Peak Age of Information Distribution for Edge Computing with Wireless Links

Age of Information (AoI) is a critical metric for several Internet of Things (IoT) applications, where sensors keep track of the environment by sending updates that need to be as fresh as possible. The development of edge computing solutions has moved the monitoring process closer to the sensor, reducing the communication delays, but the processing time of the edge node needs to be taken into account. Furthermore, a reliable system design in terms of freshness requires the knowledge of the full distribution of the Peak AoI (PAoI), from which the probability of occurrence of rare, but extremely damaging events can be obtained. In this work, we model the communication and computation delay of such a system as two First Come First Serve (FCFS) queues in tandem, analytically deriving the full distribution of the PAoI for the M/M/1 - M/D/1 and the M/M/1 - M/M/1 tandems, which can represent a wide variety of realistic scenarios.Comment: Preprint version of the paper accepted for publication in the Transactions on Communication

Towards AoI-aware Smart IoT Systems

Age of Information (AoI) has gained importance as a Key Performance Indicator (KPI) for characterizing the freshness of information in information-update systems and time-critical applications. Recent theoretical research on the topic has generated significant understanding of how various algorithms perform in terms of this metric on various system models and networking scenarios. In this paper, by the help of the theoretical results, we analyzed the AoI behavior on real-life networks, using our two test-beds, addressing IoT networks and regular computers. Excessive number of AoI measurements are provided for variations of transport protocols such as TCP, UDP and web-socket, on wired and wireless links. Practical issues such as synchronization and selection of hardware along with transport protocol, and their effects on AoI are discussed. The results provide insight toward application and transport layer mechanisms for optimizing AoI in real-life networks

Measuring age of information on real-life connections

Age of Information (AoI) is a relatively new metric to measure freshness of networked application such as real-time monitoring of status updates or control. The AoI metric is discussed in the literature mainly in a theoretical way. In this work, we want to point out the issues related to the measuring AoI-related values, such as synchronization and calculation of the values. We discussed the effect of synchronization error in the measurement and a solution for calculating an estimate of average AoI without any synchronization