Abstract
After many devices that have adopted LTE technology, it is optimistic to presume that 5G technology will have to address the huge traffic of data and volume of heterogeneous devices in future. Existing context-aware Internet of Things (IoT) applications directly control sensors on LTE devices in an uncoordinated and non-optimized manner, which leads to redundant sensor activations and energy wastage on resource-constrained IoT devices. Optimal and coordinated sensor usage dictates a comprehensive middleware solution to bring together the information from all IoT applications/sensors and intelligently select the best set of sensors to activate. In this paper, we design, implement, and evaluate a sensor management middleware for LTE devices that controls the tradeoff between energy consumption of sensors and accuracy of inferred contexts. The core task of this middleware is to minimize total energy consumption while making sure that the accuracy requested by IoT applications are met. Trace-driven simulations are conducted to demonstrate the merits of the proposed middleware and algorithms. The simulation results indicate that the proposed algorithms clearly outperform the current solution.