Energy-Constrained Data Freshness Optimization in Self-Powered Networked Embedded Systems

Abstract

This article explores how to optimize the freshness of real-time data for energy harvesting (EH)-based networked embedded systems (NESs) with energy constraints. We introduce the concept of age of information (AoI) to quantitatively measure the data freshness and present a comprehensive analysis on the average AoI of the real-time data with stochastic update arrival and energy replenishment patterns for single-source EH-based systems. An optimal offline solution and an effective online solution are designed to select a sequence of real-time data updates (while discarding the remaining ones) and determine their corresponding transmission time to minimize the average AoI. We further extend these findings to multisource EH-based NESs, and present an optimal offline solution and an efficient online solution to schedule updates for each data source to optimize the average AoI. The correctness of the analysis and the effectiveness of the proposed solutions have been validated through extensive experiments by comparing to the state-of-the-art methods. According to the experimental results, the proposed solutions reduce the average AoI by 47.2% and 69.1% on average comparing to the state-of-the-art solutions for single-source and multisource EH-based NESs, respectively, with low harvesting rates.