Age of Information in IoT Devices With Integrated Heterogeneous Sensors Under Slotted ALOHA

Abstract

Sensors deployed in environments transmit status update data using the slotted ALOHA for radio channel access. The age-of-information (AoI) metric, representing the time elapsed since the last data received by a destination (e.g., base station) was generated at a sender, quantifies data freshness, which is crucial in diverse Internet of Things (IoT). Recent advancements have integrated heterogeneous sensors into IoT devices, with each sensor potentially sensing and generating status updates with different probabilities, impacting both AoI and energy consumption levels. This creates a complex challenge in balancing tradeoffs among various sensors’ sensing probabilities, AoI constraints, and energy efficiency. Yet, the AoI impact of IoT devices equipped with heterogeneous sensors using slotted ALOHA remains largely unexplored. This study investigates the AoI performance of IoT devices equipped with heterogeneous sensors within a slotted ALOHA framework. We present three data generation and transmission schemes: multisensor device with independent sensing (MSDIS), multisensor device with simultaneous sensing (MSDSS), and multisensor device with probabilistic simultaneous sensing (MSDPSS). We analyze and prove that MSDSS and MSDPSS achieve a lower average AoI (AAoI) compared with other schemes. Furthermore, we show that AAoI solutions for systems with at least five sensors per type cannot be expressed in radical form. Hence, we further design a low-time-complexity procedure for MSDPSS to determine optimal data sensing and generation probabilities that meet diverse AAoI requirements of various sensors while minimizing energy consumption. Our analysis, validated by simulations, indicates that MSDPSS demonstrates superior energy efficiency while meeting the diverse AAoI requirements of various sensors.