  This paper investigates the benefits of integrating multiple reconfigurable
intelligent surfaces (RISs) in enhancing the timeliness performance of uplink
Internet-of-Things (IoT) network, where IoT devices (IoTDs) upload their
time-stamped status update information to a base station (BS) using
non-orthogonal multiple access (NOMA). Accounting to the potential unreliable
wireless channels due to the impurities of the propagation environments, such
as deep fading, blockages, etc., multiple RISs are deployed in the considered
IoT network to mitigate the propagation-induced impairments, to enhance the
quality of the wireless links, and to ensure that the required freshness of
information is achieved. In this setup, an optimization problem has been
formulated to minimize the average sum Age of Information (AoI) by optimizing
the transmit power of the IoTDs, the IoTDs clustering policy, and the RISs
configurations. The formulated problem ends up to be a mixed-integer non-convex
problem. In order to tackle this challenge, the RISs configurations are first
obtained by adopting a semi-definite relaxation (SDR) approach. Then, the joint
power allocation and user-clustering problem is solved using the concept of
bi-level optimization, where the original problem is decomposed into an outer
IoTDs clustering problem and an inner power allocation problem. Optimal
closed-form expressions are derived for the inner problem and the Hungarian
method is invoked to solve the outer problem. Numerical results demonstrate
that our proposed approach achieves lowest AoI compared to the other baseline
approaches.
