Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals

TL;DR

This paper develops a stochastic optimization framework to minimize the average age of information in a multi-source relaying system with resource constraints, using a CMDP approach and proposing an effective near-optimal policy.

Contribution

It formulates the AoI minimization as a constrained MDP, analyzes the policy structure, and proposes a near-optimal algorithm for resource-constrained multi-source relaying systems.

Findings

The proposed algorithm outperforms benchmarks in simulations.

Optimal policies have a switching-type structure.

The approach provides a systematic way to minimize AoI under constraints.

Abstract

We consider a multi-source relaying system where the sources independently and randomly generate status update packets which are sent to the destination with the aid of a bufferaided relay through unreliable links. We formulate a stochastic optimization problem aiming to minimize the sum average age of information (AAoI) of sources under per-slot transmission capacity constraints and a long-run average resource constraint. To solve the problem, we recast it as a constrained Markov decision process (CMDP) problem and adopt the Lagrangian method. We analyze the structure of an optimal policy for the resulting MDP problem that possesses a switching-type structure. We propose an algorithm that obtains a stationary deterministic near-optimal policy, establishing a benchmark for the system. Simulation results show the effectiveness of our algorithm compared to benchmark algorithms.