Minimizing Age of Information in Energy Harvesting Wireless Sensor Networks

Hiroki Iimori,Koji Ishibashi,Naoya Hirosawa,Giuseppe Thadeu Freitas De Abreu

doi:10.1109/access.2020.3038954

Hiroki Iimori, Koji Ishibashi + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.3038954

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Abstract

We consider the uplink of an energy harvesting (EH) wireless sensor network (WSN) where N single-antenna sensors communicate with a common fusion center (FC) with the aim of cooperatively minimizing the overall average age of information (AoI). Specifically, we propose new resource allocation algorithms to minimize the average AoI in an EH-WSNs employing common multiple-access schemes, in particular time-division multiple access (TDMA) and frequency-division multiple access (FDMA). To this end, we take advantage of the convexity of the derived AoI, enabling an optimal resource block assignment, implemented as a greedy algorithm for TDMA systems and in the form of an alternating direction method of multipliers (ADMM) scheme for FDMA systems. The optimality of the greedy resource allocation scheme derived for the TDMA case is obtained by design, whereas that of the ADMM-based method derived for the FDMA case is demonstrated numerically. Simulation results indicate that the choice between TDMA or FDMA depends on the available resources, size of the data packet, and the time of packet observation in the system.

Highlights

O WING to the latest advances in sensing and data transmission technologies, various monitoring services employing wireless sensor networks (WSNs) have been proposed over the years to solve problems in domains such as transportation [2], health [3], and the environment [4], culminating with the notion of digital twins (DTs) [5], [6].Digital twins are digital representations of physical devices or systems based on data collected in real time, which continuously track physical changes in the devices/systems while forecasting possible future states of the corresponding physical components
Considering that practical DT-WSN scenarios rely on multiple SNs communicating with a common fusion center (FC), we argue that in order to address the DT case, contributions such as those of [32]–[37] need to be generalized, in particular toward the design of optimal resource allocation handling multiple SNs, aimed at minimizing the average age of information (AoI) under battery-constrained conditions
In this article, we focus on the latter concurrent timing approach, in which the multi-access scheme employed has a greater impact, especially in the context of energy harvesting (EH) networks, as it affects both the time SNs must wait from the moment data is collected until they can transmit in the case of time-division multiple access (TDMA) schemes, as well as the time available for EH nodes to gather sufficient energy to transmit, in the case of an frequency-division multiple access (FDMA) scheme

Summary

Introduction

O WING to the latest advances in sensing and data transmission technologies, various monitoring services employing wireless sensor networks (WSNs) have been proposed over the years to solve problems in domains such as transportation [2], health [3], and the environment [4], culminating with the notion of digital twins (DTs) [5], [6].Digital twins are digital representations of physical devices or systems based on data collected in real time, which continuously track physical changes in the devices/systems while forecasting possible future states of the corresponding physical components. O WING to the latest advances in sensing and data transmission technologies, various monitoring services employing wireless sensor networks (WSNs) have been proposed over the years to solve problems in domains such as transportation [2], health [3], and the environment [4], culminating with the notion of digital twins (DTs) [5], [6]. Given that a very large number of devices may be connected to feed a DT, the corresponding data must be collected in a distributed and reliable fashion. These requirements can be satisfied by energy harvesting (EH) WSNs, well known for their self-reliance and low-maintenance characteristics. Networking protocols specific for EH-WSNs have been developed [13]–[17], which contribute to the reliability of such systems

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