Measured Age of Information on real Internet and local Wi-Fi IoT testbeds and derived how synchronization bias shifts average age under linear, exponential, and logarithmic penalties.
Age of Information: The Gamma Awakening
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abstract
We consider a scenario where a monitor is interested in being up to date with respect to the status of some system which is not directly accessible to this monitor. However, we assume a source node has access to the status and can send status updates as packets to the monitor through a communication system. We also assume that the status updates are generated randomly as a Poisson process. The source node can manage the packet transmission to minimize the age of information at the destination node, which is defined as the time elapsed since the last successfully transmitted update was generated at the source. We use queuing theory to model the source-destination link and we assume that the time to successfully transmit a packet is a gamma distributed service time. We consider two packet management schemes: LCFS (Last Come First Served) with preemption and LCFS without preemption. We compute and analyze the average age and the average peak age of information under these assumptions. Moreover, we extend these results to the case where the service time is deterministic.
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Towards AoI-aware Smart IoT Systems
Measured Age of Information on real Internet and local Wi-Fi IoT testbeds and derived how synchronization bias shifts average age under linear, exponential, and logarithmic penalties.