internet of Things (IoT) is an enabler technology for smart maritime networks. Connected IoT systems require reliable machine-type communication (MTC). However, maritime MTC is facing several practical challenges including the wide-area coverage, ubiquitous connectivity, cost-effectiveness, and reliability. In this paper, we first present a novel wireless communications assisted unmanned aerial vehicles (UAVs) system for maritime MTC. In our approach, UAVs are deployed to provide wide-area coverage, while a network of connected buoys handles data transmission between the UAVs and the on-shore data fusion and control center (DFCC). We propose a handover decision method that eliminates unnecessary handover triggers; thus, reducing the overall energy consumption and ensuring seamless connectivity. We formulate the handover decision method as a constrained optimization problem of maximizing handover efficiency in terms of signal-to-noise ratio (SNR), available data rate, residual energy, and buffered data, by identifying the buoy offering optimal connectivity. The optimization problem is solved by a probabilistic based genetic algorithm (GA). We compare the proposed handover decision model with three benchmark scenarios to validate the performance gains achieved.