Information Freshness-Guaranteed and Energy-Efficient Data Generation Control System in Energy Harvesting Internet of Things

Abstract

In energy harvesting Internet of Things (IoT) systems, the age of information (AoI) should be maintained at a low level to guarantee the accuracy and reliability of derived decisions. In this paper, we design an information freshness-guaranteed and energy-efficient data generation control system (IFE-DGCS) where an IoT gateway with a directional antenna determines the polling frequency for each sector by selecting a polling sector at periodic decision epochs. When polling data, the IoT gateway transfers the RF energy to IoT devices in the polling sector by means of simultaneous wireless information and power transfer (SWIPT). To minimize the energy outage probability while maintaining the AoI below a certain level, a constrained Markov decision process (CMDP) is formulated and the optimal stochastic policy on the polling sector is obtained by a linear programming (LP). To resolve the curse of the dimensionality problem in CMDP, a greedy IFE-DGCS is developed and its performance is extensively studied. Evaluation results demonstrate that IFE-DGCS with the optimal policy achieves a comparable energy outage probability to the conventional energy-oriented scheme while guaranteeing a sufficiently low AoI.

Keywords

• Constrained Markov decision process
• energy harvesting
• the Internet of Things
• age of information
• information freshness