Power Minimization in Wireless Sensor Networks With Constrained AoI Using Stochastic Optimization

TL;DR

This paper proposes a stochastic optimization approach to minimize power consumption in wireless sensor networks while maintaining a constrained Age of Information (AoI), balancing energy efficiency and data freshness.

Contribution

It introduces a joint optimization framework for sampling, power allocation, and subchannel assignment using Lyapunov methods to control AoI and power constraints.

Findings

The proposed algorithm effectively reduces power consumption.

The method maintains AoI constraints under various system parameters.

Numerical results validate the approach's efficiency.

Abstract

In this paper, we consider a system where multiple low-power sensors communicate timely information about a random process to a sink. The sensors share orthogonal subchannels to transmit such information in the form of status update packets. Freshness of the sensors' information at the sink is characterized by the Age of Information (AoI), and the sensors can control the sampling policy by deciding whether to take a sample or not. We formulate an optimization problem to minimize the time average total transmit power of sensors by jointly optimizing the sampling action of each sensor, the transmit power allocation, and the subchannel assignment under the constraints on the maximum time average AoI and maximum power of each sensor. To solve the optimization problem, we use the Lyapunov drift-plus-penalty method. Numerical results show the performance of the proposed algorithm versus the different parameters of the system.